A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

        1 2 | Last   [Sort alphabetically]   [Restore default list]

  Subjects -> ARCHITECTURE (Total: 219 journals)
Showing 1 - 200 of 264 Journals sorted by number of followers
Modernism/modernity     Full-text available via subscription   (Followers: 44)
American Journal of Civil Engineering and Architecture     Open Access   (Followers: 41)
Environment and Planning B : Urban Analytics and City Science     Full-text available via subscription   (Followers: 40)
Architectural Design     Hybrid Journal   (Followers: 33)
Civil Engineering and Architecture     Open Access   (Followers: 32)
European Planning Studies     Hybrid Journal   (Followers: 24)
Architectural Heritage     Hybrid Journal   (Followers: 24)
A+BE : Architecture and the Built Environment     Open Access   (Followers: 24)
Architecture and Culture     Hybrid Journal   (Followers: 22)
Interiors : Design, Architecture and Culture     Hybrid Journal   (Followers: 22)
Sustainable Cities and Society     Hybrid Journal   (Followers: 22)
Journal of Architecture and Urbanism     Open Access   (Followers: 22)
Architecture and Urban Planning     Open Access   (Followers: 21)
Grey Room     Hybrid Journal   (Followers: 20)
Architecture Research     Open Access   (Followers: 20)
Urban Research & Practice     Hybrid Journal   (Followers: 20)
Journal of Landscape Architecture     Hybrid Journal   (Followers: 19)
Landscapes     Hybrid Journal   (Followers: 18)
Cities in the 21st Century     Open Access   (Followers: 18)
Architectural Review     Full-text available via subscription   (Followers: 17)
Journal of Medieval Latin     Full-text available via subscription   (Followers: 16)
Journal of Urban Cultural Studies     Hybrid Journal   (Followers: 16)
City, Territory and Architecture     Open Access   (Followers: 16)
The Journal of Architecture     Hybrid Journal   (Followers: 15)
Environmental Science and Sustainable Development : International Journal Of Environmental Science & Sustainable Development     Open Access   (Followers: 14)
Design Ecologies     Hybrid Journal   (Followers: 13)
International Journal of Islamic Architecture     Hybrid Journal   (Followers: 13)
Buildings & Landscapes: Journal of the Vernacular Architecture Forum     Full-text available via subscription   (Followers: 13)
Engineering, Construction and Architectural Management     Hybrid Journal   (Followers: 13)
Journal of Architecture, Planning and Construction Management     Open Access   (Followers: 12)
URBAN DESIGN International     Hybrid Journal   (Followers: 12)
Journal of Architectural Education     Hybrid Journal   (Followers: 12)
TECHNE - Journal of Technology for Architecture and Environment     Open Access   (Followers: 11)
Architectural Engineering and Design Management     Hybrid Journal   (Followers: 11)
Environnement Urbain / Urban Environment     Open Access   (Followers: 11)
Proceedings of the Institution of Civil Engineers - Urban Design and Planning     Hybrid Journal   (Followers: 11)
Architectural History     Hybrid Journal   (Followers: 10)
Town and Regional Planning     Open Access   (Followers: 10)
OASE Journal for Architecture     Open Access   (Followers: 9)
Places Journal     Open Access   (Followers: 8)
Artifact : Journal of Design Practice     Open Access   (Followers: 8)
Journal of architecture&ENVIRONMENT     Open Access   (Followers: 8)
Vernacular Architecture     Hybrid Journal   (Followers: 8)
Study of Civil Engineering and Architecture     Open Access   (Followers: 8)
Future Cities and Environment     Open Access   (Followers: 7)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 7)
Home Cultures     Full-text available via subscription   (Followers: 7)
Housing and Society     Hybrid Journal   (Followers: 6)
Ambiances     Open Access   (Followers: 6)
Architectural Engineering     Open Access   (Followers: 6)
ABE Journal : Architecture Beyond Europe     Open Access   (Followers: 6)
Apuntes : Revista de Estudios sobre Patrimonio Cultural - Journal of Cultural Heritage Studies     Open Access   (Followers: 6)
Journal of Architectural Conservation     Hybrid Journal   (Followers: 6)
Architectural Theory Review     Hybrid Journal   (Followers: 6)
Journal of the Warburg and Courtauld Institutes     Full-text available via subscription   (Followers: 6)
CLARA : Classical Art and Archaeology     Open Access   (Followers: 6)
Enquiry / The ARCC Journal of Architectural Research     Open Access   (Followers: 5)
Frontiers of Architectural Research     Open Access   (Followers: 5)
International Journal of the Built Environment and Asset Management     Hybrid Journal   (Followers: 5)
International Journal of Architectural Computing     Full-text available via subscription   (Followers: 5)
Architectural Science Review     Hybrid Journal   (Followers: 5)
Bulletin of Pridniprovsk State Academy of Civil Engineering and Architecture     Open Access   (Followers: 5)
Journal of Building Performance Simulation     Hybrid Journal   (Followers: 5)
Cities & Health     Hybrid Journal   (Followers: 5)
ARQ     Open Access   (Followers: 5)
Winterthur Portfolio     Full-text available via subscription   (Followers: 5)
DEARQ - Revista de Arquitectura / Journal of Architecture     Open Access   (Followers: 4)
South East European Journal of Architecture and Design     Open Access   (Followers: 4)
Dams and Reservoirs     Hybrid Journal   (Followers: 4)
Australian Journal of Civil Engineering     Hybrid Journal   (Followers: 4)
Architecture, Civil Engineering, Environment     Open Access   (Followers: 4)
Construction Robotics     Hybrid Journal   (Followers: 4)
International Journal of Protective Structures     Hybrid Journal   (Followers: 4)
Journal of Sustainable Architecture and Civil Engineering     Open Access   (Followers: 4)
Academia : Architecture and Construction     Open Access   (Followers: 4)
GRID - Architecture, Planning and Design Journal     Open Access   (Followers: 4)
Footprint : Delft Architecture Theory Journal     Open Access   (Followers: 4)
International Journal of Human Capital in Urban Management     Open Access   (Followers: 4)
Bulletin KNOB     Open Access   (Followers: 3)
Livraisons d’Histoire de l’Architecture     Open Access   (Followers: 3)
ArcHistoR     Open Access   (Followers: 3)
Terrain.org : A Journal of the Built & Natural Environments     Free   (Followers: 3)
BUILT : International Journal of Building, Urban, Interior and Landscape Technology     Open Access   (Followers: 3)
Smart Cities     Open Access   (Followers: 3)
MediaTropes     Open Access   (Followers: 3)
International Journal of Built Environment and Sustainability     Open Access   (Followers: 3)
Architecture and Engineering     Open Access   (Followers: 3)
A&P Continuidad     Open Access   (Followers: 2)
Frontiers in Sustainable Cities     Open Access   (Followers: 2)
Gazi University Journal of Science Part B : Art, Humanities, Design and Planning     Open Access   (Followers: 2)
Arena Journal of Architectural Research     Open Access   (Followers: 2)
Eurasian Journal of Civil Engineering and Architecture     Open Access   (Followers: 2)
International Journal of Landscape Planning and Architecture     Full-text available via subscription   (Followers: 2)
Nature : National Academic Journal of Architecture     Open Access   (Followers: 2)
Technical Report Civil and Architectural Engineering     Open Access   (Followers: 2)
project baikal : Journal of architecture, design and urbanism     Open Access   (Followers: 2)
Palimpsesto     Open Access   (Followers: 2)
FORMakademisk - forskningstidsskrift for design og designdidaktikk     Open Access   (Followers: 2)
Journal of Facade Design and Engineering     Open Access   (Followers: 2)
Charrette     Open Access   (Followers: 2)
Ángulo Recto. Revista de estudios sobre la ciudad como espacio plural     Open Access   (Followers: 2)
Arquitectura y Urbanismo     Open Access   (Followers: 2)
Fabrications: The Journal of the Society of Architectural Historians, Australia and New Zealand     Hybrid Journal   (Followers: 2)
Australian Planner     Hybrid Journal   (Followers: 2)
Arqueología de la Arquitectura     Open Access   (Followers: 2)
Revista de Urbanismo     Open Access   (Followers: 2)
Revista de Arquitectura     Open Access   (Followers: 1)
Estudios del Hábitat     Open Access   (Followers: 1)
Joelho : Journal of Architectural Culture     Open Access   (Followers: 1)
Architectural Research in Finland     Open Access   (Followers: 1)
Japan Architectural Review     Open Access   (Followers: 1)
Revista de Arquitectura e Ingenieria     Open Access   (Followers: 1)
AURUM : Mühendislik Sistemleri ve Mimarlık Dergisi = Aurum Journal of Engineering Systems and Architecture     Open Access   (Followers: 1)
Herança : Revista de História, Património e Cultura     Open Access   (Followers: 1)
In Situ. Revue des patrimoines     Open Access   (Followers: 1)
Boletín Académico. Revista de investigación y arquitectura contemporánea     Open Access   (Followers: 1)
Journal of Architectural / Planning Research and Studies     Open Access   (Followers: 1)
Journal of Architecture, Design and Construction     Open Access   (Followers: 1)
Journal of Environmental Design     Open Access   (Followers: 1)
Dibt Mitteilungen (Formerly-Mitteilungen Deut Inst Fuer Bautechnik)     Hybrid Journal   (Followers: 1)
disP - The Planning Review     Hybrid Journal   (Followers: 1)
étapes: international     Full-text available via subscription   (Followers: 1)
Journal of Architecture, Art & Humanistic Science     Open Access   (Followers: 1)
Épités - Épitészettudomány     Full-text available via subscription   (Followers: 1)
Journal of Persianate Studies     Hybrid Journal   (Followers: 1)
REUDAR : European Journal of Roman Architecture     Open Access   (Followers: 1)
Spool     Open Access   (Followers: 1)
ArDIn. Arte, Diseño e Ingeniería     Open Access   (Followers: 1)
ARQUISUR     Open Access   (Followers: 1)
Space Ontology International Journal     Open Access   (Followers: 1)
Tafter Journal     Open Access   (Followers: 1)
Der Architekt     Full-text available via subscription   (Followers: 1)
Forum Journal     Full-text available via subscription   (Followers: 1)
Thresholds     Hybrid Journal  
Re. Revista de Edificación     Open Access  
Technology|Architecture + Design     Hybrid Journal  
Journal of Asian Architecture and Building Engineering     Open Access  
EN BLANCO : Revista de Arquitectura     Full-text available via subscription  
VITRUVIO : International Journal of Architectural Technology and Sustainability     Open Access  
Porta Aurea     Open Access  
Undagi : Jurnal Ilmiah Arsitektur     Open Access  
International Journal of Architecture and Infrastructure Planning     Full-text available via subscription  
Montreal Architectural Review     Open Access  
Patrimoines du Sud     Open Access  
Vitruvian     Open Access  
Sens public     Open Access  
Journal of the Society for the Study of Architecture in Canada / Le Journal de la Société pour l'étude de l'architecture au Canada     Open Access  
Revista Geometria Gráfica     Open Access  
Construindo     Open Access  
Procesos Urbanos     Open Access  
PARC Pesquisa em Arquitetura e Construção     Open Access  
tecYt     Open Access  
De Res Architettura     Open Access  
Pensum     Open Access  
Revista de Investigación     Open Access  
Polis     Open Access  
Periodica Polytechnica Architecture     Open Access  
Les Cahiers de la recherche architecturale urbaine et paysagère     Open Access  
Elkawnie : Journal of Islamic Science and Technology     Open Access  
Riset Arsitektur     Open Access  
Loggia, Arquitectura & Restauración     Open Access  
Ars Longa : Cuadernos de arte     Open Access  
ZARCH : Journal of Interdisciplinary Studies in Architecture and Urbanism     Open Access  
Limaq     Open Access  
Mokslas – Lietuvos ateitis / Science – Future of Lithuania     Open Access  
Revista de Arquitectura     Open Access  
Ra : Revista de Arquitectura     Full-text available via subscription  
Módulo Arquitectura - CUC     Open Access  
Revista Amazônia Moderna     Open Access  
Continuité     Full-text available via subscription  
Eikonocity. Storia e Iconografia delle Città e dei Siti Europei - History and Iconography of European Cities and Sites     Open Access  
Ri-Vista : Ricerche per la progettazione del paesaggio     Open Access  
Opus Incertum     Open Access  
Firenze Architettura     Open Access  
Jurnal Arsitektur KOMPOSISI     Open Access  
Risco : Revista de Pesquisa em Arquitetura e Urbanismo     Open Access  
Revista Márgenes Espacio Arte y Sociedad     Open Access  
Panambí. Revista de Investigaciones Artísticas     Open Access  
Pós. Revista do Programa de Pós-Graduação em Arquitetura e Urbanismo da FAUUSP     Open Access  
Cuadernos de Proyectos Arquitectónicos     Open Access  
Cuaderno de Notas     Open Access  
Jurnal Teknik Sipil dan Perencanaan     Open Access  
Vivienda y Ciudad     Open Access  
Oculum Ensaios     Open Access  
Paranoá : cadernos de arquitetura e urbanismo     Open Access  
Paisagem e Ambiente     Open Access  
RevistArquis     Open Access  
Revista Arquitecturas del Sur     Open Access  
Room One Thousand     Open Access  
ESTOA Revista de la Facultad de Arquitectura y Urbanismo     Open Access  
VLC arquitectura. Research Journal     Open Access  
Revista AUS     Open Access  
HBRC Journal     Open Access  
Liño     Open Access  
Revista Hábitat Sustenable     Open Access  
EGA Expresión Gráfica Arquitectónica     Open Access  
Informes de la Construcción     Open Access  
Arquiteturarevista     Open Access  
Revista INVI     Open Access  
Bauregelliste A, Bauregelliste B Und Liste C     Hybrid Journal  

        1 2 | Last   [Sort alphabetically]   [Restore default list]

Similar Journals
Journal Cover
Environment and Planning B : Urban Analytics and City Science
Journal Prestige (SJR): 0.653
Citation Impact (citeScore): 2
Number of Followers: 40  
 
  Full-text available via subscription Subscription journal
ISSN (Print) 2399-8083 - ISSN (Online) 2399-8091
Published by Sage Publications Homepage  [1176 journals]
  • Using geographical random forest models to explore spatial patterns in the
           neighborhood determinants of hypertension prevalence across chicago,
           illinois, USA

    • Free pre-print version: Loading...

      Authors: Aynaz Lotfata, George Grekousis, Ruoyu Wang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      In the United States, the rise in hypertension prevalence has been connected to neighborhood characteristics. While various studies have found a link between neighborhood and health, they do not evaluate the relative dependence of each component in the growth of hypertension and, more significantly, how this value differs geographically (i.e., across different neighborhoods). This study ranks the contribution of ten socioeconomic neighborhood factors to hypertension prevalence in Chicago, Illinois, using multiple global and local machine learning models at the census tract level. First, we use Geographical Random Forest, a recently proposed non-linear machine learning regression method, to assess each predictive factor’s spatial variation and contribution to hypertension prevalence. Then we compare GRF performance to Geographically Weighted Regression (local model), Random Forest (global model), and OLS (global model). The results indicate that GRF outperforms all models and that the importance of variables varies by census tract. Household composition is the most important factor in the Chicago tracts, while on the other hand, Housing type and Transportation is the least important factor. While the household composition is the most important determinant around north Lake Michigan, the socioeconomic condition of the neighborhood in Chicago’s mid-north has the most importance on hypertension prevalence. Understanding how the importance of socioeconomic factors associated with hypertension prevalence varies spatially aids in the design and implementation of health policies based on the most critical factors identified at the local level (i.e., tract), rather than relying on broad city-level guidelines (i.e., for entire Chicago and other large cities).
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-20T11:42:55Z
      DOI: 10.1177/23998083231153401
       
  • Modeling land-use change using partitioned vector cellular automata while
           considering urban spatial structure

    • Free pre-print version: Loading...

      Authors: Jing Yang, Xinyu Zhu, Wei Chen, Yizhong Sun, Jie Zhu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      While many published studies have explored the impact of spatial heterogeneity on land-use change, few have focused on regional differences in land-use transition rules caused by urban spatial structure. In this paper, we measured urban land-use diversity by developing self-adaptive kernel density estimation and entropy weight methods and determine the urban spatial structure (composed of urban regions, inner and outer urban-rural fringes, and a rural hinterland) by applying a spectral clustering method. Combining local neighborhood effects and environmental effects, the land-use transition rules of different types of regions were mined to construct a partitioned vector cellular automata (CA) model that zonally simulates urban land-use change. The proposed model was applied to the simulation of the land-use change process in Jiangyin City, China, from 2007 to 2017. The resulting simulation accuracy was higher than that of other well-accepted CA models that do not consider urban spatial structure, and the conventional neighborhood assimilation rule was found not to be applicable to the conversion of construction land. The results and findings demonstrate that the proposed model is an effective means for urban planners to simulate and analyze urban evolution processes of cities with urban spatial structures that fit a concentric circle model.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-17T11:08:40Z
      DOI: 10.1177/23998083231152887
       
  • Visualizing the uneven accessibility to nucleic acid testing services in
           Shenzhen under China’s COVID control measures

    • Free pre-print version: Loading...

      Authors: Zifeng Chen
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Under China’s “dynamic zero” COVID-19 policy, Shenzhen required its residents to present a negative nucleic acid testing result within 24 or 48 h to access most public spaces and transit until most recently. The uneven accessibility to testing services could render certain groups vulnerable to mobility disadvantage (e.g., denied access to public transport). Using data of nucleic acid testing services and residents’ positioning points, I created a cartogram to capture the spatial distribution of people’s activities and that of testing services in Shenzhen. The cartogram indicates that the nucleic acid testing services were spatially concentrated in a way inconsistent with the distribution of people’s daily activities. Several girds exhibit high presence of activities but low or no provision of testing services that were necessary for residents to accessing public spaces and transport. The cartogram casts light to potential consequence of regular nucleic acid testing on mobility equality.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-17T06:08:41Z
      DOI: 10.1177/23998083231153402
       
  • Agglomeration effects as spatially embedded social interactions:
           identifying urban scaling beyond metropolitan areas

    • Free pre-print version: Loading...

      Authors: Deborah Strumsky, Luis Bettencourt, José Lobo
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Agglomeration is the tell-tale sign of cities and urbanization. Identifying and measuring agglomeration economies has been achieved by a variety of means and by various disciplines, including urban economics, quantitative geography, and regional science. Agglomeration is typically expressed as the non-linear dependence of many different urban quantities on city size, proxied by population. The identification and measurement of agglomeration effects is of course dependent on the choice of spatial units. Metropolitan areas (or their equivalent) have been the preferred spatial units for urban scaling modeling. The many issues surrounding the delineation of metropolitan areas have tended to obscure that urban scaling is principally about the measurable consequences of social and economic interactions embedded in physical space and facilitated by physical proximity and infrastructure. These generative processes obviously must exist in the spatial subcomponents of metropolitan areas. Using data for counties and urbanized areas in the United States, we show that the generative processes that give rise to scaling effects are not an artifact of metropolitan definitions and exist at smaller spatial scales.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-16T02:54:49Z
      DOI: 10.1177/23998083221148198
       
  • How to measure large-scale complex urban network structures using
           night-time light satellite databases. Application to European metropolitan
           regions

    • Free pre-print version: Loading...

      Authors: Joan Marull, Mercè Farré, Marta Andreu Espuña, Adrià Prior, Vittorio Galletto, Joan Trullén
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This article uses new methods and evidence from satellite data on night lighting to assess the urban network structure of 100 European metropolitan regions. Its aim was to develop indicators to test the hypothesis that complex urban networks are more efficient economically and less dependent on energy consumption owing to better information organization. It uses NPP-VIIRS NTL satellite data on night lighting (NTL) and employs a topographical representation of NTL intensities to detect urban centers. Based on the distribution of NTL intensities in urban centers represented as a Lorenz curve, it develops two new indicators of monocentricity and polycentricity to evaluate large-scale urban network structures. The results show that polycentric urban networks create more innovation, which allows them to be more economically efficient and less dependent on energy consumption. Further research should study in greater detail the relationships between urban network structures and their social, economic, and ecological performances.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-13T06:51:43Z
      DOI: 10.1177/23998083231151689
       
  • A network-based analysis to assess COVID-19 disruptions in the Bogotá
           BRT system

    • Free pre-print version: Loading...

      Authors: Juan D. Garcia-Arteaga, Laura Lotero
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The global COVID-19 crisis has severely affected mass transit in the cities of the global south. Fear of widespread propagation in public spaces and the dramatic decrease in human mobility due to lockdowns have resulted in a significant reduction of public transport options. We analyze the case of TransMilenio in Bogotá, a massive Bus Rapid Transit system that is the main mode of transport for an urban area of roughly 10 million inhabitants. Concerns over social distancing and new health regulations reduced the number of trips to under 20% of its historical values during extended periods of time during the lockdowns. This has sparked a renewed interest in developing innovative data-driven responses to COVID-19 resulting in large corpora of TransMilenio data being made available to the public. In this paper we use a database updated daily with individual passenger card swipe validation microdata including entry time, entry station, and a hash of the card’s ID. The opportunity of having daily detailed minute-to-minute ridership information and the challenge of extracting useful insights from the massive amount of raw data (∼1,000,000 daily records) require the development of tailored data analysis approaches. Our objective is to use the natural representation of urban mobility offered by networks to make pairwise quantitative similarity measurements between daily commuting patterns and then use clustering techniques to reveal behavioral disruptions as well as the most affected geographical areas due to the different pandemic stages. This method proved to be efficient for the analysis of large amount of data and may be used in the future to make temporal analysis of similarly large datasets in urban contexts.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-11T02:58:04Z
      DOI: 10.1177/23998083221150646
       
  • The Law of Population Concentration

    • Free pre-print version: Loading...

      Authors: Antonio Ciccone
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.

      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-10T06:36:45Z
      DOI: 10.1177/23998083221147139
       
  • TTS2016R: A data set to study population and employment patterns from the
           2016 Transportation Tomorrow Survey in the Greater Golden Horseshoe area,
           Ontario, Canada

    • Free pre-print version: Loading...

      Authors: Anastasia Soukhov, Antonio Páez
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This paper describes and visualises the data contained within the {TTS2016R} data package created in R, the statistical computing and graphics language. {TTS2016R} contains home-to-work commute information for the Greater Golden Horseshoe area in Canada retrieved from the 2016 Transportation Tomorrow Survey (TTS). Included are all Traffic Analysis Zones (TAZ), the number of people who are employed full-time per TAZ, the number of jobs per TAZ, the count of origin destination (OD) pairs and trips by mode per origin TAZ, calculated car travel time from TAZ OD centroid pairs and associated spatial boundaries to link TAZ to the Canadian Census. To illustrate how this information can be analysed to understand patterns in commuting, we estimate a distance-decay curve (i.e. impedance function) for the region. {TTS2016R} is a growing open data product built on R infrastructure that allows for the immediate access of home-to-work commuting data alongside complimentary objects from different sources. The package will continue expanding with additions by the authors and the community at-large by requests in the future. {TTS2016R} can be freely explored and downloaded in the associated Github repository where the documentation and code involved in data creation, manipulation and all open data products are detailed.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-09T08:10:36Z
      DOI: 10.1177/23998083221146781
       
  • A barrier too far: Understanding the role of intersection crossing
           distance on bicycle rider behavior in Chicago

    • Free pre-print version: Loading...

      Authors: Rohan L Aras, Nicholas T Ouellette, Rishee K Jain
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      For a variety of environmental, health, and social reasons, there is a pressing need to reduce the automobile dependence of American cities. Bicycles are well suited to help achieve this goal. However, perceptions of rider safety present a large hindrance toward increased bicycle adoption. These perceptions are largely influenced by the design of our current road infrastructure, including the crossing distances of large intersections. In this paper, we examine the role of intersection crossing distances in modifying rider behavior through the construction of a novel dataset integrating street widths and probable trip routes from Chicago’s Divvy bikeshare system. We compare real trips to synthetic trips that are not influenced by the width of intersections and exploit behavior differences that result from the semi-dockless nature of the bikeshare system. Our analysis reveals that bikeshare riders do avoid large intersections in limited circumstances; however, these preferences appear to be heavily outweighed by the relative spatial positions of origins and destinations (i.e., the urban morphology of Chicago). Our results suggest that specific infrastructural investments such as protected intersections could prove feasible alternatives to reduce the perception and safety concerns associated with large road barriers and enhance the attractiveness of non-motorized mobility.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-07T09:27:13Z
      DOI: 10.1177/23998083221147922
       
  • Ethnic segregation on linguistic landscapes

    • Free pre-print version: Loading...

      Authors: Seong-Yun Hong, Yeorim Kim, Yongchae Lee
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This work presents a novel approach to studying ethnic segregation from the perspective of linguistic landscapes. Numerous street-level images accumulated over the last two decades have enabled the exploration of linguistic landscapes at a larger scale than ever before. Since the prevalence of a specific language in a public space implies the linguistic group inhabiting the area, its careful evaluation can reveal the degree of segregation between linguistically different ethnic groups. To demonstrate the effectiveness of the proposed approach, we applied it to the linguistic landscape of Seoul, South Korea. Using a large set of street-level images collected from an online map platform, we measured the levels of segregation between Korean and Chinese signs from 2010 to 2018. The levels of segregation on the street-level images were different to a certain extent from those of residential segregation. While residential segregation gradually increased between 2010 and 2018, except for 2011, more fluctuations were observed in linguistic segregation. This finding is likely because a linguistic landscape is shaped mainly by advertising signs, banners, and billboards in commercial areas, and such commodified urban spaces change more dynamically to attract inhabitants and visitors. These results suggest that the proposed approach can offer an alternative way of understanding the complex socio-demographic phenomenon from a new perspective, as with other emerging data sources in the era of big data.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-04T08:57:27Z
      DOI: 10.1177/23998083221150240
       
  • Would people prefer city-center living in the post-COVID era':
           Experience, status, and attitudes to social disasters

    • Free pre-print version: Loading...

      Authors: Kiseong Jeong, Jaebin Lim
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The COVID-19 pandemic was a significant social disaster that radically affected the paradigm of current urbanization and city-center living. Responses to the disaster varied depending on related experiences, individual status, and attitudes. Thus, this research extends the previous literature by examining the effects of experiences related to the COVID-19 pandemic, socioeconomic status, and how perceptions and attitudes affect preferences for city-center living in the Seoul Metropolitan Area, South Korea. We use data from PSSRAC (Perception Survey of Seoul metropolitan area Residential Awareness during COVID-19) of 2021. A binary logistic regression method is used to examine significant characteristics that affected the residential preference change due to “Experience,” “Status,” and “Attitude” in the COVID-19 era. The findings showed that respondents’ experience, status, and attitude related to the pandemic could have a complex effect on predictions of preference, for central or suburban living tendencies in the post-COVID-19 era. In terms of “Experience,” people who had bad experiences during the pandemic, for example, poor economic conditions were associated with suburban area living trends. For “Status,” socially and economically vulnerable groups preferred suburban residence due to the steep rise in housing prices in the city center after the pandemic. Finally, for “Attitude,” ‘value of housing for investment” was positively associated with a preference for city-center living in the post-COVID-19 era; respondents with a higher priority for maintaining remote work tended not to change their current residence. This study may provide planners, housing developers, and policymakers with meaningful implications for addressing urban changes in the post-COVID-19 era. Additionally, it is expected that this research’s ESA analysis and results can be used as a valid reference for other global cities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-04T01:45:42Z
      DOI: 10.1177/23998083221149424
       
  • A hybrid modeling approach considering spatial heterogeneity and
           nonlinearity to discover the transition rules of urban cellular automata
           models

    • Free pre-print version: Loading...

      Authors: Haoran Zeng, Bin Zhang, Haijun Wang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban sprawl is a typical geographic dynamic process with spatial heterogeneity and nonlinearity. However, current studies usually focus on only one of them to extract urban sprawl mechanisms and build cellular automata (CA) models. In the current work, the urban CA transition rules are derived by a geographically weighted artificial neural network (GWANN), which can discover the driving mechanism of urban sprawl by considering both spatial heterogeneity and nonlinearity. Taking the urban sprawl of Wuhan and Beijing during 2000–2020 as examples, the advantages of GWANN in deriving transition rules are investigated by comparing it with logistic regression (LR), geographically weighted logistic regression (GWLR), and artificial neural network (ANN). Furthermore, the simulation performance of CA models based on LR, GWLR, ANN, and GWANN is compared and analyzed from the aspects of global and regional simulation accuracy and the morphology of simulated urban patches. The results show that GWANN has better fitting and simulation performance, indicating the validity and necessity of coupling spatial heterogeneity and nonlinearity to establish transition rules. This study is a novel exploration that contributes to deriving CA transition rules through a hybrid modeling approach that couples statistical models with learning models.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-03T10:28:19Z
      DOI: 10.1177/23998083221149018
       
  • Visual analytics of graffiti spatial patterns across 30 European city
           centres

    • Free pre-print version: Loading...

      Authors: Alexandros Bartzokas-Tsiompras, Eleftheria Konstantinidou
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Graffiti as an urban phenomenon comes in different forms and materials, from simple spray slogans to wall paintings and art, containing multi-thematic content. Despite the contradictory nature of various literature opinions, reports of a positive association between wall-graffiti and fear of crime or streetscape value have emerged. However, comparative urban studies registering graffiti locations are non-existent, thereby hindering the benchmarking of urban liveability. In this work, the spatial patterns of graffiti-vandalism across 30 European city centres were investigated, using Google Street View–derived observations. A significant variation in graffiti presence across Europe was recorded, ranging from about 3%–9% of street segments in London, Oslo and Vienna, to roughly 70%–76% in Madrid, Athens and Sofia. In addition, their spatial polarisation that reflects the presence of potential socio-spatial inequities requiring further attention was demonstrated. Overall, the created geo-visualisations could enable European policymakers to facilitate better-informed response strategies and researchers to delve into the effects of graffities on urban systems and societies.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2023-01-02T12:57:29Z
      DOI: 10.1177/23998083221149426
       
  • Spatially disaggregated simulation of interactions between home prices and
           land-use change

    • Free pre-print version: Loading...

      Authors: Reza Amindarbari, Perver Baran, Ross K. Meentemeyer
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Land-use regulations play a key role on both sides of the real estate market by regulating the supply of housing (e.g., through restrictions on unit density or building height) and by controlling the location and density of places of work, which are the primary drivers of the demand for housing. Developing geospatial models for this interaction between land use and home price on a spatially disaggregated level enables decisionmakers to evaluate the impact of their land-use decisions from the housing affordability perspective. However, existing standalone residential real estate pricing models are insensitive to changes in land use. In addition, the data preparation, calibration, and training of integrated land-use and transportation models is nontrivial too, and still impractical for most municipalities and planning agencies. This paper presents a simple-to-implement framework, SimP-R, for simulating changes in housing prices on a spatially disaggregated level in response to land-use change. It is composed of a residential real estate pricing model and an algorithm for computing a novel measure of supply-to-demand ratio. This paper then demonstrates the implementation of SimP-R in the city of San Francisco, with the entire Bay Area serving as the influence geography. Our findings showed our proposed measure of the supply-to-demand ratio is a strong predictor of and inversely related to housing prices. Simulation experimentation results highlighted SimP-R’s ability to capture the effect of local land-use changes on housing prices across the metropolitan area.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-27T10:27:05Z
      DOI: 10.1177/23998083221142603
       
  • A spatiotemporal disparity of transit and automobile access gap and its
           impact on transit use

    • Free pre-print version: Loading...

      Authors: Fatemeh Janatabadi, Sanju Maharjan, Alireza Ermagun
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This research empirically evaluates the access gap between transit and automobile to examine the extent of auto-access-orientation within and between the 50 American Metropolitan Areas. The Modal Access Gap (MAG) index is calculated over space and travel time to test three hypotheses: (1) MAG is a function of space and travel time, (2) MAG is CBD-centric, and (3) MAG is associated with transit use. Results indicate that (1) MAG merely possesses negative values ranging between −0.98 and −0.79, regardless of the travel-time thresholds or metropolitan areas, and the travel time lag between transit and automobile ranges from 35 minutes in New York to 51 minutes in Riverside for a 60-minute commute, (2) MAG decreases as one moves away from the central area, and (3) a 1% increase in MAG increases transit use by 1.37% on average.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-27T07:37:32Z
      DOI: 10.1177/23998083221147527
       
  • Visualizing the pattern of origin of international visitors to Beijing and
           Shanghai based on mobile phone data

    • Free pre-print version: Loading...

      Authors: Yao Wang, Yongheng Feng, Xiaodong Meng, Yang Xiao
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      There is a long tradition of understanding globalization by measuring the “world city-ness”, and there are two distinctive frameworks concerning the interrelations of the “world city network”, one of which builds upon the notion of worldwide corporate organizations and the other on the infrastructure of transport. Despite that, more studies on a single city are still required, since most cities participated in the globalization process on their own terms. Thus, the aim of this study is to visualize the patterns of origins of foreign visitors using data from mobile phones in order to better understand how China's global cities contribute to globalization in a cartogram. It is found that the strength of Shanghai’s global connections are concentrated overtly in the countries of the Asia-Pacific region, but Beijing still has the dominant role in sustaining China’s global links.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-27T04:50:22Z
      DOI: 10.1177/23998083221147529
       
  • Evaluating building color harmoniousness in a historic district
           intelligently: An algorithm-driven approach using street-view images

    • Free pre-print version: Loading...

      Authors: Zihao Zhou, Teng Zhong, Mengyang Liu, Yu Ye
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Building color and harmoniousness have been regarded as critical issues in planning historic districts. Harmoniousness of building façade colors (HBFC) is an indicator to evaluate the quality of the built environment, which can be perceived but is difficult to measure quantitatively. In addition, alleviating the impact of shadows in street-view images (SVIs) to assess building façade color is another research gap that is difficult to address. This paper proposes an efficient approach for evaluating HBFC on a large-scale using SVIs and a deep learning algorithm. Specifically, a shadow processing method was developed, and transfer learning was integrated into the harmoniousness evaluation process. The historical district of Guangzhou, China, was selected as a case study area. This study contributes to the development of human-centered planning and design by providing continuous measurements of “unmeasurable” quality across large-scale areas. Meanwhile, insights into building façade color and its harmoniousness can assist with accurate design guidance, which is important for historic districts.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-22T04:32:01Z
      DOI: 10.1177/23998083221146539
       
  • Study on the hotspots of urban tourism spaces based on Instagram-Worthy
           locations data: Taking Beijing as an example

    • Free pre-print version: Loading...

      Authors: Lai Fan, Dayu Zhang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      As the mobile Internet emerges, numerous Instagram-worthy locations gradually constitute new spaces of urban tourism. For instance, the Xiaohongshu application, a community with shared content, has increasingly become a platform for people to share well-known tourist attractions, providing a new perspective for the study of the popularity of tourism spaces. On the basis of data of ticking off Instagram-worthy locations from the Xiaohongshu application, the present study aims to identify tourism hotspots in Beijing, analyze their spatial characteristics, and explore their evolution features from two dimensions of time and space. In addition, the emotional images of tourism hotspots in Beijing are interpreted by semantic analysis with an internal mechanism that influences those locations explored. The results of the study show that (1) the overall spatial structure of tourism hotspots in Beijing is C-shaped, which expands from the core area to the periphery with the feature of a circle layer. (2) under the influence of the COVID-19 pandemic, the spatial distribution center of tourism hotspots in Beijing is gradually shifting to the Southeast with the tendency of expanding to the surrounding suburbs. (3) the reception and serviceability of the tourist attractions have a significant influence on the popularity of tourism hotspots. To date, less research has been focused on the data of ticking off emerging Instagram-worthy locations like the Xiaohongshu application, and there is a dearth of the study related to in-depth excavation of the internal influencing mechanism of their popularity. This paper, therefore, under the interaction of virtual and reality, provides new ideas and methods for studying the popularity of urban tourist attractions.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-19T01:36:22Z
      DOI: 10.1177/23998083221146542
       
  • Fractured smart cities: Missing links in India’s smart city mission

    • Free pre-print version: Loading...

      Authors: Uttam Singh, Dr Surya Prakash Upadhyay
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The postscripts of smart cities have been written before its prelude. Inserting smart technologies in infrastructure to improve urban environments, smart cities emphasize data-driven approaches and evidence-based planning. While it asks for production of new vocabularies, new ways of thinking, and proposes new methodologies, smart cities have trivialized baseline surveys. The insignificance to baseline survey hides the existing and functioning cities and leads to appropriation of “smart in the box” technologies. The omission of baseline survey fails to revamp planning and governance techniques as well as management and delivery of urban services. India’s Smart City Mission runs through a similar fate. Despite changes in vision and approach towards urban improvement, Smart City Mission suffers from methodological apathy and produces fractured smart cities. In doing so, the paper explores how the idea of normative smart city shrouds urban complexities and heterogeneities and proposes solutions without comprehending the functional and existing cities. Drawing on cases of urban water and solid waste management in Smart City Dharamshala, this paper discusses how fissures in normative and functional smart cities are continually produced through broken, incomplete, and erroneous data that, ultimately, fails in creating robust and resilient cities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-08T12:23:05Z
      DOI: 10.1177/23998083221144321
       
  • Deploying geospatial visualization dashboards to combat the socioeconomic
           impacts of COVID-19

    • Free pre-print version: Loading...

      Authors: Sarbeswar Praharaj, Patricia Solis, Elizabeth A Wentz
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      COVID-19 dashboards with geospatial data visualization have become ubiquitous. There is a growing sense of responsibility to report public health data pushing governments and community organizations to develop and share web-based dashboards. While a substantial body of literature exists on how these GIS technologies and urban analytics approaches support COVID-19 monitoring, their level of social embeddedness, quality and accessibility of user interface, and overall decision-making capabilities has not been rigorously assessed. In this paper, we survey 68 public web-based COVID-19 dashboards using a nominal group technique to find that most dashboards report a wealth of epidemiologic data at the state and county levels. However, these dashboards have limited emphasis on providing granular data (city and neighborhood level) broken down by population sub-groups. We found severe inadequacy in reporting social, behavioral, and economic indicators that shape the trajectory of the pandemic and vice versa. Our survey reveals that most COVID-19 dashboards ignore the provision of metadata, data download options, and narratives around visualizations explaining the data’s background, source, and purpose. Based on these lessons, we illustrate an empirical experiment of building a dashboard prototype—the COVID-19 Economic Resilience Dashboard in Arizona. Our dashboard project demonstrates a model that can inform decision-making (beyond plain information sharing) while being accessible by design. To achieve this, we provide localized data, drill-down options by geography and sub-population, visualization narratives, open access to the data source, and accessible features on the interface. We exhibited the value of linking pandemic-related information with socioeconomic data. Our findings suggest a pathway forward for researchers and governments to incorporate more action-oriented data and easy-to-use interfaces as they refine existing and develop new information systems and data analytics dashboards.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-08T02:17:00Z
      DOI: 10.1177/23998083221142863
       
  • Defining archetypes of mixed-use developments using Google Maps API data

    • Free pre-print version: Loading...

      Authors: Zhongming Shi, Heidi Silvennoinen, Arkadiusz Chadzynski, Aurel von Richthofen, Markus Kraft, Stephen Cairns, Pieter Herthogs
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban planning relies on the definition, modelling and evaluation of multidimensional phenomena for informed decision-making. Urban building energy modelling, for instance, usually requires knowledge about the energy use profile and surface area of each use that takes place within a building. We do not have a detailed understanding of such information for mixed-use developments, which are gaining prominence in urban planning. In this paper, we developed a methodology to quantitatively define the characteristics of mixed-use developments using archetypes of programme profiles (ratios of each programme type) of a city’s mixed-use plots. We applied our methodology in Singapore, resulting in 163 mixed-use zoning archetypes using Singapore’s master plan data and Google Maps API data. In a case study, we demonstrated how these archetypes can be used to provide more detailed data for urban building energy modelling, including energy demand forecasts and energy supply system design. To enable future automation of the workflow, the archetype definitions were represented and stored as a machine-readable ontology. This ontology can later be extended with for example, the mobility properties of archetypes; thus, enabling the archetypes' use in other urban planning applications beyond building energy modelling.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-03T11:06:37Z
      DOI: 10.1177/23998083221141428
       
  • Dark cities or cities of light' – sunlight amenity preservation at
           whole-city scale using a spatio-temporal decision support approach

    • Free pre-print version: Loading...

      Authors: Marcus White, Nano Langenheim, Tianyi Yang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Public open spaces are fundamentally important for the health and well-being of citizens in densely populated cities. If not carefully planned, high-density urban development can overshadow adjacent open spaces, resulting in poor quality, dark and oppressive winter conditions. Current planning control approaches for protecting light amenity in cities are often limited to simple overshadowing impact diagrams (e.g. shadows cast on the equinox at 9 a.m., 12 p.m. and 3 p.m.). In cities transitioning from low to higher density, comprising more complex urban forms and more extreme seasonal light amenity dynamics, these static approaches are insufficient. This paper outlines the development of a spatio-temporal design decision support system for analysing and protecting the light amenity of public open spaces, applied to a capital city in Australia. The system described has two parts: Firstly, to assess the overshadowing of existing public open spaces and identify those in need of protection (Part A), and secondly to generate planning restrictions to protect designated open spaces from future deprivation of light (Part B). For Part A, we use a graphics processing unit accelerated aggregate-shadow (15 minute increments) calculation applied to a detailed city-wide 3D model generated from billions of points of aerial survey (LiDAR) data. For Part B, we use a reversed solar ray casting approach we call the ‘Subtracto-Sun’ which allows a user to specify a time range (e.g. 9 a.m.–4 p.m.) for multiple days of the year and subsequent generation of 3D maximum building height development envelopes. The output of this system was used by the local government to inform a proposed planning policy amendment for the City of Melbourne. The findings illustrate the potential for urban professionals to use the system to rapidly assess shadow impacts for existing and proposed, contextually accurate, large, complex urban environments with high levels of geometric and temporal details. The presented results are significant in that we develop and apply our spatio-temporal decision-support approach to a local government area, successfully informing planning height restriction decisions to protect daylight amenity of public open spaces in need of protection. Our method for setting development height restrictions allows for higher density to be achieved, while not increasing the overshadowing of critical open space infrastructure during designated times.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-03T01:56:40Z
      DOI: 10.1177/23998083221143120
       
  • Comparing types and patterns: A context-oriented approach to densification
           in Switzerland and the Netherlands

    • Free pre-print version: Loading...

      Authors: Vera Götze, Mathias Jehling
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      While governments worldwide develop policies to promote urban densification, critics point to possible negative effects of densification on social sustainability. The occurrence and distribution of these negative social effects are strongly influenced by land policies. This makes it crucial to monitor the role of land policies and understand what processes shape urban development in the context of densification. To do so, detailed, large-scale international comparisons of densification patterns, including building and social changes, are needed. We address this issue by introducing a method to measure and compare urban development in two countries with contrasting planning systems: the Netherlands, where public actors play a strong and active role, and Switzerland, where strong private property titles and a highly democratic planning system are prevailing. Our GIS-based method analyses densification processes within their surrounding morphological and socio-demographic context. A k-proto cluster analysis on highly detailed spatial and statistical data based on housing units, covering 2011–2019, results in five densification types. The distribution of these types reveals different patterns in the two city regions of Utrecht (NL) and Bern (CH). Most strikingly, contiguous redevelopments frequently occurred in Utrecht but hardly in Bern, pointing at possible advantages for Dutch municipalities to intervene in property rights. While having developed an empirical basis in this study, future research that refines the analysis of the legal, planning and ownership conditions underlying the identified densification patterns can contribute significantly to policy evaluation.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-02T02:44:43Z
      DOI: 10.1177/23998083221142198
       
  • Geographical detector-based assessment of multi-level explanatory powers
           of determinants on China’s medical-service resumption during the
           COVID-19 epidemic

    • Free pre-print version: Loading...

      Authors: Bisong Hu, Sumeng Fu, Jin Luo, Hui Lin, Qian Yin, Vincent Tao, Bin Jiang, Lijun Zuo, Yu Meng
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Knowing the multi-level influences of determinants on medical-service resumptions is of great benefits to the policymaking for medical-service recovery at different levels of study units during the post-COVID-19 pandemic era. This article evaluated the hospital- and city-level resumptions of medical services in mainland China based on the data of location-based service (LBS) requests of mobile devices during the two time periods (December 2019 and from February 21 to March 18, 2020). We selected medical-service capacity, human movement, epidemic severity, and socioeconomic factors as the potential determinants on medical-service resumptions and then explicitly assessed their multi-level explanatory powers and the interactive effects of paired determinants using the geographical detector method. The results indicate that various determinants had different individual explanatory powers and interactive relationships/effects at different levels of medical-service resumptions. The current study provides a novel multi-level insight for assessing work resumption and individual/interactive influences of determinants, and considerable implications for regionalized recovery strategies of medical services.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-01T08:34:13Z
      DOI: 10.1177/23998083221143122
       
  • The multisensory environmental evaluations of sound and odour in urban
           public open spaces

    • Free pre-print version: Loading...

      Authors: Meihui Ba, Zhongzhe Li, Jian Kang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Few studies have focused on the multisensory perception of audio–olfactory interaction with the purpose of improving the use of urban spaces. This study conducted multisensory environmental evaluations in three urban open spaces in China with the aim of verifying the existence of audio–olfactory interaction in the urban environments and providing different perspectives for the improvement of urban environmental quality. A sensewalk approach was adopted in the study, and the main research contents were: the odour’s effects on sound source and sound environment evaluations, and the sound’s effects on odour source and odour environment evaluations. The results indicated that food odour improved acoustic comfort and sound congruency and reduced subjective loudness. Pollution odour worsened the assessment of traffic and lowered subjective loudness. Sound decreased the subjective intensity of odour and exacerbated its evaluation. Additionally, food odour enhanced the sound environment assessment of pedestrian streets, while pollution odour worsened it. Sound had a weak impact on odour environment evaluations. The masking effect between sound and odour showed that the presence of the latter decreased subjective loudness while increased sound diminished the subjective intensity of odour. Furthermore, odour’s influence on sound evaluations was greater than the influence of sound on odour evaluations. These findings have implications for the planning and design of a livable and comfortable urban environment through the perspective of sensory interaction.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-01T07:54:53Z
      DOI: 10.1177/23998083221141438
       
  • Half-(head)way there: Comparing two methods to account for public
           transport waiting time in accessibility indicators

    • Free pre-print version: Loading...

      Authors: Anson F Stewart, Andrew M Byrd
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Various methods have been developed to account for travel time variability and uncertainty when analyzing public transport networks and computing related accessibility indicators. In this paper, we establish some convergence characteristics of one such method, implemented in the R5 routing engine, yielding guidelines for the minimum number of randomized schedules. This parameter has implications for result stability, analysis turnaround time, and computation costs. We also confirm that for travel time and accessibility results, there are spatially varying differences between our method and the conventional method relying on the assumption of half-headway waiting times. The conventional method appears to understate the benefits of transit in certain locations, particularly those served by multiple lines. Researchers and planning practitioners may find the R5 method preferable when analyzing complex networks or comparing transit scenarios where routes are specified in terms of headways or frequencies, rather than complete schedules with exact departure times for each trip.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-01T03:21:31Z
      DOI: 10.1177/23998083221137077
       
  • Predicting housing construction period based on a cox proportional hazard
           model––an empirical study of housing completions in the greater
           Toronto and Hamilton area

    • Free pre-print version: Loading...

      Authors: Yu Zhang, Eric J Miller
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The completion progress of residential development projects and the length of construction are frequently discussed in the construction industry, but rarely studied by urban modellers. Nonetheless, a realistic reflection of housing supply processes is important for urban microsimulation and land use modelling. To predict the dwelling units generated over space and time, this paper decomposes the housing supply process into two major components: housing starts and completions, the nature and modelling logic of which are quite different. This paper deals with the latter segment, aiming to answer the question of: how long will it take to complete construction of new dwellings' A Cox Proportional Hazard (CPH) Model is employed to examine the “survival” rate of residential building projects and the probabilistic distribution of construction periods. Narrowing down the scope of research, this study investigates housing completions at the individual project level, and discusses the impact of structure type, surrounding land use, and accessibility on the housing completion rate. The Cities of Toronto, Hamilton, and Brampton in the Greater Toronto and Hamilton Area (GTHA) were selected to conduct the empirical study, with each representing different types of urban form to test model compatibility. The hazard models show good performance in replicating completion rates, and the impact of each factor on hazard ratio indicates that, single detached dwelling units with relatively homogeneous land use have the shortest completion time. This study could provide one component of a comprehensive framework for modelling housing supply, especially in urban microsimulation systems.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-29T07:53:45Z
      DOI: 10.1177/23998083221143386
       
  • Analysing the consequences of progressive Urban Spatial cycles to evaluate
           urban land use policy

    • Free pre-print version: Loading...

      Authors: Biswajit Mondal
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban expansion patterns have always evolved with various successive Urban Spatial Cycles (USCs). Both densification and dispersion strategies have shown limited success in optimizing local benefits such as affordable housing, access to amenities, a good environment, and low-cost transport in the cities of developing countries. However, in such countries, a systematic assessment of USCs and strategic utilization of the analyses, are not usually part of the land use policy-making process. The outcomes of the policy decisions are therefore less than optimal. This paper aims to explore the impact of progressive USCs on housing price, travel time, fuel consumption and environment. Based on geospatial data, this study examines the progress of USCs in Ahmedabad city. Landscape matrices and local perceptions are used to quantify the consequences of USCs using the Generalized Additive Model (GAM). Ahmedabad’s case study shows that the densification cycle is firmly active in the inner suburb and is closely associated with housing price inflation as well as the increase in travel time and fuel consumption. The cycles of fragmentation and sprawl in the outer suburban area are consistent with environmental degradation and travel frequency. Findings suggest that USCs-based policy assessment can be a useful tool to trade-off the cost and benefit of urban expansion.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-29T07:24:13Z
      DOI: 10.1177/23998083221140884
       
  • Are neighbourhood amenities associated with more walking and less
           driving' Yes, but predominantly for the wealthy

    • Free pre-print version: Loading...

      Authors: Samuel Heroy, Isabella Loaiza, Alex Pentland, Neave O’Clery
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Cities are home to a vast array of amenities, from local barbers to science museums and shopping malls. But these are unequally distributed across urban space. Using Google Places data combined with trip-based mobility data for Bogotá, Colombia, we shed light on the impact of neighbourhood amenities on urban mobility patterns. By deriving a new accessibility metric that explicitly takes into account spatial range, we find that a higher density of local amenities is associated with a higher likelihood of walking as well as shorter bus and car trips. Digging deeper, we use an effect modification framework to show that this relationship varies by socioeconomic status. Our main focus is walking and driving, finding that amenities within about a 1-km radius from home are robustly associated with a higher propensity to walk and shorter driving time only for the wealthiest group. These results suggest that wealthier groups may weigh the proximity of local amenities more heavily into travel decisions, perhaps based on differentiated time-money trade-offs. As cities globally aim to boost public transport and green travel, these findings enable us to better understand how commercial structure shapes urban mobility in highly income-segregated settings.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-28T11:32:18Z
      DOI: 10.1177/23998083221141439
       
  • Who can walk' An analysis of public amenity access in America’s
           ten largest cities

    • Free pre-print version: Loading...

      Authors: Emily Talen
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      How uneven is the proximity to public amenities like libraries and schools among racial groups, or children and older people' This paper uses a catchment area approach to evaluate walkable proximity to four common public amenities (parks, libraries, schools, and transit stops), looking at four racial categories and a set of variables that one might reasonably expect proximity to be related to (e.g., population density). For each of the 10 largest US cities examined, location quotients for each amenity (libraries, parks, schools, and transit stops) were calculated at three distances (0.25 miles, 0.5 miles, and 1 mile). Across all amenities, the racial group whose LQ had the greatest increase when comparing net median change between distance bands (i.e., between .25 miles and 1 mile) was Black Americans. There were large differences between the location quotient means and medians in non-White racial groups for each amenity, indicating a large amount of skew. In most cities and with most amenities, the difference between mean and median was considerably smaller in White populations, indicating a more normal curve and fewer outliers. Proximity, in other words, seems to be more homogenous in White populations. The LQs were also significantly higher in White populations across cities. Further, in all cities except Los Angeles, Asian populations were generally the most under-represented group for each catchment area around each amenity. The fact that non-White residents predominantly had lower LQs and therefore lower access (with some exceptions, for example, in the case of schools) is a generalized and problematic finding that adds to the body of evidence documenting the spatial injustices that American cities continue to manifest.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-28T08:41:43Z
      DOI: 10.1177/23998083221142866
       
  • Road infrastructures, spatial surroundings, and the demand and route
           choices for cycling: Evidence from a GPS-based mode detection study from
           Oslo, Norway

    • Free pre-print version: Loading...

      Authors: Tineke de Jong, Lars Böcker, Christian Weber
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      To achieve a higher cycling uptake, it is essential for planners to know what kind of cycling infrastructure to plan and where, that is, through which types of urban environments. In this paper, we provide a deeper understanding of cycling demand and cycling route choices and infer insights into cyclists’ latent preferences and dispreferences concerning both infrastructure attributes and the spatial characteristics of route surroundings. Hereto, this study has collected, map-matched, geovisualized, and examined a unique GPS-based database with over 25,915 cycling trips in Oslo, Norway. Our findings reveal that cyclists substantially deviate from shortest paths, covering 59% more distance on average. Higher cycling frequencies, both in absolute terms and relative to shortest-path-expected-values, can be found on route sections that have some form of cycling infrastructure, especially those having segregated bicycle highways and bike roads. We also find higher demand and route choices for flatter and water-facing routes, as well as routes less disrupted by crossings and away from highway environments. In contrast, routes surrounded by green space or high population density, despite having high demand in absolute terms, are cycled less than expected based on shortest paths. The paper concludes by reflecting on the significance, limitations, and implications of our findings and novel methodological approaches for the bicycle route choice theory and practice moving forward.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-28T04:16:28Z
      DOI: 10.1177/23998083221141431
       
  • Feasibility assessment of solar photovoltaic deployments on building
           surfaces with the constraint of visual impacts

    • Free pre-print version: Loading...

      Authors: He Zheng, Bo Wu, Hui Lin, Junsong Jia, Heyi Wei
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      As a major component of social acceptance, visual impact is often considered a significant constraint in solar applications. Visual impact assessment of solar applications, however, has been limited to pedestrians in previous studies. The extent to which PV systems can have visual impacts on occupants and whether it is necessary to include occupants in the measurement of visual impact remains uncertain. To fill this gap, we extended it from pedestrians to occupants and proposed a quantitative method to integrate pedestrians and occupants into a framework, combining the estimation of solar potential for the feasibility assessment of PV applications in a built environment. The concept is tested with a real case, located in Qingdao city, China, to present the technical flowchart for the feasibility assessment of solar PV deployments with the visual constraint. Building surfaces with qualified solar irradiation and low visibility were identified and compared in two cases, that is, with and without the inclusion of occupants as the visual constraint. The comparison results show that the change of suitable building surfaces for solar applications is 172,306 m2 (21% of suitable area) and 126 GWh (19% of yield energy) across the study area, indicating the significance of including occupants in the visibility assessment for the deployment of solar applications. The proposed method considers the visual constraint for the feasibility assessment of solar applications from the perspective of pedestrians and occupants, and it is helpful to identify the suitable surfaces for the large-scale deployment of solar applications at an early planning stage of solar city.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-26T06:14:14Z
      DOI: 10.1177/23998083221142196
       
  • Generative methods for Urban design and rapid solution space exploration

    • Free pre-print version: Loading...

      Authors: Yue Sun, Timur Dogan
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Rapid population growth and climate change drive urban renewal and urbanization at massive scales. New computational methods are needed to better support urban designers in developing sustainable, resilient, and livable urban environments. Urban design space exploration and multi-objective optimization of masterplans can be used to expedite planning while achieving better design outcomes by incorporating generative parametric modeling considering different stakeholder requirements and simulation-based performance feedback. However, a lack of generalizable and integrative methods for urban form generation that can be coupled with simulation and various design performance analysis constrains the extensibility of workflows. This research introduces an implementation of a tensor-field–based generative urban modeling toolkit that facilitates rapid design space exploration and multi-objective optimization by integrating with Rhino/Grasshopper ecosystem and its urban analysis and environmental performance simulation tools. Our tensor-field modeling method provides users with a generalized way to encode contextual constraints such as waterfront edges, terrain, view-axis, existing streets, landmarks, and non-geometric design inputs such as network directionality, desired densities of streets, amenities, buildings, and people as forces that modelers can weigh. This allows users to generate many, diverse urban fabric configurations that resemble real-world cities with very few model inputs. We present a case study to demonstrate the proposed framework's flexibility and applicability and show how modelers can identify design and environmental performance synergies that would be hard to find otherwise.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-25T08:20:02Z
      DOI: 10.1177/23998083221142191
       
  • How changes in urban morphology translate into urban metabolisms of
           building stocks: A framework for spatiotemporal material flow analysis and
           a case study

    • Free pre-print version: Loading...

      Authors: Mario Kolkwitz, Elina Luotonen, Satu Huuhka
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Anthropogenic stocks are increasingly seen as potential reserves for secondary resources, which has led to a rapid development in research of urban metabolic systems. With regard to buildings and their associated material stocks and flows, one of the most critical shortcomings in the state-of-the-art is the knowledge gap for drivers, dynamics, patterns and linkages that affect the urban metabolism. This paper is premised on the idea that urban planning stirs up these material flows, so it should also adopt their sustainable management on its agenda. It presents an approach that highlights the intertwined nature of changing urban morphology and building material stocks and flows in space and time. An analytical framework, based on the principles of material flow analysis, is provided for an integrated, spatiotemporal study of urban morphology and urban metabolism of buildings, using building and plot data as the input and identifying internal processes of the urban metabolism as the output. The identified processes include greenfield development, infill construction, building replacement and shrinkage, each of which can be expected to have tangible yet very different material and environmental consequences in the form of embodied materials and CO2. The use of the framework is demonstrated with a case study in the Finnish city of Vantaa in 2000–2018. The case study shows patterns pertaining to a growing city unrestricted by geographic or historic factors, manifested as vast greenfield developments and replacement of a notably young building stock. As sustainability may soon call into question both these strategies, uncovering the material consequences of a city’s past urban (re)development strategies lay the foundation for using the presented approach proactively in planning support, in pursuit of more circular economy-based and low carbon cities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-25T07:46:39Z
      DOI: 10.1177/23998083221140892
       
  • Urban neighbourhood classification and multi-scale heterogeneity analysis
           of Greater London

    • Free pre-print version: Loading...

      Authors: Tengfei Yu, Birgit S Sützl, Maarten van Reeuwijk
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      We study the compositional and configurational heterogeneity of Greater London at the city- and neighbourhood-scale using Geographic Information System (GIS) data. Urban morphometric indicators are calculated including plan-area indices and fractal dimensions of land cover, frontal area index of buildings, evenness, and contagion. To distinguish between city-scale heterogeneity and neighbourhood-scale heterogeneity, the study area of 720 km2 is divided into 1 [math] 1 km2 neighbourhoods. City-scale heterogeneity is represented by categorisation of the neighbourhoods using a k-means clustering algorithm based on the morphometric indicators. This results in six neighbourhood types ranging from “greenspace” to “central business district”. Neighbourhood-scale heterogeneity is quantified using a hierarchical multi-scale analysis for each neighbourhood type. The analysis reveals the dominant length scales for land-cover and neighbourhood types and the resolutions with the most information gain. We analyse multi-scale anisotropy and show that small-scale features are homogeneous, and that anisotropy is present at larger length scales.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-25T07:24:32Z
      DOI: 10.1177/23998083221140890
       
  • Identifying relevant volunteered geographic information about adverse
           

    • Free pre-print version: Loading...

      Authors: Tomasz Opach, Jan Ketil Rød, Carlo Navarra, Tina-Simone Neset, Julie Wilk, Sara Santos Cruz, Almar Joling
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The study set out to investigate how the experience of creating a map-based participatory system might help identify what is needed to support the production of relevant volunteered geographic information (VGI) about urban areas exposed to impacts of adverse weather events in Trondheim, Norway. This article details the systematic approach used to collect VGI, starting from the active engagement of end users during the design and development process of the CitizenSensing participatory system, through using the system in two VGI campaigns, up to the examination of the collected data. Although the VGI examination identified exposed areas in Trondheim, for instance, those that are likely to accumulate surface water from heavy rains or meltwater, the experience gained from the use of the CitizenSensing system helped to identify some critical points regarding the production of relevant VGI. Potential practical implications justify the need for VGI. For instance, in the case of Trondheim, relevant VGI may result in better planned municipal interventions regarding city infrastructure for pedestrians, cyclists and drivers, increased public awareness and access to local knowledge about areas exposed to inundation. The study also confirmed the need for adequate system components for VGI vetting and exploration in the post-collection stage to obtain a comprehensive insight into collected VGI.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-23T11:17:42Z
      DOI: 10.1177/23998083221136557
       
  • Examining the geometry of streets through accessibility: new insights from
           streetspace allocation analysis

    • Free pre-print version: Loading...

      Authors: Nicolas Palominos, Duncan A Smith
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This paper describes streetspace allocation analysis, a method that uses street cross-sections to measure footway and carriageway widths and quantify a key parameter of street design citywide. The resulting network-based streetspace allocation metrics are employed on a proof-of-concept study of train station service areas in London, applying shortest-path analysis under a place and walking prioritisation approach. Overall, streetspace allocation statistics for London confirm the citywide predominance of space allocated for vehicular transport over pedestrian uses. A comparison of the current distribution and proposed re-allocation of streetspace on streets near stations allows for the investigation of the effects of streetspace enhancements, which tend to be beneficial in reducing pedestrian movement impedance and extending service areas. The methods presented here can offer valuable analytical capacity for developing new transit-oriented schemes and designing place-based streets that support sustainable transport and sustainable urban development.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-18T08:19:48Z
      DOI: 10.1177/23998083221139849
       
  • How do urban services facilities affect social segregation among people of
           different economic levels' A case study of Shenzhen city

    • Free pre-print version: Loading...

      Authors: Yuyang Wu, Yao Yao, Shuliang Ren, Shiyi Zhang, Qingfeng Guan
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Social segregation hinders the development of cities and has become a hot topic in urban research. Existing studies have focused on the difference in the distribution of crowd activities to measure segregation but have ignored the impact of the urban environment on crowd gathering and segregation. To study the impact and understand social segregation more comprehensively, we coupled mobile phone datasets and housing price data to divide city dwellers into three socioeconomic levels. Considering that spatial colocation is a necessary condition for interaction among various social groups, spatial colocation probability was proposed to quantitatively describe the degree of social segregation at the community scale. Point-of-interest (POI) data were introduced to represent the urban service facilities. The effect of urban service facilities on the segregation of different groups was analyzed by using geographically weighted regression (GWR). The results indicate three points, as follows. (1) Significant social segregation in Shenzhen mostly occurs in suburban and downtown areas, and the interaction segregation of people mainly occurs between people with high and low socioeconomic levels. (2) More economically inclusive and necessary service facilities (e.g., medical and insurance companies) can promote crowd interaction and ease the segregation of social activities. (3) The impact of service facilities on the interaction of various social groups is related to the development of the area where the activities occur, and the most significant impact is in high-tech industrial zones. This study quantitatively calculated the impacts of different service facilities on different groups of people in different communities and times. From the results, detailed and reasonable suggestions were made for city planners.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-17T10:06:01Z
      DOI: 10.1177/23998083221140415
       
  • Categorizing urban space based on visitor density and diversity: A view
           through social media data

    • Free pre-print version: Loading...

      Authors: I-Ting Chuang, Qingqing Chen, Ate Poorthuis
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Analyses of urban spaces have often stressed the importance of both the density and diversity of the people they attract. However, the diversity of people is a challenging concept to operationalize within the context of urban spaces, which is why many evaluations of urban space have relied primarily on density-based measures. We argue that a focus on only one of the two aspects misses important aspects of the variety of urban spaces in our cities. To address this, we design a methodology that evaluates both the density and diversity of human behavior in urban spaces based on geosocial media data. We operationalize density as the frequency of tweets from visitors to a particular location and diversity as the variety of the home neighborhoods of those visitors. Taking Singapore as a test case, we identify networks between the home neighborhoods of 28k Twitter users based on 2.2 million geolocated tweets collected between 2012 and 2016. Based on these data, we categorize the urban landscape of Singapore into four “performance” categories, namely High-Density/High-Diversity, High-Density/Low-Diversity, Low-Density/High-Diversity, and Low-Density/Low-Diversity. Our findings illustrate that this combined indicator provides useful nuance compared to differentiation between well and less performing spaces based on density alone. By enabling a categorization of urban spaces that fits closer to the diversity of human behavior in these spaces, human mobility data sets, such as the social media data we use, open the door to a practical evaluation of the design and planning of our heterogeneous urban environment.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-16T10:58:05Z
      DOI: 10.1177/23998083221139848
       
  • Determinants of Urban land development: A panel study for U.S.
           metropolitan areas

    • Free pre-print version: Loading...

      Authors: Joachim Zietz, Heiko Kirchhain
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This study examines the extent and determinants of urban land expansion and fragmentation for 104 U.S. metropolitan areas for the time period 2001-2019. It leverages temporally and spatially consistent, satellite-based data. The analysis distinguishes among four different intensity levels of urban development and makes use of a number of landscape fragmentation metrics. Estimation relies on two-way fixed-effects panel techniques. Our time fixed-effects indicate that high-intensity urban developments grew by about 25% from 2001 to 2019, low-intensity developments by about 5%. The percentage increases for the corresponding fragmentation statistics are higher, at about 40% and 15%, respectively. Higher gasoline prices are associated with less urban land expansion and fragmentation.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-16T05:36:22Z
      DOI: 10.1177/23998083221139844
       
  • Incorporating networks in semantic understanding of streetscapes:
           Contextualising active mobility decisions

    • Free pre-print version: Loading...

      Authors: Winston Yap, Jiat-Hwee Chang, Filip Biljecki
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Planning for active mobility satisfies many fundamental tenets of good urban design and planning. However, planning for active mobility is a complex endeavour due to numerous local, place-based factors that influence active mobility decisions. Recent advancements in urban data research have demonstrated the effectiveness of deep learning methods in evaluating active mobility potential for urban environments. At present, the incorporation of semantic information from deep learning models and street view imagery into spatio-temporal contexts remains a challenge. In particular, knowledge extraction from deep learning models remains an open question for urban planning and decision-making. Towards this issue, we propose a functional deep learning and network science workflow that employs open data from OpenStreetMap and Mapillary to assess factors affecting active mobility decisions and route planning. We demonstrate the generalisability of our analytical workflow through two case studies focusing on urban greenery in Nerima city (Japan) and urban visual complexity in Pasir Ris town (Singapore). Our results reveal clear patterns of heterogeneity in urban streetscapes and identify unevenness in street infrastructure provision based on destination types. Using this information, we propose specific areas for design intervention to improve active mobility planning. Our workflow is applicable for a diverse range of use cases making it relevant to a wide range of stakeholders, not limited to, urban researchers, policy makers and urban planners.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-11T10:04:22Z
      DOI: 10.1177/23998083221138832
       
  • Incorporating water quality into land use scenario analysis with random
           forest models

    • Free pre-print version: Loading...

      Authors: Robert Goodspeed, Camilla Lizundia, Lingxiao Du, Srishti Jaipuria, Runzi Wang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Emerging research has begun to document the nuanced ways that urban form can influence water quality in urban areas. To facilitate the greater consideration of water quality by planning practitioners, this paper illustrates a two-step method to predict the water quality performance of land use scenarios through the presentation of a case study in the Huron River watershed in Michigan, USA. First, random forest models are used to relate 38 urban form variables to three water quality outcomes within the watershed: total suspended solids (TSS), total phosphorus (TP), and Escherichia coli (E. coli) concentrations. Second, the calibrated random forest models are used to predict the water quality performance for three land use scenarios for a local jurisdiction. The case study illustrates how even scenarios describing additional urbanization can result in predicted improvements to water quality. The methods contribute to the greater consideration of water issues in urban planning practice.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-11T07:54:41Z
      DOI: 10.1177/23998083221138842
       
  • The Social Digital Twin:The Social Turn in the Field of Smart Cities 

    • Free pre-print version: Loading...

      Authors: Batel Yossef Ravid, Meirav Aharon-Gutman
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Complexity theory has become a conceptual framework and a source of inspiration for Smart City initiatives. In addition to many other conceptions, the Urban Digital Twin (UDT) became both a concept and a tool for generating the revolutionary act of data-driven 3D city modeling. Indeed, the UDT has increased the ability of planners to make decisions vis-à-vis data-driven city models; at the same time, however, it has attracted criticism because of its focus on the physical dimensions of cities. In facing these challenges, we seek to join the conceptual and practical efforts to generate a social turn in the field of Smart Cities and urban innovation. Creating a UDT with a social focus, we maintain, is not only a 1:1 translation of the built environment into the social realm, but also demands interdisciplinary knowledge from the fields of sociology, anthropology, planning, and ethics studies. This article makes theoretical and methodological contributions. Theoretically, it discusses the potential contribution of the Social Urban Digital Twin (SUDT) to the theory of urbanism, enabling us to represent the physical and the social environments as a single fabric. Methodologically, it enhances the know-how of the City Analytics research community by advancing a six-phase protocol for developing SUDTs, each phase of which integrates technological conceptions and social-theoretical content. The phases of the SUDT protocol are demonstrated using a specific case study: the experience of elderly residents of the Haifa neighborhood of Hadar—a low-income neighborhood in Israel characterized by ethnic and national diversity—during the Coronavirus pandemic. We conclude by discussing the contributions and limitations of the SUDT.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-11T05:08:54Z
      DOI: 10.1177/23998083221137079
       
  • Where to invest in cycle parking: A portfolio management approach to
           spatial transport planning

    • Free pre-print version: Loading...

      Authors: Yuhei Ito, Malcolm Morgan, Robin Lovelace
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      A lack of cycle parking is a known barrier to promoting the uptake of cycling in urban areas. Unlike cars that can be parked on the roadside with little additional infrastructure, bikes usually require dedicated parking facilities. The existing research and guidance on where cycle parking should be provided primarily focuses on key destinations such as train stations or schools. Thus, there is a gap in knowledge about the amount of general-purpose cycle parking required and how it should be distributed across a city. This paper presents a novel method for analysing and prioritising the spatial distribution of cycle parking. The method draws on established portfolio management techniques but applies them in a spatial context. Using the case study of London, we demonstrate that it is possible to identify areas that have a deficit of cycle parking as well as locations that have the most significant potential for increasing cycling uptake by providing additional cycle parking.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-10T10:52:35Z
      DOI: 10.1177/23998083221138575
       
  • Transit communication via Twitter during the COVID-19 pandemic

    • Free pre-print version: Loading...

      Authors: Wenwen Zhang, Camille Barchers, Janille Smith-Colin
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Transit providers have used social media (e.g., Twitter) as a powerful platform to shape public perception and provide essential information, especially during times of disruption and disaster. This work examines how transit agencies used Twitter during the COVID-19 pandemic to communicate with riders and how the content and general activity influence rider interaction and Twitter handle popularity. We analyzed 654,345 tweets generated by the top 40 transit agencies in the US, based on Vehicles Operated in Annual Maximum Service (VOM), from January 2020 to August 2021. We developed an analysis framework, using advanced machine learning and natural language processing models, to understand how agencies’ tweeting patterns are associated with rider interaction outcomes during the pandemic. From the transit agency perspective, we find smaller agencies tend to generate a higher percentage of COVID-related tweets and some agencies are more repetitive than their peers. Six topics (i.e., face covering, essential service appreciation, free resources, social distancing, cleaning, and service updates) were identified in the COVID-related tweets. From the followers’ interaction perspective, most agencies gained followers after the start of the pandemic (i.e., March 2020). The percentage of follower gains is positively correlated with the percentage of COVID-related tweets, tweets replying to followers, and tweets using outlinks. The average like counts per COVID-related tweet is positively correlated with the percentage of COVID-related tweets and negatively correlated with the percentage of tweets discussing social distancing and agency repetitiveness. This work can inform transportation planners and transit agencies on how to use Twitter to effectively communicate with riders to improve public perception of health and safety as it relates to transit ridership during delays and long-term disruptions such as those created by the COVID-19 public health crisis.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-10T07:58:46Z
      DOI: 10.1177/23998083221135609
       
  • Exploring the role of accessibility in shaping retail location using space
           syntax measures: A panel-data analysis in Lisbon, 1995–2010

    • Free pre-print version: Loading...

      Authors: Rui Colaço, João de Abreu e Silva
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Although location theory is now almost two centuries old, the firms' location choice processes areyet to be fully understood. And while accessibility, in some form, has long been used as an explanatory factor, spatial configuration measures (space syntax) have hardly been used in location models, and longitudinal analyses have also been infrequent. Therefore, a panel multinomial logit model is implemented in Lisbon to explore the role of this specific type of accessibility measures in shaping firm location, throughout a 15-year period, using data from 1995, 2002 and 2010. The analysis is focused on retail activity (five retail categories), restaurants and cafes. The results show that firm location can persistently be related to Local integration and Choice, although the magnitude of the relationship changes depending on the commercial category. These results reinforce the general idea that good urban design can potentially counteract information costs and help commerce locate in new areas of the city while allowing it to continue to succeed in the city’s older, more central areas.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-08T12:26:14Z
      DOI: 10.1177/23998083221138570
       
  • Challenges of consultant-led planning in India’s smart cities
           mission

    • Free pre-print version: Loading...

      Authors: Surajit Chakravarty, Mohammed S Bin Mansoor, Bibek Kumar, Priya Seetharaman
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The growing involvement of private-sector consultants in urban planning has been critiqued as a potential problem, mainly due to doubts over their ethical position. India’s Smart Cities Mission which aims to equip 100 cities with smart technologies, relies on private consultants both to plan the interventions and to implement them. With the planning phase now complete, and implementation in its early stages, this study examines the proposals generated by the consultants. The study deploys natural language processing computational techniques to compare a large corpus of text extracted from the proposal documents to a framework of common planning terms. The analysis yields insights regarding the consultants’ “styles,” and the evolution of the proposals over four rounds of selection. Findings suggest that some consultants show better results than others, but as many as a third of the reports prepared for the mission have low scores on the study’s metrics. In addition, a close reading of the program design helps understand the institutional context within which consultants are embedded. The paper concludes with recommendations for closer scrutiny of the consultants’ work within the mission.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-08T11:45:40Z
      DOI: 10.1177/23998083221137078
       
  • Coupled use of isovists and wavelets for street intersection pattern
           determination

    • Free pre-print version: Loading...

      Authors: Thomas Leduc
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The city is a complex “object” whose structure can be studied at several levels of scale. In this article, we propose to work on the scale of the street, the one in which the pedestrian is immersed, and more precisely on the scale of its articulations, the street intersections. These are indeed structuring places, variously walkable, potentially difficult to cross, which a methodical description can facilitate the use. To this end, we operate, in each intersection, a matching between the shape of the open space as captured by the pedestrian in immersion (this visual pattern is more commonly called the isovist) and a corpus of geospatial patterns. This matching exploits a wavelet compression technique from signal processing which also has the advantage of evaluating the orientation of the pattern. The different urban fabrics presented during the comparative analysis highlight the versatility of the method but also its scalability.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-08T08:54:53Z
      DOI: 10.1177/23998083221138833
       
  • Analysis of spatial form and structure of commercial pedestrian blocks
           based on Isovist and big data

    • Free pre-print version: Loading...

      Authors: Ye Sun, Wei Lu, Zongchao Gu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Commercial pedestrian blocks play an indispensable role in urban life. With the development of urban commercial intensification, the construction of commercial pedestrian blocks has ushered in a period of rapid development. To explore the spatial form and structural features of commercial pedestrian blocks, we examined the Qingniwa-Tianjin Street commercial pedestrian block in Dalian, China. We developed a new quantitative research method, using Isovist-App software simulation, big data statistics and Arc GIS analysis methods to explore the spatial morphological structure characteristics of commercial districts. The results show that Tianjin Street’s pedestrian axis has low spatial permeability and monotonous browsing routes. This suggests that the outdoor pedestrian space design does not attract crowds to wander around and stroll. The overall centrality of the space was relatively high, and the spatial accessibility was good. The walking route provided a wide field of vision, stimulating people’s desire for exploration. The space is highly guided, and people can visit according to the designed route. There is a big difference in the spatial aggregation and dispersion of POI facilities. Transportation, sports, and leisure facilities are the most evenly distributed, while shopping and life service street facilities vary considerably. During holidays, the intensity and duration of crowd activities are the largest, followed by working days and weekends. The people in the block mainly gather in the western and southern commercial complexes, and the attractiveness of outdoor pedestrian streets is lower than that of commercial complexes. Node space B has pedestrian streets with varying spatial interfaces and inconsistent visual appeal. The results can be used to support the spatial form and structural renewal design of commercial pedestrian blocks. The methods presented in this study provide a quantitative approach for the spatial analysis of other functional areas in the city.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-07T12:56:01Z
      DOI: 10.1177/23998083221138571
       
  • The cityseer Python package for pedestrian-scale network-based urban
           analysis

    • Free pre-print version: Loading...

      Authors: Gareth Simons
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      cityseer-api is a Python package consisting of computational tools for fine-grained street-network and land-use analysis, helpful in assessing the morphological precursors to vibrant neighbourhoods. It is underpinned by network-based methods developed specifically for urban analysis at the pedestrian scale. cityseer-api computes a variety of node and segment-based network centrality methods, land-use accessibility and mixed-use measures, and statistical aggregations. Accessibilities and aggregations are computed dynamically over the street-network while taking walking distance thresholds and the direction of approach into account, and can optionally incorporate spatial impedances and network decomposition to increase spatial precision. The use of Python facilitates compatibility with popular computational tools for network manipulation (NetworkX), geospatial topology (shapely), geospatial data state management (GeoPandas), and the NumPy stack of scientific packages. The provision of robust network cleaning tools aids the use of OpenStreetMap data for network analysis. Underlying loop-intensive algorithms are implemented in Numba JIT compiled code so that the methods scale efficiently to larger cities and regions. Online documentation is available from cityseer.benchmarkurbanism.com, and the Github repository is available at github.com/benchmark-urbanism/cityseer. Example notebooks are available at cityseer.benchmarkurbanism.com/examples/
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-11-05T07:33:44Z
      DOI: 10.1177/23998083221133827
       
  • Let’s discuss our city! Engaging youth in the co-creation of living
           environments with digital serious geogames and gamified storytelling

    • Free pre-print version: Loading...

      Authors: Alenka Poplin, Bruno de Andrade, Ítalo de Sena
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This article concentrates on ways in which novel playful technologies can engage youth in co-creation of living environments. The presented study focuses on five selected prototypes of serious digital geogames and gamified storytelling that were developed specifically for younger generations of users. The analysis concentrates on reviewing their goals, game story, outcomes, and the results of testing serious digital geogames prototypes with youth. It leads to a set of identified urban planning engagement forms that can be well supported with the help of serious digital geogames. They include exploring landscapes, learning about places, learning about specific topics, reconstructing the past, envisioning the future, connecting with action projects, and communicating. The article concludes with the discussion of the main findings and perspectives for further research.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-10-25T06:32:40Z
      DOI: 10.1177/23998083221133828
       
  • Exploring large-scale spatial distribution of fear of crime by integrating
           small sample surveys and massive street view images

    • Free pre-print version: Loading...

      Authors: Fengrui Jing, Lin Liu, Suhong Zhou, Zhenlong Li, Jiangyu Song, Linsen Wang, Ruofei Ma, Xiaoming Li
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      A tremendous amount of research use questionnaires to obtain individuals’ fear of crime and aggregate it to the neighborhood level to measure the spatial distribution of fear of crime. However, the cost of using questionnaires to measure the large-scale spatial distribution of fear of crime is high. The built environment is known to influence people’s perceptions, including fear of crime. This study develops a machine learning model to link built environment extracted from street view images to fear of crime obtained from questionnaires, and then applies this model to extrapolate fear of crime for neighborhoods without the questionnaires. Using massive street view images and a survey among 1,741 residents in 80 neighborhoods in Guangzhou, China, this study developed a novel systematic approach to measuring large-scale spatial fear of crime at the neighborhood level for 1,753 neighborhoods. This is the first study to measure fear of crime at the neighborhood level for a metropolitan area of nearly 20 million people. The integration of survey data and street view images provides an opportunity to develop a more effective way to measure the spatial distribution of fear of crime. This approach could be applied to map other types of perceptions at a spatial resolution of the neighborhood level.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-10-25T01:39:13Z
      DOI: 10.1177/23998083221135608
       
  • Data-driven micromobility network planning for demand and safety

    • Free pre-print version: Loading...

      Authors: Pietro Folco, Laetitia Gauvin, Michele Tizzoni, Michael Szell
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Developing safe infrastructure for micromobility like bicycles or e-scooters is an efficient pathway towards climate-friendly, sustainable, and livable cities. However, urban micromobility infrastructure is typically planned ad-hoc and at best informed by survey data. Here, we study how data of micromobility trips and crashes can shape and automatize such network planning processes. We introduce a parameter that tunes the focus between demand-based and safety-based development, and investigate systematically this tradeoff for the city of Turin. We find that a full focus on demand or safety generates different network extensions in the short term, with an optimal tradeoff in-between. In the long term, our framework improves overall network quality independent of short-term focus. Thus, we show how a data-driven process can provide urban planners with automated assistance for variable short-term scenario planning while maintaining the long-term goal of a sustainable, city-spanning micromobility network.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-10-22T09:09:17Z
      DOI: 10.1177/23998083221135611
       
  • Income-related spatial concentration of individual social capital in
           cities

    • Free pre-print version: Loading...

      Authors: Ádám J Kovács, Sándor Juhász, Eszter Bokányi, Balázs Lengyel
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Social connections that span across diverse urban neighborhoods can support prosperity by mobilizing social capital. However, there is limited evidence on the spatial structure of individual social capital inside cities. This paper demonstrates that social capital measured by online social connections is spatially more concentrated for residents of lower-income neighborhoods than for residents of higher-income neighborhoods. We map the micro-geography of individual online social networks in the 50 largest metropolitan areas of the United States using a large-scale geolocalized Twitter dataset. We analyze the spatial dimension of individual social capital by the share of friends, closed triangles, and share of supported ties within circles of short distance radii (1, 3, 5, and 10 km) around users’ home location. We compare residents from below-median income neighborhoods with above-median income neighborhoods, and find that users living in relatively poorer neighborhoods have a significantly higher share of connections in close proximity. Moreover, their network is more cohesive and supported within a short distance from their home. These patterns prevail across the 50 largest US metropolitan areas with only a few exceptions. The found disparities in the micro-geographic concentration of social capital can feed segregation and income inequality within cities constraining social circles of low-income residents.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-10-18T04:43:31Z
      DOI: 10.1177/23998083221120663
       
  • Urban form and COVID-19 cases and deaths in Greater London: An urban
           morphometric approach

    • Free pre-print version: Loading...

      Authors: Alessandro Venerandi, Luca Maria Aiello, Sergio Porta
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The COVID-19 pandemic generated a considerable debate in relation to urban density. This is an old debate, originated in mid 19th century’s England with the emergence of public health and urban planning disciplines. While popularly linked, evidence suggests that such relationship cannot be generally assumed. Furthermore, urban density has been investigated in a spatially coarse manner (predominantly at city level) and never contextualised with other descriptors of urban form. In this work, we explore COVID-19 and urban form in Greater London, relating a comprehensive set of morphometric descriptors (including built-up density) to COVID-19 deaths and cases, while controlling for socioeconomic, ethnicity, age and co-morbidity. We describe urban form at individual building level and then aggregate information for official neighbourhoods, allowing for a detailed intra-urban representation. Results show that: (i) control variables significantly explain more variance of both COVID-19 cases and deaths than the morphometric descriptors; (ii) of what the latter can explain, built-up density is indeed the most associated, though inversely. The typical London neighbourhood with high levels of COVID-19 infections and deaths resembles a suburb, featuring a low-density urban fabric dotted by larger free-standing buildings and framed by a poorly inter-connected street network.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-10-15T03:39:55Z
      DOI: 10.1177/23998083221133397
       
  • Measuring the superblock based on a hierarchy matrix of geometry,
           configuration, network, and area: The case of Nanjing

    • Free pre-print version: Loading...

      Authors: Yacheng Song, Yueting Pang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      A superblock is a core unit of the built form of an old city in China, in which various morphological elements are organized and related through a hierarchical structure. Existing quantitative studies are generally limited to a single perspective or object and do not support the classification of morphological types through comprehensive analysis methods. In this study, a new cognitive framework, the hierarchy matrix, is presented to bridge this knowledge gap. It consists of four dimensions: configuration of network, geometry of network, configuration of area, and geometry of area. These dimensions are formed by the intersection of the two coordinates of perspective and object. Based on their measurement, the overall characteristics of the superblocks are represented and compared through matrix diagrams. Subsequently, the validity and adaptability of this quantitative approach are verified through an empirical analysis of Nanjing’s old city superblocks. The results reveal the morphological type of superblocks, and their causes are analyzed through the correlation with the urban environmental background. hierarchy matrix is potentially a useful method for studying the complex emerging built form of rapidly changing cities, especially in developing countries, such as China. The hierarchical matrix method is not only an analysis tool but also has the potential to develop an evaluation method to provide scientific support for the practice of urban renewal.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-10-14T01:17:47Z
      DOI: 10.1177/23998083221133393
       
  • Estimating the effects of urban green regions in terms of diffusion

    • Free pre-print version: Loading...

      Authors: Eric K Tokuda, Henrique F de Arruda, Guilherme S Domingues, Luciano da F Costa, Florence AS Shibata, Roberto M Cesar-Jr, Cesar H Comin
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The interaction between cities and their respective green regions corresponds to an interesting issue that has received growing attention over the last decades. These relationships have multiple natures, ranging from providing habitat for animal life to temperature and humidity dynamics. Several methods based on area, size, shape, and distance have been considered in the literature. Given that several important contributions of green regions to urban areas involve temperature, humidity, and gases exchanges, which are intrinsically related to physical diffusion, it becomes particularly interesting to simulate the diffusion of green effects over urban areas as a means of better understanding the respective influences. The present work reports a related approach. Once the green regions of a given city are automatically identified by semantic segmentation and have eventual artifacts eliminated, successive convolutions are applied as a means to obtain the unfolding of the diffusion of the green effects along time. As illustrated, the diffusion dynamics is intrinsically interesting because it can be strongly affected by the spatial distribution of the green mass. In particular, we observed that smaller green regions could substantially contribute to the diffusion. The reported approach has been illustrated with respect to the Brazilian city of Ribeirão Preto, whose small- and medium-sized green regions were found to complement in an effective manner the diffusion of the green effects as inferred from the performed simulations under specific parameter settings.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-10-05T08:56:22Z
      DOI: 10.1177/23998083221131572
       
  • Housing price indices from online listing data: Addressing the spatial
           bias with sampling weights

    • Free pre-print version: Loading...

      Authors: Esteban Lopez Ochoa
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This paper proposes a method to reduce the inherent sampling bias when estimating housing price indices using online listing data. Producing more accurate and representative metrics is important as new sources of data emerge with higher frequency, detail, and volume, providing more information for policymaking, but usually come with strong sampling biases that are often overlooked. In the case of housing price indices, although the literature around its estimation is abundant, it has concentrated only in traditional and formal sources of housing data, which is normally not available in some markets (i.e. renting) and locations (developing countries). In this paper, I propose a method to create a housing price index (HPI) that is comparable in quality to the industry-standard Case-Shiller HPI but using online listing data. Using online listing data from a developing economy (Chile), this paper shows that large sampling biases present when using raw unweighted data, how these biases can be minimized using sampling weights, and how new and relevant information can be obtained from adjusted HPIs that can lead better policymaking.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-10-04T05:06:25Z
      DOI: 10.1177/23998083221130713
       
  • Disadvantaged communities have lower access to urban infrastructure

    • Free pre-print version: Loading...

      Authors: Leonardo Nicoletti, Mikhail Sirenko, Trivik Verma
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Disparity in spatial accessibility is strongly associated with growing inequalities among urban communities. Since improving levels of accessibility for certain communities can provide them with upward social mobility and address social exclusion and inequalities in cities, it is important to understand the nature and distribution of spatial accessibility among urban communities. To support decision-makers in achieving inclusion and fairness in policy interventions in cities, we present an open and data-driven framework to understand the spatial nature of accessibility to infrastructure among the different demographics. We find that accessibility to a wide range of infrastructure in any city (54 cities) converges to a Zipf’s law, suggesting that inequalities also appear proportional to growth processes in these cities. Then, assessing spatial inequalities among the socioeconomically clustered urban profiles for 10 of those cities, we find urban communities are distinctly segregated along social and spatial lines. We find low accessibility scores for populations who have a larger share of minorities, earn less and have a relatively lower number of individuals with a university degree. These findings suggest that the reproducible framework we propose may be instrumental in understanding processes leading to spatial inequalities and in supporting cities to devise targeted measures for addressing inequalities for certain underprivileged communities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-10-04T01:30:19Z
      DOI: 10.1177/23998083221131044
       
  • Factors influencing the performance of virtual reality in urban planning:
           Evidence from a View corridor Virtual Reality project, Beijing

    • Free pre-print version: Loading...

      Authors: Huaxiong Jiang, Stan Geertman, Hao Zhang, Shangyi Zhou
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Virtual reality (VR) technologies, as new forms of planning support systems (PSSs), are becoming increasingly vital to planning. However, there is a lack of empirical research on factors influencing VR’s supportive role from a user perspective, thus producing barriers to VR’s advancement in planning practices. This neglect motivates the focus of this study, in which we adapt relevant PSS theory to build a conceptual framework that examines factors influencing VR performance in an experience-based environment. Empirical data are gathered predominantly through students’ experiences with and evaluation of the “Viewing the Western Hills at Yinding Bridge” (Yinding Guanshan) VR Project—a VR system developed to optimize the view corridor of Beijing’s Western Hills. The results show large variability in factors influencing VR performance. In general, the effects of six factors are significant, including 3D visualization, simulating real-world scenes, user-friendliness, interactivity, inspiring participants’ enthusiasm, and inspiring creative thinking. These factors are attributed to the functionality, usability and innovativeness dimensions of VR systems. This study concludes that to realize the supportive and useful role of VR in planning, at minimum, these six factors should be explicitly taken into account.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-30T01:37:24Z
      DOI: 10.1177/23998083221130709
       
  • A data-driven investigation on park visitation and income mixing of
           visitors in New York City

    • Free pre-print version: Loading...

      Authors: Hanxue Wei, Xiao Huang, Sicheng Wang, Junyu Lu, Zhenlong Li, Liao Zhu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      It is crucial to understand the current pattern of urban park visitation to achieve environmental justice. Current discussions of environmental equity of parks mainly focus on the inequality provision measured by park accessibility, park area, park quality, and park congestion, ignoring the inequity of social benefits through interactions among mixed-income groups. Based on fine-grained mobile phone location data at the census block group level in 2018 and 2019, we explored visitation patterns and the mixed-income levels of visitors in urban parks in New York City. The visitors were divided into five income groups, with the “income entropy” used as a measure of the mixed level of the visitors in terms of income groups. We answered an important question: what factors affect the visitation intensity and the mixed level of income groups in urban park visitors' Our results revealed that the time of year and season, the parks’ characteristics, the built environment, and the socioeconomic characteristics of the park’s surrounding neighborhoods have strong associations with park use patterns. We also offered implications for urban planning and urban design to promote park visitation and income-diverse park use and improve social inclusion and environmental equity.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-29T11:58:06Z
      DOI: 10.1177/23998083221130708
       
  • Evaluating the effects of heat vulnerability on heat-related emergency
           medical service incidents: Lessons from Austin, Texas

    • Free pre-print version: Loading...

      Authors: Kijin Seong, Junfeng Jiao, Akhil Mandalapu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Extreme heat exposure and sensitivity have been a growing concern in urban regions as the effects of extreme heat pose a threat to public health, the water supply, and the infrastructure. Heat-related illnesses demand an immediate Emergency Medical Service (EMS) response since they might result in death or serious disability if not treated quickly. Despite increased concerns about urban heat waves and relevant health issues, a limited amount of research has investigated the effects of heat vulnerability on heat-related illnesses. This study explores the geographical distribution of heat vulnerability in the city of Austin and Travis County areas of Texas and identifies neighborhoods with a high degree of heat vulnerability and restricted EMS accessibility. We conducted negative binomial regressions to investigate the effects of heat vulnerability on heat-related EMS incidents. Heat-related EMS calls have increased in neighborhoods with more impervious surfaces, Hispanics, those receiving social benefits, people living alone, and the elderly. Higher urban capacity, including efficient road networks, water areas, and green spaces, is likely to reduce heat-related EMS incidents. This study provides data-driven evidence to help planners prioritize vulnerable locations and concentrate local efforts on addressing heat-related health concerns.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-27T12:31:34Z
      DOI: 10.1177/23998083221129618
       
  • Measuring and mapping neighborhood opportunity: A comparison of
           opportunity indices in California

    • Free pre-print version: Loading...

      Authors: Noli Brazil, Jenny Wagner, Raziel Ramil
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Backed by decades of empirical research, there has been increasing acknowledgment in policy, practice and research of the importance of neighborhood opportunity in shaping well-being. This has led to the proliferation of opportunity maps in cities throughout the United States with the purpose of identifying low opportunity neighborhoods in need of investment and intervention and high opportunity neighborhoods that can offer access to resources and amenities to disadvantaged population groups. By explicitly linking investment to the identification of neighborhoods that are high or low in opportunity, opportunity indices have the potential to help transform local and regional landscapes of spatial inequality. Despite this common goal, indices rely on varying theoretical conceptualizations, data, variables, and statistical approaches. How much these opportunity definitions overlap has yet to be fully examined. In this study, we compared five approaches to measuring neighborhood opportunity in California. We found low to moderate overlap across the indices, with disagreement higher for low opportunity designations. As with any quantitative analysis, opportunity mapping is not a purely technical exercise and requires a series of subjective decisions. The only way to validate these decisions is for opportunity measures to be constructed transparently and vetted by the research community. This study is a first step in this process.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-27T05:06:28Z
      DOI: 10.1177/23998083221129616
       
  • The impact of geometric and land use elements on the perceived
           pleasantness of urban layouts

    • Free pre-print version: Loading...

      Authors: Nuno Sousa, João Monteiro, Eduardo Natividade-Jesus, João Coutinho-Rodrigues
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This article presents a model to estimate the impact of geometric and land use elements on citizens’ perception of urban layout pleasantness. An ordinal regression cumulative link mixed model with those elements as regressors is proposed and calibrated using data from an online survey. Results show that landscape building height and density of green areas are the factors that most impact the perception of pleasantness. Based on the model, a methodology to derive pleasantness mean scores for a city is also proposed and applied to a case study. The methodology allows for benchmarking the pleasantness of different cities or comparing neighborhoods within a city. It can be used both as an urban evaluation tool and a decision-aid for city expansion programs.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-27T01:20:24Z
      DOI: 10.1177/23998083221129879
       
  • Geographies of grocery shopping in major Canadian cities: Evidence from
           large-scale mobile app data

    • Free pre-print version: Loading...

      Authors: Lindsey G Smith, Maggie Yifei Ma, Michael J Widener, Steven Farber
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Socioeconomic and place-based factors contribute to grocery shopping patterns which may be important for diet and health. Big data provide the opportunity to explore behaviours at the population level. We used data collected from Flipp, a free all-in-one savings and deals content app, to identify visitation to grocery stores and estimate home-to-store distances, monthly frequencies and number of unique stores visited in eight Canadian cities during 2020. Grocery shopping outcomes and associations with income, population density and percentage of car commuters were explored using data aggregated at the Aggregate Dissemination Area level in which app users lived. Changes in patterns of grocery shopping following restrictions implemented in response to the COVID-19 pandemic were also investigated. The median of average home-to-store distances ranged from 4 to 5 km across all cities throughout 2020. Shorter distances for grocery shopping were shown consistently for shoppers living in lower income, densely populated and low car-commuting ADAs. A maximum of three unique supermarkets were visited on average each month. Decreases in the frequency and variability of grocery store visits were shown across all cities in April 2020 following the implementation of restrictions in response to COVID-19, and pre-pandemic levels of shopping were rarely achieved by the end of the year. Ultimately, these results provide much needed information regarding the characteristics of grocery shopping trips in a high-income country, as well as how food shopping was impacted by the onset of the COVID-19 pandemic. This information will be useful for a range of future studies seeking to characterise access to food retail.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-26T03:50:20Z
      DOI: 10.1177/23998083221129272
       
  • Factors influencing vertical urban development at the parcel scale: The
           case in Brisbane, Australia

    • Free pre-print version: Loading...

      Authors: Yuanyuan Huang, Scott N. Lieske, Yan Liu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Increasing urban density has become an important focus in mitigating the adverse impacts of urban sprawl. A common way to increase urban density is the development of multi-story residential housing, or vertical urban development (VUD). Compared to low-rise detached housing, VUD has been purported to be more effective in mitigating the adverse impact of urban sprawl. This paper examines factors influencing VUD through a case study of Brisbane, Australia. Three types of housing developments – low-rise detached houses, low-rise apartments, and medium- to high-rise apartments – are explored, with the latter two types classified as VUD. Building on the literature that suggests a range of environmental, socio-demographic, built environment, and planning regulations factors driving or constraining VUD, our study further explores how land parcel size and parcel change over time either through parcel amalgamation or subdivision as factors driving VUD. The findings show that parcel size and parcel amalgamation are key factors leading to VUD, particularly in the form of medium- to high-rise apartment development. On the other hand, land use upzoning alone does not appear to be sufficient to drive VUD. Our study enriches the understanding of the scale effects of land parcels and zoning regulation on vertical urban development, and contributes to parcel-based land use planning policies that are targeted at more intensive urban land use.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-24T10:50:39Z
      DOI: 10.1177/23998083221129283
       
  • A method to derive small area estimates of linked commuting trips by mode
           from open source LODES and ACS data

    • Free pre-print version: Loading...

      Authors: Kevin Credit, Zander Arnao
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This paper describes a fully customizable open source method to create linked origin-destination data on commuting flows by mode at the Census tract scale by combining LODES and ACS data from the US Census Bureau. With additional work, the method could be scaled to the entire US (with a small number of exceptions) for every year from 2002 to 2019. For demonstration purposes, the paper applies this method to 2015 commuting flows in Cook County, Illinois. At an aggregate scale, the results of this application show that commuting by all modes is dominated by travel to large regional employment centres. However, the pattern is more localised for the walking mode, and focused along corridors of mode-specific infrastructure investment for the cycling and transit modes, as might be expected. The auto and work from home modes demonstrate the most distributed pattern of travel, revealing more instances of commuting to regional sub-centres than the other modes.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-24T07:03:59Z
      DOI: 10.1177/23998083221129614
       
  • Predicting onset risk of COVID-19 symptom to support healthy travel route
           planning in the new normal of long-term coexistence with SARS-CoV-2

    • Free pre-print version: Loading...

      Authors: Chengzhuo Tong, Wenzhong Shi, Anshu Zhang, Zhicheng Shi
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Due to the increased outdoor transmission risk of new SARS-COV-2 variants, the health of urban residents in daily travel is being threatened. In the new normal of long-term coexistence with SARS-CoV-2, how to avoid being infected by SARS-CoV-2 in daily travel has become a key issue. Hence, a spatiotemporal solution has been proposed to assist healthy travel route planning. Firstly, an enhanced urban-community-scale geographic model was proposed to predict daily COVID-19 symptom onset risk by incorporating the real-time effective reproduction numbers, and daily population variation of fully vaccinated. On-road onset risk predictions in the next following days were then extracted for searching healthy routes with the least onset risk values. The healthy route planning was further implemented in a mobile application. Hong Kong, one of the representative highly populated cities, has been chosen as an example to apply the spatiotemporal solution. The application results in the four epidemic waves of Hong Kong show that based on the high accurate prediction of COVID-19 symptom onset risk, the healthy route planning could reduce people’s exposure to the COVID-19 symptoms onset risk. To sum, the proposed solution can be applied to support the healthy travel of residents in more cities in the new normalcy.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-17T02:35:16Z
      DOI: 10.1177/23998083221127703
       
  • Visual impact assessment of urban developments around heritage landmarks
           using ULVIA method: (The case of Ark-e-Alishah monument in Tabriz)

    • Free pre-print version: Loading...

      Authors: Sirwan Salimi, Morteza Mirgholami, Amir Shakibamanesh
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban intensification and erection of high-rise buildings can affect the visibility of urban landmarks and pedestrians’ viewshed toward important monuments. Current 2D and 3D Isovist techniques use static rather than dynamic and cumulative view sheds to analyze visibility. The purpose of this research is to develop a method called ULVIA to assess the average visibility degree of urban landmarks in urban design process. Several factors such as observer and environmental characteristics as well as the concept of cumulative viewshed (using Nurbs data and ray casting in Grasshopper) have been considered to develop this method. Ark-e-Alishah Mosque in Tabriz was selected as a case study and three alternative 3D urban models were reproduced based on data and aerial photos of the monument and its urban context in 2003, 2020 and a proposed model. The ULVIA is executed in sequential steps. The findings reveal that the 2003 urban fabric creates visibility with normal intensity and distribution in all paths, the 2020 option does not have this balance, and the difference between riding and pedestrian mode is higher. The final proposed alternative has a higher visibility intensity and better distribution in both pedestrian and rider modes than other alternatives and therefore UlVIA has the potential to be integrated into urban design process to assess various development alternatives to achieve the best results in terms of historical landmarks’ visibility from surrounding environments.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-14T12:40:42Z
      DOI: 10.1177/23998083221123812
       
  • COVID-19 pandemic and minority health disparities in New York City: A
           spatial and temporal perspective

    • Free pre-print version: Loading...

      Authors: Rui Li, Youqin Huang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      New York City (NYC) was the epicenter of COVID-19 pandemic for a long time, and the government introduced a city-wide lockdown policy to mitigate the spread of virus. Minority communities, however, suffered disproportionally high percentage of infection and mortality rates, a disturbing phenomenon that deserves scrutiny. Adopting a spatial and temporal perspective, this study aims to investigate health disparities in this pandemic by focusing on mobility in the city. Considering both public transit and the lockdown policy essential factors that impact infection and mortality, this study introduced a measure indicating mobility-restricted transit as the spatial factor. Additional factors include ethnic minorities based on their nativity and three categories of social vulnerability: socioeconomic status, household composition, and housing type. This study selects eight phases, each of which consists of 2 weeks to derive infection and mortality rates to investigate the impacts of those factors. As infection and mortality data are published based on ZIP code, this study further estimates the infection and mortality rates at a finer level of census tract through spatial apportionment. Results reveal the significant impact of mobility-restricted transit on both infection and mortality and show certain clusters of neighborhoods being highly impacted. In addition, this study identifies neighborhoods where native-born and foreign-born of each ethnic minority (Blacks, Hispanics, and Asians) have high risk of infection and mortality. Through a spatial and temporal perspectives, this study identifies the complexity of patterns in minority health disparities in COVID-19 pandemic, which can inform policy makers for localized support to vulnerable neighborhoods to alleviate minority health disparities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-14T10:54:13Z
      DOI: 10.1177/23998083221126525
       
  • Ownership diversity and fragmentation: A barrier to urban centre
           resilience

    • Free pre-print version: Loading...

      Authors: Allison M Orr, Joanna L Stewart, Cath Jackson, James T White
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Fragmentation of ownership has long been a recognised constraint to UK city centre development, a complexity that is growing in significance as centres try to manage the decline in physical retailing and transform obsolete retail units. Yet, our understanding of the structure of ownership and how that might be facilitating or inhibiting urban change remains weak. In this paper, the objective is to address this gap by examining the structure and diversity of land ownership in five retailing centres - Edinburgh, Glasgow, Hull, Liverpool, and Nottingham – between 2000–2017 using original databases created by linking administrative and commercial property data sets. Overall, the analysis finds property ownership to be spatially complex with ownership richness and diversity generally rising over the study period. The study also reveals that ownership structure has been shifting away from financial institutions towards overseas investors, private individuals and unlisted property companies, implying greater fragmentation of ownership. While the greater diversity in ownership should stimulate competition and innovation in property market practices, the shift in balance from equity-rich larger investors towards smaller and sometimes unknown investors makes urban centre management harder to manage. This suggests policymakers need to rethink the urban governance model to find a better way to galvanise the actions of this increasing disparate group of stakeholders if their visions of more resilient, mixed use city centres are to be realised.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-05T10:17:10Z
      DOI: 10.1177/23998083221124600
       
  • COVID-19 impacts on non-work travel patterns: A place-based investigation
           using smartphone mobility data

    • Free pre-print version: Loading...

      Authors: Yang Song, Sungmin Lee, Amaryllis H Park, Chanam Lee
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The COVID-19 pandemic has brought unprecedented changes to our mobility. It has not only changed our work-related travel patterns but also impacted leisure and other utilitarian activities. Non–work-related trips tend to be more seriously affected by the neighborhood/contextual factors such as socioeconomic status (SES), and destination accessibility, and COVID-19 impact on non-work trips may not be equal across different neighborhood SES. This study compares non–work-related travel patterns between the pre- and during COVID-19 pandemic in the City of El Paso, Texas. By utilizing smartphone mobility data, we captured the visitation data for major non-work destinations such as restaurants, supermarkets, drinking places, religious organizations, and parks. We used Census block groups (n = 424) within the city and divided them into low- and high-income neighborhoods based on the citywide median. Overall, the total frequency of visitations and the distances traveled to visit these non-work destinations were influenced by the COVID-19 pandemic. However, significant variations existed in their visitation patterns by the type of non-work destinations. While the overall COVID-19 effects on non-work activities were evident, its effects on the travel patterns to each destination were not equal by neighborhood SES. We also found that COVID-19 had differently influenced non-work activities between high- and low-income block groups. Our findings suggest that the COVID-19 pandemic may exacerbate neighborhood-level inequalities in non-work trips. Thus, safe and affordable transportation options together with compact and walkable community development appear imperative to support daily travel needs for various utilitarian and leisure purposes, especially in low-income neighborhoods.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-05T01:20:44Z
      DOI: 10.1177/23998083221124930
       
  • Analyzing the impact of three-dimensional visibility value on shopping
           center retail unit rental prices

    • Free pre-print version: Loading...

      Authors: Nur A Khairunnisa, Ahmad Gamal
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This research examines the effect of a three-dimensional visibility value variable on shopping experience and estimates the contribution to retail units’ rental prices for shopping centers. The visibility value in a three-dimensional scheme is measured by adding storefront area volume to existing two-dimensional calculations. This study utilized an explanatory research design and a quantitative analysis method—a STATA regression test—for 150 store units in Jakarta. All units are permanent physical stores, excluding food courts, anchor, and exhibitions. The results showed that visibility value has the positive effect of increasing the average initial rental price by 6% (IDR15,403). The findings of this research can be useful for shopping center managers when estimating rental rates for retail units and architects when considering the visibility factor when designing shopping centers.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-09-01T12:17:33Z
      DOI: 10.1177/23998083221123329
       
  • How applicable are scaling laws in predicting slum populations in urban
           systems' Evidence from India

    • Free pre-print version: Loading...

      Authors: Amit Patel
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Recently, we have seen new developments in our understanding of the emergence and organization of cities and urban systems, including application of scaling laws to urban areas. A recent wave of studies has observed consistent behavior of multiple urban measures that scale with city size across geographic and sectoral contexts. However, the extant evidence is lacking in two important ways: first, a wide variety of urban measures still remain unexplored, and second, there is limited evidence from developing countries. This paper offers new evidence on both these fronts: i) applying scaling laws to predict slum population in cities, an urban measure that remains largely unexplored, and ii) applying them in the context of a developing country, India. Results suggest that population alone is not sufficient to predict slum population in India. Conversely, I use empirical results from scaling laws to test established slum growth theories that have influenced policymaking globally for decades, despite having limited empirical evidence to support them. I also show that scaling exponents are sensitive to the way we define urban systems, of which cities are a part, an issue that has been raised in the ongoing methodological debate on urban scaling laws. I believe that findings presented in this paper have implications for advancement of slum theories as well as urban scaling laws by offering new empirical evidence and mechanisms through which such scaling might happen in the context of slums.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-08-28T02:03:50Z
      DOI: 10.1177/23998083221122793
       
  • Roughness and intermittency within metropolitan regions - Application in
           three French conurbations

    • Free pre-print version: Loading...

      Authors: Janka Lengyel, Stéphane Roux, François Sémécurbe, Stéphane Jaffard
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Even though the past three decades have seen numerous crucial investigations on interurban scaling characteristics, there has been less focus on revealing multiscale properties within municipal or metropolitan structures. We demonstrate how a newly developed methodology, the Geographically Weighted Multiscale Analysis (GWMSA) stemming from the theory of multifractal systems, can be used to analyze small-scale urban environments with respect to their intermittency and roughness simultaneously. To this end, apart from the widely used sand-box method, we introduce wavelet coefficients in the multiscale analysis of urban systems. In more detail, the spatially continuous scanning of the three largest French conurbations—Paris, Marseille, and Lyon—over their territories and at length scales ranging from parcel to neighborhood level will allow to derive and compare globally and locally characteristic scaling exponents. Depending on the feature under analysis, the exponents reveal qualitatively distinct structural properties, whereby the viability of our findings is further verified on four exemplary typologies of multiscale behavior in urban systems. To introduce GWMSA, this paper focuses primarily on morphological characteristics and findings provide a compelling alternative to how we capture and define district-scale spatial organization and interdependencies within urban settlements.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-08-28T01:58:02Z
      DOI: 10.1177/23998083221116120
       
  • A spatial autoregressive geographically weighted quantile regression to
           explore housing rent determinants in Amsterdam and Warsaw

    • Free pre-print version: Loading...

      Authors: Mateusz Tomal, Marco Helbich
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      A hedonic approach is typically performed to identify housing rental or sales price determinants. However, standard hedonic regression models disregard spatial autocorrelation of prices and heterogeneity of housing preferences across space and over price segments. We developed a spatial autoregressive geographically weighted quantile regression (GWQR-SAR) to address these shortcomings. Using data on the determinants of residential rental prices in Warsaw (Poland) and Amsterdam (The Netherlands) as case studies, we applied GWQR-SAR and rigorously compared its performance with alternative mean and quantile hedonic regressions. The results revealed that GWQR-SAR outperforms other models in terms of fitting accuracy. Compared with mean regressions, GWQR-SAR performs better, especially at the tails of the dependent variable distribution, where non-quantile models overestimate low rent values and underestimate high ones. Policy recommendations for the development of private residential rental markets are provided based on our results, which incorporate spatial effects and price segment requirements.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-08-26T02:54:19Z
      DOI: 10.1177/23998083221122790
       
  • Allocating synthetic population to a finer spatial scale: An integer
           quadratic programming formulation

    • Free pre-print version: Loading...

      Authors: Boyam Fabrice Yameogo, Pierre Hankach, Pierre-Olivier Vandanjon, Pascal Gastineau
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Agent-Based Models (ABMs) are being increasingly used to evaluate urban systems, urban policies and environmental impacts. One prerequisite for using the ABM framework consists of generating a synthetic population representative of the actual population, featuring the appropriate attributes with respect to model objectives. A precise spatial positioning of the synthetic population agents is often key to ensuring ABM modeling quality. This paper considers the problem of allocating synthetic population agents to a finer spatial scale. Such an allocation process is performed from a higher-level statistical area where a synthetic population can be generated, that is, a container statistical area (CSA), to several nested non-overlapping elementary statistical areas (ESAs), where only marginals are available. This allocation step relies not only on common attributes between CSA and ESA, but also on additional discriminatory attributes, that is, attributes of interest, estimated from external data sources. The case study examined herein is based on French census and fiscal data. Common attributes include eight socio-demographic variables, totaling 17 modalities. An additional attribute of interest, that is, income, has also been added. The allocation problem at hand is modeled as an integer quadratic programming problem. An exact algorithm is first applied to solve the problem; the applicability of this algorithm proves to be limited to small-size synthetic populations. A heuristic is proposed to handle the allocation of larger-size synthetic populations. Tests carried out on the case study show that this heuristic yields near-optimal solutions; it is also computationally efficient and may fulfill the needs of a majority of users.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-08-20T01:46:01Z
      DOI: 10.1177/23998083221120019
       
  • Towards a 15-minute city: A network-based evaluation framework

    • Free pre-print version: Loading...

      Authors: Shanqi Zhang, Feng Zhen, Yu Kong, Tashi Lobsang, Sicong Zou
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Developing 15-minute cities, where people can access to living essentials within a 15-minute trip, has become a global effort. In addition to practical exercise, researchers have paid attention to the evaluation of 15-minute cities using home-based accessibility approaches. However, existing approaches do not account for human mobility, an important indicator of how people access and interact with urban amenities. In this study, we propose a novel network-based framework that assesses a 15-minute city considering human mobility patterns. We assume that there exists an optimal mobility network, which would maximize human mobility under the constraints of the current distribution of amenities. Locations where the provision of urban amenities does not match local needs are first identified based on the comparison between optimal mobility patterns and their actual counterparts. Built environment, demographic, and network structure factors that contribute to identified mismatch issues are then examined. The empirical study of Nanjing, China, suggests that the proposed framework could enable a dynamic evaluation of 15-minute cities and could provide important insights on policies and intervention strategies of planning and developing 15-minute cities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-08-13T12:56:01Z
      DOI: 10.1177/23998083221118570
       
  • Explaining a century of Swiss regional development by deep learning and
           SHAP values

    • Free pre-print version: Loading...

      Authors: Youxi Lai, Wenzhe Sun, Jan-Dirk Schmöcker, Koji Fukuda, Kay W Axhausen
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      We use a graph convolutional neural network (GCN) for regional development prediction with population, railway network density, and road network density of each municipality as development indicators. By structuring the long-term time series data from 2833 municipalities in Switzerland during the years 1910–2000 as graphs over time, the GCN model interprets the indicators as node features and produces an acceptable prediction accuracy on their future values. Moreover, SHapley Additive exPlanations (SHAPs) are used to make the results of this approach explainable. We develop an algorithm to obtain SHAP values for the GCN and a sensitivity indicator to quantify the marginal contributions of the node features. This explainable GCN with SHAP decomposes the indicator into the contribution by the previous status of the municipality itself and the influence from other municipalities. We show that this provides valuable insights into understanding the history of regional development. Specifically, the results demonstrate that the impacts of geographical and economic constraints and urban sprawl on regional development vary significantly between municipalities and that the constraints are more important in the early 20th century. The model is able to include more information and can be applied to other regions and countries.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-08-13T01:28:25Z
      DOI: 10.1177/23998083221116895
       
  • Comparison of precise and approximated building height: Estimation from
           number of building storeys and spatial variations in the Tokyo
           metropolitan region

    • Free pre-print version: Loading...

      Authors: Hiroyuki Usui
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Precise building height is indispensable for evaluating variability in building heights. However, relevant data are not always available. Conventionally, building height is approximated as the product of the number of building storeys and floor height, called approximated building height. However, there is no consensus on how floor height, a key determinant of approximated building height, should be set. In Japan, increasingly precise building height data are becoming available as an open 3D urban model. This provides the motivation for answering the following research questions, in the context of the Tokyo metropolitan region: (1) What is the difference between approximated and precise building height' (2) How should we set floor height to minimise the difference between approximated and precise building height' The results show that (1) the average difference is −3.46 m if floor height, c, is 5 m, −0.87 m if c is 4 m and 1.71 m if c is 3 m; (2) c = 4 can effectively estimate building height from the number of storeys; and (3) the greatest difference between approximated and precise building height is spatially clustered where commercial zones and industrial zones are allocated, with their degree being dependent on how floor height is set. Furthermore, it is found that (1) in commercial zones and industrial districts, the optimal floor height, defined as the optimal solution which minimises the sum of squared differences between approximated and precise building height, is greater than 4 m; (2) in mid/high rise residential districts, the optimal floor height ranges from 3 to 3.4 m; and (3) in low-rise residential districts, the optimal floor height ranges from 3.5 to 3.9 m. The findings of this paper can help urban planners find the optimal floor height in each district and understand spatial variations in building and floor heights.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-08-11T07:30:30Z
      DOI: 10.1177/23998083221116117
       
  • Digital traces: Mapping Bogotá’s unmapped transit network using
           smartphones and networked databases

    • Free pre-print version: Loading...

      Authors: C Erik Vergel-Tovar, Eric Goldwyn, Jonathan Leape
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      New tools have enabled “civic hackers” and transportation researchers to map previously uncharted transit networks previously confined to the purview of locals and insiders. These new datasets reveal the extent of these systems and their role in providing access to the city. In this paper, we describe the methodology regarding the mapping process of Bogotá’s semi-formal SITP Provisional bus system, accomplished using smartphones, cloud-based data management systems, and GIS software. By visualizing the semi-formal SITP Provisional system alongside the centrally planned bus system, we provide the first complete picture of Bogotá’s transit system. We also develop two types of data analysis based on General Transit Feed Specification (GTFS) data generated from this mapping process. Using spatial algorithms, we identify parallelism between the semi-formal transit routes and the formal transit network. We then visualize the degree of access to job opportunities that each system provides. We find that integrating semi-formal and formal transit services, that is, the entire network, increases accessibility levels for workers, especially at urban peripheries. Results suggest the importance of considering semi-formal transit services in transportation planning, the services often neglected in the planning process, and the advantages of integrating them into the network to increase accessibility to opportunity areas. We recommend that other cities harness GPS-enabled apps to map transit systems, generate GTFS data, and empower local actors to make use of the data. Based on this bottom-up approach, semi-formal transit networks can provide additional inputs for urban transportation planning processes regarding the transportation user´s accessibility needs.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-08-10T02:46:47Z
      DOI: 10.1177/23998083221117831
       
  • Measuring the local complementarity of population, amenities and digital
           activities to identify and understand urban areas of interest

    • Free pre-print version: Loading...

      Authors: Eduardo Graells-Garrido, Rossano Schifanella, Daniela Opitz, Francisco Rowe
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Identifying and understanding areas of interest are essential for urban planning. These areas are normally defined from static features of the resident population and urban amenities. Research has emphasised the importance of human mobility activity to capture the changing nature of these areas throughout the day, and the use of digital applications to reflect the increasing integration between material and online activities. Drawing on mobile phone data, this paper develops a novel approach to identify areas of interest based on the degree of complementarity of digital activities, available amenities and population levels. As a case study, we focus on the largest urban agglomeration of Chile, Santiago, where we identify three distinctive groups of areas: those concentrating (1) high availability of amenities; (2) high diversity of amenities and digital activities; and (3) areas lacking amenities, yet, presenting high usage of digital leisure and mobility applications. These findings identify areas where digital activities and local amenities play a complementary role in association with local population levels, and provide data-driven insights into the structure of material and digital activities in urban spaces that may characterise large Latin American cities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-08-08T01:46:10Z
      DOI: 10.1177/23998083221117830
       
  • Forecasting the urbanization dynamics in the Seoul metropolitan area using
           a long short-term memory–based model

    • Free pre-print version: Loading...

      Authors: Changyeon Lee, Jaekyung Lee, Sungjin Park
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Over the past half century, the Seoul metropolitan area (SMA) has experienced rapid urbanization. Urban development and population growth within the SMA have caused various problems, such as a lack of affordable housing, traffic congestion, and socioeconomic inequality between the SMA and the rest of the country. As a solution, growth control was adopted, but it resulted in increasing housing prices within Seoul. In late 2018, skyrocketing housing prices forced Seoul’s government to abandon its growth-control policy and announce large-scale “new-town” projects planned outside of the city’s urban growth boundary. The primary purpose of this research is to predict future urbanization dynamics by utilizing the long short-term memory (LSTM)–based prediction model. The secondary purpose is to identify the influential driving factors in urbanization that can help policy makers develop evidence-based, informed strategies. To predict future urbanization’s spatial patterns in the SMA, LSTM models have been estimated under two scenarios: (A) assuming that current urbanization trends and contributing factors will remain consistent in the future and (B) considering new development plans’ impacts. A comparison of the modeling results indicates that the government-driven new-town projects will help urbanize 55.8% more land by 2030. The variable influence analysis also reveals that strong growth-control measures may be necessary for areas with higher employment and homeownership rates to control rapid urbanization. However, housing supply and economic growth–related policies in Seoul’s suburbs would help attract the city’s population to the outskirts. The LSTM-based model yields an accurate and reliable spatial prediction in the form of visual maps, and its graphic results will assist policy makers greatly in developing effective strategies for smart urban growth management.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-08-06T10:24:14Z
      DOI: 10.1177/23998083221118002
       
  • Tracking plan implementation using elected officials’ social media
           communications and votes

    • Free pre-print version: Loading...

      Authors: Albert Tonghoon Han, Lucie Laurian
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Plans can only impact practice when elected officials adopt, enact, and approve funding for specific strategies. We explore ways to track implementation from the planning documents to elected officials’ priorities and to their voting patterns to identify the consistencies and gaps that may limit the impact of plans. We use Twitter data mining, text content analysis, and voting records from the digitized council minutes in Calgary, Alberta, between the 2017 municipal election and the last quarter of 2020. We connect the expressed preferences to votes for each councilor over the study period. On the two most salient topics—transit and affordable housing—those who expressed support on Twitter also supported investments. With one exception of an anti-tax councilor, over time, the rest of the councilors reached agreements on public investments (supra-local funding lightened the financial burdens for the city facilitating “yes” votes). Planners can derive meaningful information from the elected officials’ social media communication, such as concerns and support for specific planning initiatives, to promote successful plan implementation. This information can also enhance voters’ awareness of local officials’ views and actions on planning initiatives.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-08-06T05:00:03Z
      DOI: 10.1177/23998083221118003
       
  • How to harmonise variations in streetscape skeletons under zoning
           regulations: Considering their external diseconomies

    • Free pre-print version: Loading...

      Authors: Hiroyuki Usui
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The arrangement of buildings along roads creates one of the most fundamental patterns of three-dimensional streetscape skeletons, primarily defined as a set of building heights and setbacks in a district. Under zoning regulations, building heights and setbacks are indirectly controlled by the building coverage ratio (BCR) and the floor area ratio (FAR). Variations in the BCR result in variations in streetscape skeletons. Moderate complexity of streetscape skeletons is a necessary condition for aesthetic streetscape. Understanding the relationships between variations in the BCR, building heights and setbacks is thus important in order to harmonise streetscape skeletons, smaller variations in building heights, and setbacks, however, this relationship has yet to be theoretically investigated due to the complex relationship between buildings. The objective of this paper is therefore to formulate the relationship between variations in building heights and setbacks as a function of the standard deviation of BCR, and, based on this formulation, to discuss how to indirectly harmonise variations in streetscape skeletons under zoning regulations. This formulation enables us to analytically investigate the relationship between these two functions and the standard deviation of a BCR. An indirect scheme for harmonising variations in streetscape skeletons under zoning regulations is proposed on the basis of this formulation. The external diseconomies of inharmonious streetscape skeletons are quantitatively defined in order to incentivise plot owners to harmonise streetscape skeletons. The optimal building height and setback criteria are computed, which minimises the social cost of inharmonious building heights and building setbacks in a district. This scheme for incentivising plot owners to reduce their social costs is expected to contribute to indirectly harmonising streetscape skeletons.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-08-04T04:20:56Z
      DOI: 10.1177/23998083221116121
       
  • Multimodal urban mobility and multilayer transport networks

    • Free pre-print version: Loading...

      Authors: Laura Alessandretti, Luis Guillermo Natera Orozco, Federico Battiston, Meead Saberi, Michael Szell
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Transportation networks, from bicycle paths to buses and railways, are the backbone of urban mobility. In large metropolitan areas, the integration of different transport modes has become crucial to guarantee the fast and sustainable flow of people. Using a network science approach, multimodal transport systems can be described as multilayer networks, where the networks associated to different transport modes are not considered in isolation, but as a set of interconnected layers. Despite the importance of multimodality in modern cities, a unified view of the topic is currently missing. Here, we provide a comprehensive overview of the emerging research areas of multilayer transport networks and multimodal urban mobility, focusing on contributions from the interdisciplinary fields of complex systems, urban data science, and science of cities. First, we present an introduction to the mathematical framework of multilayer networks. We apply it to survey models of multimodal infrastructures, as well as measures used for quantifying multimodality, and related empirical findings. We review modeling approaches and observational evidence in multimodal mobility and public transport system dynamics, focusing on integrated real-world mobility patterns, where individuals navigate urban systems using different transport modes. We then provide a survey of freely available datasets on multimodal infrastructure and mobility, and a list of open-source tools for their analyses. Finally, we conclude with an outlook on open research questions and promising directions for future research.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-07-20T05:41:14Z
      DOI: 10.1177/23998083221108190
       
  • Methods for neighbourhood Mapping, boundary agreement

    • Free pre-print version: Loading...

      Authors: Nicholas S Dalton, Mark Hurrell
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Any analytical study of a neighbourhood must begin with an accurate definition of the geographic region that contains it. For a long time, there has been an interest in taking surveys of neighbourhood extents, but this can generate numerous haphazardly sketched polygons. Researchers typically face the challenges of using boundary polygons reported by each participant and unifying these polygons into one representative boundary. Over the years, several researchers have reported their findings on methods for unifying these boundaries. We present and compare the following five methods (two existing, one modified and two new): Dalton radial average, Bae–Montello average, a vectorised version of the Bae–Montello raster grid overlay, a vectorised derivative inspired by the Wenhao kernel density axis method maximum kernel density axis and a new k-medians clustering method. A crowd-sourced evaluation method is presented. N=42 raters ranked the five methods of aggregating real boundary data based on the results from three study areas. We found that the boundary aggregation method derived from the Bae–Montello grid, closely followed by the Dalton radial average method, provided the most reasonable results. This paper outlines the reasons for these results and illustrates how this knowledge may point to the ability of future algorithms to improve the presented methods. The paper ends with a recommendation that neighbourhood boundaries should utilise boundaries derived from the Bae–Montello raster grid overlay method and/or the Dalton radial average method to facilitate comparisons in the field.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-07-18T01:57:26Z
      DOI: 10.1177/23998083221115195
       
  • Strategies and inequities in balancing recreation and COVID exposure when
           visiting green spaces

    • Free pre-print version: Loading...

      Authors: Sarina Dass, Daniel T. O’Brien, Alina Ristea
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Green spaces are beneficial for physical and mental health, especially during and after disasters. The COVID-19 pandemic, however, created a trade-off: parks could be therapeutic but also could expose people to infection. This paradox posed inequities as marginalized populations often have less access to parks and were hit harder by the pandemic. We combined cellphone-generated mobility data with demographic indicators, a neighborhood survey, and local infection rates to examine how residents of Boston, MA, navigated this trade-off in April–August 2020. We hypothesized that they adopted strategies for mitigating infection exposure—including fewer park visits and prioritizing parks that might have lower infection risk, including larger parks with more opportunity for social distancing and parks near home with fewer unfamiliar faces—but that marginalized populations would have less opportunity to do so. We also introduce a novel measure of exposure per visit based on the volume of other visitors, infection rates, and park size. Bostonians made fewer park visits relative to 2019 and prioritized larger parks and parks closer to home. These strategies varied by community. Experiences of the pandemic were influential, as communities that perceived greater risk or had more infections made more park visits, likely because they were a relatively safe activity. Communities with more infections tended to avoid nearby parks. Inequities were also apparent. Communities with more Black residents and infections had greater infection exposure per visit even when controlling for the types of parks visited, highlighting difficulties in escaping the challenges of the pandemic.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-07-16T07:57:13Z
      DOI: 10.1177/23998083221114645
       
  • Urban form character and Airbnb in Amsterdam (NL): A morphometric approach

    • Free pre-print version: Loading...

      Authors: Alessandro Venerandi, Alessandra Feliciotti, Martin Fleischmann, Karima Kourtit, Sergio Porta
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Proliferation of Short Term Rental (STR) in cities has generated considerable debate as it was found associated with negative externalities, such as gentrification. Nonetheless, it signals urban qualities working as attractors at different geographical scales. STRs’ relation with urban form remains largely understudied. In this paper, we explore how urban form relates to STRs registered by the Airbnb platform in Amsterdam (NL). First, we identify urban types (homogenous patterns of form) through an ‘urban morphometric’ approach. Second, we assess the relation between urban types and density of Airbnbs via a composite machine learning (ML) technique. Third, we provide profiles of the urban types most strongly associated with it. Fifteen urban types explain up to 44% of Airbnb density’s variance. Compact and diverse urban types relate more strongly with Airbnbs. Conversely, repetitive, sparse and uniform urban types are inversely related. The proposed morphometric-based method is robust, replicable and scalable, offering a novel way to study the intricate relation between urban form, STRs and, in fact, any other measurable urban dynamics at an unprecedented scale. By identifying spatial features related to urban attractiveness, it can inform evidence-based design codes incorporating place-making qualities in existing and new neighbourhoods.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-07-14T03:06:14Z
      DOI: 10.1177/23998083221115196
       
  • Impact of COVID-19 policies on pedestrian traffic and walking patterns

    • Free pre-print version: Loading...

      Authors: Avital Angel, Achituv Cohen, Sagi Dalyot, Pnina Plaut
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The spread of COVID-19 pandemic provoked new policies and restrictions, which had an unprecedented impact on urban mobility and traffic on local and global scales. While changes in motorized traffic were investigated and monitored throughout the recent pandemic crisis in many cities around the world, not much was done on the changes in pedestrian street-traffic and walking patterns during this time. This study aims to identify, quantify, and analyze the changes in pedestrian traffic and walking patterns induced by COVID-19 policies. The “first wave” period of COVID-19 policies in Tel-Aviv, Israel, is used as a case study in this work. The analysis includes over 116 million pedestrian movement records documented by a network of 65 Bluetooth sensors, between 1.2.2020 and 26.7.2020, with a comparison to the equivalent time in 2019 that signifies “normal” pre-COVID-19 conditions. The results show clear correlation between the various COVID-19 policy restrictions and pedestrian count. The shifts to work-from-home and closure of businesses were highly correlated with changes in walking patterns during weekdays, while distinguishing changes in commercial and residential street segments. Nevertheless, while the restrictions dramatically influenced pedestrian movement volume and time of walking, it did not significantly change where people chose to walk, signifying the essentialness of attractive streets, parks and squares for citizens living in urban areas. This study shows how policy affects walking behavior in cities, demonstrating the potential of passive crowdsourced sensing technologies to provide urban planners and decision makers an efficient tool for monitoring and evaluating pedestrian infrastructure implementation in cities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-07-12T01:33:40Z
      DOI: 10.1177/23998083221113332
       
  • Unfolding time, race and class inequalities to access leisure

    • Free pre-print version: Loading...

      Authors: Diego Bogado Tomasiello, Mariana Giannotti
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The access to leisure activities is an important element to understand the potential participation and integration of individuals in the society. Despite its importance, urban planners in large urban centers in developing countries seek to prioritize access to mandatory activities. This study quantifies the accessibility to leisure and its inequalities in the municipality of São Paulo, considering the opening hours of leisure opportunities and racial and class population groups. Tracking data from buses and TomTom speed profile were used in the public and the private transport networks, respectively, to analyze and compare accessibility to parks and cultural equipment. A multitemporal analysis was performed to better understand the fluctuation of accessibility to leisure through different hours considering the opening hours of parks and cultural equipment. The population was stratified into four groups according to race and class (higher black, higher white, lower black, and lower white) to perform accessibility inequalities analysis. Results show that accessibility to leisure is higher for private transport users, it decreases from the central to the peripheral areas, and it changes significantly during the day due to traffic conditions, transit supply, and leisure opportunities opening hours. The Lorenz curves, Gini, and the Palma coefficients showed a highly unequal level of accessibility to leisure for different population groups, with the low-black population having the lowest level of leisure accessibility. Our findings may support policy makers in designing strategies to provide more spatial equity in the access to leisure opportunities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-07-07T06:12:55Z
      DOI: 10.1177/23998083221111405
       
  • The temporality of on-street parking – exploring the role of land-use
           mix and change on parking dynamics

    • Free pre-print version: Loading...

      Authors: Anthony Kimpton, Dominic Stead, Jonathan Corcoran
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Parking is often overlooked by urban researchers even though parking consumes large proportions of a city’s physical footprint and imposes a significant impediment to more sustainable travel. Underpinning this lack of attention is suitable data and methods capable of capturing the complex dynamics of parking. Here we redress this gap by drawing on an emergent source of parking data and deploying empirical techniques to unpack this complexity. Data from 3542 on-street parking sensors observed over a 9-year period are used to delineate the first typology of parking routines before using a fixed-effects logistic regression model to explain how nearby land-use types and land-use mix shapes tempo and timing of parking utilisation. The benefit of our approach lies in its capacity to discriminate broad types of temporal rhythms associated with parking dynamics at particular places, how these change over time and how these rhythms are associated with different types and mixes of nearby land use. This knowledge is important to inform policies seeking to optimise the use of on-street parking and invoke more sustainable patterns of mobility.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-07-06T11:45:17Z
      DOI: 10.1177/23998083221112957
       
  • Marked crosswalks in US transit-oriented station areas, 2007–2020: A
           computer vision approach using street view imagery

    • Free pre-print version: Loading...

      Authors: Meiqing Li, Hao Sheng, Jeremy Irvin, Heejung Chung, Andrew Ying, Tiger Sun, Andrew Y Ng, Daniel A Rodriguez
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Improving the built environment to support walking is a popular strategy to increase urban sustainability and walkability. In the past decade alone, many US cities have implemented crosswalk visibility enhancement programs as part of road safety improvements and active transportation plans. However, there are no systematic ways of measuring and monitoring the presence of key built environment attributes that influence the safety and walkability of an area, such as marked crosswalks. Furthermore, little is known about how these attributes change over time at a national scale. In this paper, we introduce an innovative approach using a deep learning-based computer vision model on Street View images to identify changes in intersection-level marked crosswalks around more than 4,000 US transit stations over a 14-year period. We found an increase in the overall number of marked crosswalks at intersections. Furthermore, high-visibility crosswalks became more common, as they replaced existing parallel-line crosswalks. We further examine crosswalks around transit stations in New York City and San Francisco to illustrate geographic variations and compare associations with other characteristics of the built environment as reported in the Smart Location Database. Areas with increases in high-visibility crosswalks focused on high density residential areas and areas with a higher percent of zero-vehicle households. However, geographic variations exist. For example, in San Francisco, transit station areas outside downtown or major corridors (South and Southwest of the city) had the lower prevalence of marked crosswalks. This analysis confirms important gaps in crosswalk visibility that call for safety enhancements and opens the door for additional research involving these data. We conclude by discussing the limitations and future research opportunities using computer vision to automatically detect large-scale transportation infrastructure changes at a relatively low cost.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-07-04T06:09:00Z
      DOI: 10.1177/23998083221112157
       
  • Future land use conflicts: Comparing spatial scenarios for urban-regional
           planning

    • Free pre-print version: Loading...

      Authors: Cristian Henríquez, Mauricio Morales, Jorge Qüense, Rodrigo Hidalgo
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Latin America’s intensive urbanization processes are triggering rapid peri-urban transformations and the expansion of cities. These include accelerated metropolization processes, urban sprawl, and the emergence of new conurbations. These changes parallel the expansion of highly profitable agricultural activities and plantations linked to international markets. This paper aims to analyze land use/cover changes between 1990 and 2050 in the Quillota Province, Valparaíso Region, Chile. Specific objectives considered (1) analyzing changes in land use/cover trajectories between 1990 and 2017, (2) simulating changes in land use/cover based on three scenarios of territorial planning to 2050 (trending, ecological planning, and spatial planning), and (3), identifying the areas most likely to be modified by urbanization and agricultural activity as a result of biodiversity loss in the study area. The Dyna-CLUE model implemented was complemented with GIS techniques for the analysis of land use/cover trajectories that allowed classifying and characterizing the most dynamic land uses/cover within the Quillota Province, such as urban land uses. The results of simulations to 2050 show a probable conurbation of medium-sized cities of Quillota-La Cruz-Calera, and future land use conflicts between peri urban-agricultural land use and plantation-natural conservation land use. The results suggest that it is essential to choose scenarios to ensure sustainable land use planning to control urban and peri-urban sprawl and protect areas of high natural value.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-07-02T10:38:15Z
      DOI: 10.1177/23998083221111404
       
  • Deep learning-based investigation of the impact of urban form on the
           particulate matter concentration on a neighborhood scale

    • Free pre-print version: Loading...

      Authors: Moon-Hyun Kim, Tae-Hyoung Tommy Gim
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Despite the importance of urban forms to the dispersion of particulate matter (PM), only a few studies exist on the relationship between them due to the limitations of the data and methodology. Thus, this study used a deep learning-based investigation of the impact of urban form on PM2.5 concentration. Autoencoder, long short-term memory (LSTM), and the random forest model were used to analyze their relationship. The random forest model showed that urban form variables predict PM2.5 concentration with a 95.66% accuracy, confirming that urban form characteristics significantly impact PM2.5 concentrations. Among the urban form variables, floor area ratio turned out to be the most important, suggesting the need for more detailed efforts to reduce PM2.5 in locations with high floor areas. The effect on PM2.5 prediction accuracy was evaluated with root mean square error. It was difficult to accurately predict PM2.5 in areas with large building coverage areas and low-rise residential areas. This study improved the accuracy of results on the influence of urban form by using PM2.5 non-aggregated data measured hourly over 4 years, which expanded the applicability of deep learning-based urban analysis.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-06-27T07:36:40Z
      DOI: 10.1177/23998083221111162
       
  • A participatory e-planning model in the urban renewal of China:
           Implications of technologies in facilitating planning participation

    • Free pre-print version: Loading...

      Authors: Li Tian, Jinxuan Liu, Yinlong Liang, Yaxin Wu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      While collaborative planning has gained popularity in addressing conflicts of interest in urban renewal, the development of information communication technologies has provided creative tools in participatory planning. To accommodate the needs of participatory e-planning, we designed a digital collaborative platform composed of four modules to establish a framework for all stakeholders to participate in the urban renewal process in China. By taking a village as a case study (hereafter referred to as village X), this research introduces the application of a digital platform in the renewal of an old village facilitated by a third party. Although the application of e-planning participation in the renewal of X village has been effective, its further application has encountered challenges, such as willingness, the capacity of the residents, and credibility, due to the lack of an institutionalized arrangement. Compared with the West, China has a long way to go in promoting public participation in urban renewal through institutional arrangements. Educating the public and deepening the understanding of local governments in the necessity of public participation should be the future task of urban planners in China. The limitations and further applications of digital platforms are also discussed.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-06-27T05:53:10Z
      DOI: 10.1177/23998083221111163
       
  • Spatial variations of the third and fourth COVID-19 waves in Hong Kong: A
           comparative study using built environment and socio-demographic
           characteristics

    • Free pre-print version: Loading...

      Authors: Zidong Yu, Xintao Liu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Since the first confirmed case was reported in January 2020, Hong Kong has experienced multiple waves of COVID-19 outbreaks. Recent literature has explored the spatial patterns of disease incidence and their relationships with the built environment and demographic characteristics. Nonetheless, few studies aim at the comparative patterns of different epidemic waves occurring in the same spatial context. This study analyses spatial patterns of the third and fourth COVID-19 epidemic waves and then evaluates the spatial relationship between case incidence and built environment and socio-demographic characteristics. By collecting local-related cases, this study incorporates a two-fold analytical strategy: (1) Using rank-size distribution and log-odd ratio to depict the spatial pattern of COVID-19 incidence rates; (2) through global and local regression models, investigating incidence’s associations with the urban built environment and socio-demographic characteristics. The results reveal that the two different epidemic waves have far distinct spatial tendencies to their infection risk factors, reflecting location-specific associations with the built environments and socio-demographics. Collectively, we discover that the third and fourth COVID-19 waves are likely associated with residential context and urban activities, respectively. Practical implications are discussed that would be of interest to policymakers and health professionals.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-06-04T11:54:35Z
      DOI: 10.1177/23998083221107019
       
  • Understanding and predicting the occurrence of void street interfaces

    • Free pre-print version: Loading...

      Authors: Luiz de Carvalho Filho, Patrizia Sulis
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Void street interfaces (VSIs) – building plinths with restricted visual interaction, accessibility, and public use – constitute an urban feature often associated with undermining the public domain, limiting free access and preventing interaction between social groups. Moreover, VSIs have been described as products of inequality designed to segregate and hinder integration between public and private urban spaces. This study assesses VSIs across six cities in Brazil, a country notable for its profound inequality and sociospatial fragmentation. The main aims of this research are: (i) to develop and test a predictive model for VSIs using socioeconomic indicators drawn from open-source ground-truth data; (ii) to identify the variance of VSI within selected case studies. In the development phase of the predictive model, data from the city of Recife are used to build the model. The testing phase involves the analysis of VSIs in the cities of Fortaleza, Salvador, Belo Horizonte, Curitiba and Porto Alegre. The model can potentially assist urban planners in better understanding and locating VSIs and mitigating undesirable outcomes.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-05-13T09:34:52Z
      DOI: 10.1177/23998083221093067
       
  • The geography of public transport competitiveness in thirteen medium sized
           cities

    • Free pre-print version: Loading...

      Authors: Erik B Lunke, Nils Fearnley, Jørgen Aarhaug
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Securing sufficient accessibility with public transport is essential for reducing private car commuting. While most studies of transport accessibility are based on travel times, other quality factors such as the perceived disadvantage of congestion and service frequency are also of importance for transport mode choice. In this study, we use generalized journey times to calculate accessibility and public transport competitiveness, allowing us to account for other characteristics of commute trips than just travel time. We use detailed trip data to calculate generalized journey times to typical employment areas in thirteen urban regions in Norway. The results show that public transport services compete better with the car in the largest cities. Specifically, public transport is competitive for access to central employment areas but less so for less central employment areas. In the smaller cities, the private car is the most competitive mode on most commute trips. With detailed travel data, the method developed in this study can be replicated in other contexts to provide a more holistic measure of accessibility than traditional methods.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-05-09T05:29:19Z
      DOI: 10.1177/23998083221100265
       
  • Exploiting COVID-19 related traffic changes to evaluate flow dependency of
           an FCD-defined congestion measure

    • Free pre-print version: Loading...

      Authors: Megan M Bruwer, Simen J Andersen
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Traffic congestion poses a significant problem in urban areas globally, and yet no measure of congestion is universally applied. Various studies have evaluated congestion measures, however, none have identified and demonstrated a best-practice congestion metric that can compare congestion between road segments, networks, and city zones. Furthermore, no studies have proven the link between a congestion metric and traffic flow, despite suggestion by Lomax et al. in their seminal 1997 Quantifying Congestion report that an appropriate congestion metric should vary predictably according to flow. This paper aims to address these gaps in traffic congestion literature. Various congestion measures are evaluated according to standard criteria. Although this process has been followed before, this paper adds a unique criterion that requires congestion to be quantifiable from commercial floating car data (FCD), due to its extensive availability and relative affordability. The most appropriate congestion measure is evaluated to be the speed reduction index (SRI). The application of the SRI to describe spatiotemporal congestion patterns and flow dependency is then demonstrated in a case-study analysis in South Africa. This analysis exploited traffic impacts of the COVID-19 pandemic in 2020 (particularly, the stepwise increase from severely reduced traffic flows as lockdown levels eased), to evaluate SRI. The wide range of flows enabled an unprecedented regression analysis comparing congestion level and flow. The results of the regression analysis are highly significant (p < 0.001) indicating that SRI-based congestion measurement tracks flow variation. This study further identified that unidirectional congestion, quantified by the SRI, is impacted by high bi-directional flow along arterials. These findings confirm the appropriateness of the SRI quantified from commercial FCD to measure congestion.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-03-29T11:48:05Z
      DOI: 10.1177/23998083221081529
       
  • A microsimulation of spatial inequality in energy access: A bayesian
           multi-level modelling approach for urban India

    • Free pre-print version: Loading...

      Authors: André P Neto-Bradley, Ruchi Choudhary, Peter Challenor
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Access to sustained clean cooking in India is essential to addressing the health burden of indoor air pollution from biomass fuels, but spatial inequality in cities can adversely affect uptake and effectiveness of policies amongst low-income households. Limited data exists on the spatial distribution of energy use in Indian cities, particularly amongst low-income households, and most quantitative studies focus primarily on the effect of economic determinants. A microsimulation approach is proposed, using publicly available data and a Bayesian multi-level model to account for effects of current cooking practices (at a household scale), local socio-cultural context and spatial effects (at a city ward scale). This approach offers previously unavailable insight into the spatial distribution of fuel use and residential energy transition within Indian cities. Uncertainty arising from heterogeneity in the population is factored into fuel use estimates through use of Markov Chain Monte Carlo (MCMC) sampling. The model is applied to four cities in the South Indian states of Kerala and Tamil Nadu, and comparison against ward-level survey data shows consistency with the model estimates. Ward-level effects exemplify how specific wards compare to the city average and to other urban areas in the state, which can help stakeholders design and implement clean cooking interventions tailored to the needs of those households.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-02-24T04:18:10Z
      DOI: 10.1177/23998083211073140
       
  • Using mobile phone big data to discover the spatial patterns of rural
           migrant workers’ return to work in China’s three urban agglomerations
           in the post-COVID-19 era

    • Free pre-print version: Loading...

      Authors: Kai Liu, Pengjun Zhao, Dan Wan, Xiaodong Hai, Zhangyuan He, Qiyang Liu, Yonghui Qu, Xue Zhang, Kaixi Li, Ling Yu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Knowing how workers return to work is a key policymaking issue for economic recovery in the post-COVID-19 era. This paper uses country-wide time-series mobile phone big data (comparing monthly and annual figures), obtained between February 2019 and October 2019 and between February 2020 and October 2020, to discover the spatial patterns of rural migrant workers’ (RMWs’) return to work in China’s three urban agglomerations (UAs): the Beijing–Tianjin–Hebei Region, the Yangtze River Delta and the Pearl River Delta. Spatial patterns of RMWs’ return to work and how these patterns vary with location, city level and human attribute were investigated using the fine-scale social sensing related to post-pandemic human mobility. The results confirmed the multidimensional spatiotemporal differentiations, interaction effects between variable pairs and effects of the actual situation on the changing patterns of RMWs’ return to work. The spatial patterns of RMWs’ return to work in China’s major three UAs can be regarded as a comprehensive and complex interaction result accompanying the nationwide population redistribution, which was affected by various hidden factors. Our findings provide crucial implications and suggestions for data-informed policy decisions for a harmonious society in the post-COVID-19 era.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-02-02T07:22:38Z
      DOI: 10.1177/23998083211069375
       
  • Modelling and simulating ‘informal urbanization’: An integrated
           agent-based and cellular automata model of urban residential growth in
           Ghana

    • Free pre-print version: Loading...

      Authors: Felix S. K. Agyemang, Elisabete Silva, Sean Fox
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The global urban population is expected to grow by 2.5 billion over the next three decades, and 90% of this growth will occur in African and Asian countries. Urban expansion in these regions is often characterised by ‘informal urbanization’ whereby households self-build without planning permission in contexts of ambiguous, insecure or disputed property rights. Despite the scale of informal urbanization, it has received little attention from scholars working in the domains of urban analytics and city science. Towards addressing this gap, we introduce TI-City, an urban growth model designed to predict the locations, legal status and socio-economic status of future residential developments in an African city. In a bottom-up approach, we use agent-based and cellular automata modelling techniques to predict the geospatial behaviour of key urban development actors, including households, real estate developers and government. We apply the model to the city-region of Accra, Ghana, drawing on local data collection, including a household survey, to parameterise the model. Using a multi-spatial-scale validation technique, we compare TI-City’s ability to simulate historically observed built-up patterns with SLEUTH, a highly popular urban growth model. Results show that TI-City outperforms SLEUTH at each scale, suggesting the model could offer a valuable decision support tool in similar city contexts.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-01-13T01:57:04Z
      DOI: 10.1177/23998083211068843
       
  • The Link between Theory and Practice

    • Free pre-print version: Loading...

      Authors: Michael Batty
      First page: 3
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.

      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-12-26T09:29:03Z
      DOI: 10.1177/23998083221149271
       
  • Developing urban biking typologies: Quantifying the complex interactions
           of bicycle ridership, bicycle network and built environment
           characteristics

    • Free pre-print version: Loading...

      Authors: Ben Beck, Meghan Winters, Trisalyn Nelson, Chris Pettit, Simone Z Leao, Meead Saberi, Jason Thompson, Sachith Seneviratne, Kerry Nice, Mark Stevenson
      First page: 7
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Extensive research has been conducted exploring associations between built environment characteristics and biking. However, these approaches have often lacked the ability to understand the interactions of the built environment, population and bicycle ridership. To overcome these limitations, this study aimed to develop novel urban biking typologies using unsupervised machine learning methods. We conducted a retrospective analysis of travel surveys, bicycle infrastructure and population and land use characteristics in the Greater Melbourne region, Australia. To develop the urban biking typology, we used a k-medoids clustering method. Analyses revealed 5 clusters. We highlight areas with high bicycle network density and a high proportion of trips made by bike (Cluster 1; reflecting 12% of the population of Greater Melbourne, but 57% of all bike trips) and areas with high off-road and on-road bicycle network length, but a low proportion of trips made by bike (Cluster 4, reflecting 23% of the population of Greater Melbourne and 13% of all bike trips). Our novel approach to developing an urban biking typology enabled the exploration of the interaction of bicycle ridership, the bicycle network, population and land use characteristics. Such approaches are important in advancing our understanding of bicycling behaviour, but further research is required to understand the generalisability of these findings to other settings.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-05-19T10:46:06Z
      DOI: 10.1177/23998083221100827
       
  • The shape and size of urban blocks

    • Free pre-print version: Loading...

      Authors: Ermal Shpuza
      First page: 24
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Two measures of shape compactness and fragmentation are coupled together into a plot that is defined as a two-dimensionalmatrix for classifying boundary shapes. Block shapes in a large sample of cities result in a swallowtail distribution in the matrix, which exposes two fundamental ways of transforming the basic compact block: by dissection, corresponding to large blocks with internal dendritic streets, and by stretching and bending, corresponding to serpentine blocks in hilly terrains and edge blocks along highways, railroads, and canals. The density of cases in each matrix zone reveals the realization of actual blocks out of the probable shape combinations as a manifestation of the social logic of urban form. The observed affinity between the shape and size of non-basic blocks in cities is used to formulate a model that explains them according to the constraints of arranging plots along the streets combined with the requirements for the intelligibility of navigation and the minimization of travel distance. Considering blocks as intra-street cells, the proposed block classification reveals important links between topological and geometric aspects of the street networks thus contributing to urban modeling, morphological classification, and comparative studies.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-05-17T11:26:39Z
      DOI: 10.1177/23998083221098744
       
  • Time, the other dimension of urban form: Measuring the relationship
           between urban density and accessibility to grocery shops in the 10-minute
           city

    • Free pre-print version: Loading...

      Authors: Todor Kesarovski, Fabio Hernández-Palacio
      First page: 44
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Compact settlements take advantage of economies of scale by sustaining a system of high-quality socio-economic services at close proximities. Urban density with a balanced mix of uses also benefits walking and cycling as mobility modes that provide sufficient access to urban amenities, especially when combined with effective public transport. Indeed, walking and cycling can decrease the use of cars for short-distance trips. From this perspective, urban density can help to reduce pollution, optimise energy consumption and decrease infrastructural expenditures while contributing to more attractive urban environments. These ideas have induced a new wave of time geography planning concepts, such as the ‘10-minute city’, to enhance urban sustainability. For these concepts to move beyond visionary narratives, they must be expressed in specific empirical frameworks. Thus, the current research focuses on accessibility to grocery shops, as an essential urban service, in the Stavanger metropolitan area (Norway) using 10 minutes isochrones for walking and cycling. The study integrates open data, GIS network analyses, statistical regressions and bivariate representations of the results. The research estimates the level of serviceability by quantifying the number of shops that are accessible for each location and interrelates this estimation with spatial and population densities. The paper also presents a method to detect spatial inequalities by visualising over/under-serviced areas. This visualisation can become a tool to support strategies to rebalance such imbalances. Moreover, this study offers a practical approach towards the ‘10-minute city’ concept, as it can be adjusted to different isochrones at different spatial scales. In general, this approach can serve both to analyse existing contexts and to model strategies to support sustainability policies, such as urban densification and the promotion of environmental-friendly transport.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-05-26T05:57:19Z
      DOI: 10.1177/23998083221103259
       
  • Monitoring the well-being of vulnerable transit riders using machine
           

    • Free pre-print version: Loading...

      Authors: Martino Tran, Christina Draeger, Xuerou Wang, Abbas Nikbakht
      First page: 60
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Using open-source data, we show that despite significant reductions in global public transit during the COVID-19 pandemic, ∼20% of ridership continues during social distancing measures. Current urban transport data collection methods do not account for the distinct behavioural and psychological experiences of the population. Therefore, little is known about the travel experience of vulnerable citizens that continue to rely on public transit and their concerns over risk, safety and other stressors that could negatively affect their health and well-being. We develop a machine learning approach to augment conventional transport data collection methods by curating a population segmented Twitter dataset representing the travel experiences of ∼120,000 transit riders before and during the pandemic in Metro Vancouver, Canada. Results show a heightened increase in negative sentiments, differentiated by age, gender and ethnicity associated with public transit indicating signs of psychological stress among travellers during the first and second waves of COVID-19. Our results provide empirical evidence of existing inequalities and additional risks faced by citizens using public transit during the pandemic, and can help raise awareness of the differential risks faced by travellers. Our data collection methods can help inform more targeted social-distancing measures, public health announcements, and transit monitoring services during times of transport disruptions and closures.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-06-01T01:55:47Z
      DOI: 10.1177/23998083221104489
       
  • Re-examining Jane Jacobs’ doctrine using new urban data in Hong Kong

    • Free pre-print version: Loading...

      Authors: Jianxiang Huang, Yuming Cui, Lishuai Li, Mengdi Guo, Hung Chak Ho, Yi Lu, Chris Webster
      First page: 76
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Jane Jacobs (1961) theorized that four urban form conditions, namely, mixed use, short block, aged buildings and density, are indispensable for the ‘exuberant diversity’ and conducive to, or perhaps even determinant of, the success of a city district. Jacobs’ theory has been used widely as a reference point in case study research and policy and design prescriptions. We found five studies that attempted to test it more formally, using various performance indicators such as mobile phone activities, walking, crime and mortality. Their findings were inconsistent and unable to settle theoretical controversies. Questions remained as what performance indicators are most strongly associated with her urban form conditions' Are these conditions independently associated with desired outcomes or in combination and what are the interaction effects' Our study aimed to test Jacobs’ theory that urban form conditions contribute to the vitality and success of city districts. Jacobs’ urban form conditions were measured using GIS data for each of Hong Kong’s Tertiary Planning Unit. Performance outcomes were gauged using a combination of ‘new urban data’, comprising Twitter activities, sentiment tones and Point-Of-Interest (POI), and ‘traditional data’, comprising walking commute, employment and mortality. Urban context, income and demographic indicators were used as controls in fitting spatial regression models to predict measures of performances based on urban conditions. Results showed that Jacobs’ urban form conditions contribute positively to ‘vitality’ indicators such as the density of tweets, walking trips and POI, but not with ‘failure and success’ indicators such as expressed sentiment on Twitter, employment, or mortality. Out findings suggest that her theory largely hold for Hong Kong, except that dwelling density should be substituted by building density, whilst tall buildings associated positively with desirable outcomes, contrary to Jacobs’ observation in the American context. More generally, we demonstrate how new urban data can be used to evaluate classic planning theories at scale.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-06-04T05:50:22Z
      DOI: 10.1177/23998083221106186
       
  • Investigating rural public spaces with cultural significance using
           morphological, cognitive and behavioural data

    • Free pre-print version: Loading...

      Authors: Nan Bai, Pirouz Nourian, Ana Pereira Roders, Raoul Bunschoten, Weixin Huang, Lu Wang
      First page: 94
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      During the rural [re]vitalization process in China, national strategies required rural public spaces with cultural significance to be identified before planning decision-making. However, places identified as culturally significant by planners and visitors can differ from the ones mostly used and valued by locals. Even if there is a growing interest in integrating local perspectives and experiences in planning, studies seldom discuss and compare openly the adequacy of spatial configuration, cognition and behaviour to support it. This study took Anyi Historic Village Cluster as a case study to empirically investigate rural public spaces with three distinct, yet related approaches: (1) Morphological: spatial network centralities based on space syntax; (2) Cognitive: Lynchian village images with semi-structured interviews; (3) Behavioural: spatiotemporal occupation patterns using Wi-Fi positioning tracking. Significant places valued and used by locals and non-locals were detected with the multi-source data. Furthermore, multivariant regression models managed to characterize the relationship among different aspects of investigated rural public spaces, which also helped diagnose places of interest to prioritize in planning, demonstrating the advantage of integrating the sources of information in practice instead of studying them apart. Results can also assist rural planning on how to identify what to preserve, what to enhance, and how to develop such spaces, without overlooking the local needs or losing the rural identity.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-06-08T02:54:43Z
      DOI: 10.1177/23998083211064290
       
  • Examining the interplay between racial segregation patterns and access to
           hospital care

    • Free pre-print version: Loading...

      Authors: Gordon Cromley, Jie Lin
      First page: 117
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Access to hospitals and especially intensive care units is an important issue given the current COVID-19 pandemic. This study examined the interplay between the pattern of spatial separation of racial groups and the access by those groups to hospital services as measured by the number of beds. Differences between racial groups in the Chicago Area were investigated using two models that calculated supply and cost accessibility to hospital care using Huff-style probabilities. An additional two models focused on minimizing the unevenness in congestion for ICU beds at hospitals. Results suggest that with respect to hospital beds, there was not much difference between racial groups in terms of supply accessibility, but there were greater differences in the travel cost for accessing those services. This is due to the association between the centrality dimension of residential segregation and the central location of hospitals in the Chicago Area. Results also suggest that the goal of even congestion levels results in higher travel costs with the region.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-06-10T03:50:32Z
      DOI: 10.1177/23998083221108188
       
  • Measuring urban nighttime vitality and its relationship with urban spatial
           structure: A data-driven approach

    • Free pre-print version: Loading...

      Authors: Chao Wu, Minwei Zhao, Yu Ye
      First page: 130
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Nighttime vitality has garnered attention in recent years as an important indicator reflecting urban economy and quality of life. However, it is difficult to characterize this intangible issue. As a response, this study employed a data-driven approach to measure nighttime vitality and explored its relationships with urban spatial structure. Specifically, the data from Meituan.com—the largest Chinese shopping platform for local consumer products and retail services—were used to measure nighttime vitality based on a hierarchical weighting method. Multidimensional characteristics of the urban spatial structure were evaluated. Spatial regression models were conducted on the effect analysis of urban spatial structure on nighttime vitality. Relationship estimations were statistically significant with indicators, such as block functions, building density, interaction density, enclosure of locals, and the age structure of the main population. Our findings provide a more complete understanding of nighttime vitality, which is often overlooked in urban vitality studies. Insights derived from this study could help formulate spatial strategies to enhance nighttime vitality and quality of life.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-06-14T11:34:40Z
      DOI: 10.1177/23998083221108191
       
  • From urban form to information: Cellular configurations in different
           spatial cultures

    • Free pre-print version: Loading...

      Authors: Vinicius M Netto, Edgardo Brigatti, Caio Cacholas
      First page: 146
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Cities are different worldwide, but does this fact have any relation to culture' The idea that urban form embodies idiosyncrasies related to cultural identities captures the imagination of many in urban studies, but it is an assumption yet to be carefully examined. At its heart, the question of whether cities can be seen as cultural artefacts is informational: whether or not cultural traces can be encoded in the physical configuration of cities. Approaching spatial configuration as a proxy of urban culture, we investigate this possibility by focussing on buildings as the primary components shaping cities. Looking into how buildings aggregate in combinations and complexes, we explore Shannon’s information theory to introduce an entropy measure and analyse frequencies of cellular configurations of built form. We apply this method to downtown areas of 45 cities from different regions around the world. Assessing differences and similarities in cellular configurations, we identify clusters of cities potentially consistent with specific spatial cultures. Our findings suggest a classification scheme that sheds light on the ‘cultural hypothesis’: the possibility that different cultures and regions find different ways of ordering space. We conclude our analysis by arguing that the endless combinatorial possibilities of building configurations, missing from street network approaches, add complexity to cities and prompt a renewed interest in built form systems.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-06-14T09:54:09Z
      DOI: 10.1177/23998083221107382
       
  • Realising the Sustainable Development Goal 11.7 in the post-pandemic era
           – A case study of Taiwan

    • Free pre-print version: Loading...

      Authors: Yi-Ya Hsu, Zih-Hong Lin, Chong-En Li
      First page: 162
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The COVID-19 pandemic has dramatically impacted our daily lives worldwide. For instance, pandemic-prevention policies restrict people’s mobility, which causes problems in accessing urban greenspaces. Indeed, unequal access to urban greenspace has been accentuated during the most stringent lockdowns of 2020 and 2021. Amid such challenging circumstances, there has been a growing attention placed on Sustainable Development Goal (SDG) 11.7, which has brought opportunities for urgent action. In this paper, we applied the Gini coefficient to our analysis of unequal access to urban greenspaces across all urban planning areas in six special municipalities in Taiwan. Moreover, we also conducted comparative analyses between the Gini coefficient and other socio-economic factors. The results show that approximately 63.98% of the urban planning area suffers from unequal access to greenspaces. In addition, urban greenspace provision and household income show significant positive correlations with the Gini coefficient, which reflects Taiwan’s environmental injustice. Furthermore, these findings can help city planners and decision-makers evaluate levels of equality in each urban planning area and decide which priority areas should be improved. Finally, this study can also be used as a reference for decision-makers to realise SDG 11.7 in the post-pandemic era.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-06-15T12:06:28Z
      DOI: 10.1177/23998083221108403
       
  • Modelling the interdependence of spatial scales in urban systems

    • Free pre-print version: Loading...

      Authors: Janka Lengyel, Seraphim Alvanides, Friedrich Jan
      First page: 182
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The multitude of interwoven spatial scales and their relevance for urban systems has been of interest to the complexity science of cities since its conception. Today, we are well aware that urban environments are being simultaneously shaped and organised through actions at all levels. However, the fundamental question of how to reveal and quantify the interdependence of processes in between various spatial and temporal scales is less often addressed. Deepening our theoretical understanding of the multiscale spatiotemporal complexity of urban systems demands a transdisciplinary framework and the deployment of novel and advanced mathematical models. This article performs a multiscale analysis of urban structures using a large dataset of rent price values in the Ruhr area, Germany. We argue that, due to their many interacting degrees of freedom, urban systems exhibit similar features as other strongly correlated systems, for example, turbulent flows, notably the occurrence of extreme small-scale fluctuations. This analogy between urban and turbulent systems, which we support by empirical evidence, allows for the modelling of spatial structures on the basis of concepts and methods from turbulence theory. We demonstrate how by identifying the main turbulence-borrowed characteristics of an arbitrary two-dimensional urban field, it can be fully reproduced with a small number of prescribed points. Our findings have theoretical implications in the way we quantify and analyse scales in urban systems, model small-scale urban structures as well as potential policy relevance on understanding the evolution and spatial organisation of cities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-05-26T05:20:30Z
      DOI: 10.1177/23998083221091569
       
  • Exploring temporal variability in travel patterns on public transit using
           big smart card data

    • Free pre-print version: Loading...

      Authors: Xia Zhao, Mengying Cui, David Levinson
      First page: 198
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Passengers generate travel behaviours on public transit, whose variations deserve an exploration with an aim to guide daily-updated managements. In this study, we investigate temporal variability in travel patterns for over 3.3 million passengers across 120 days who use public transit in Beijing. Temporal variability is characterized by a series of features in terms of space coverage, travel distance and travel frequency, based on which, passengers are clustered into two types, that is, commuters with daily travel routines, and non-commuters who do not. How, and to which extent, they change travel patterns over time are examined, with using approaches concerning multivariate regression and curve fitting. Results show that, (1) commuters are more likely to travel longer but cover less territory than non-commuters on weekdays, while the opposite patterns occur on weekends. The variation of day of week affects commuters less, compared to non-commuters, due to more fixed schedules, as expected; (2) travel distance and frequency are found to increase faster, more linearly, than space-coverage features, the last of which experience a progressive decreasing of marginal increases before reaching a plateau. The above findings facilitate transport practitioners to design sound management schemes for passengers in different categories.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-05-23T01:04:59Z
      DOI: 10.1177/23998083221089662
       
  • Physical geography and traffic delays: Evidence from a major coastal city

    • Free pre-print version: Loading...

      Authors: Albert Saiz, Luyao Wang
      First page: 218
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Traffic congestion is a major environmental and social problem whose causes include urban sprawl, imbalanced home-job distributions, increased car ownership, and lack of public transportation. We focus on a relatively understudied factor: the existence of geographic barriers. We study traffic times and flows in the Boston metropolitan area, a major coastal city with substantial shape non-convexities. We show that natural barriers not only cause additional delays to the trips affected directly, but also worsen downtown congestion for everyone. Additionally, commuter flows between places separated by barriers decrease, generating additional traffic elsewhere. We also find that places next to geographic obstacles suffer from higher risks of congestion, due to their lower traffic-diffusion ability. Policymakers may consider specific solutions for congestion arising from constraining physical geographies.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-06-18T02:19:12Z
      DOI: 10.1177/23998083221108406
       
  • Modeling clusters from the ground up: A web data approach

    • Free pre-print version: Loading...

      Authors: Christoph Stich, Emmanouil Tranos, Max Nathan
      First page: 244
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This paper proposes a new methodological framework to identify economic clusters over space and time. We employ a unique open source dataset of geolocated and archived business webpages and interrogate them using Natural Language Processing to build bottom-up classifications of economic activities. We validate our method on an iconic UK tech cluster – Shoreditch, East London. We benchmark our results against existing case studies and administrative data, replicating the main features of the cluster and providing fresh insights. As well as overcoming limitations in conventional industrial classification, our method addresses some of the spatial and temporal limitations of the clustering literature.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-06-18T05:22:44Z
      DOI: 10.1177/23998083221108185
       
  • Tabulating Home Owners’ Loan Corporation area description sheet data

    • Free pre-print version: Loading...

      Authors: Scott Markley
      First page: 268
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      In the late 1930s, an agency of the United States government called the “Home Owners’ Loan Corporation” (HOLC) graded thousands of urban neighborhoods on the perceived risk they posed to property owners. To make these determinations, HOLC field agents collected vast amounts of socioeconomic, demographic, and housing data about these places and presented their findings in an impressive set of maps. While these “redlining” maps have received considerable academic and media attention, the neighborhood-level race, housing, and socioeconomic data used to assign risk grades—available for most cities in their “area description” sheets—remain virtually unusable. Correcting this issue, I convert eight of the most consequential variables from 129 cities into an accessible and analyzable tabular format. These include the Black population percentage, “foreign-born” population percentage and group, family income, occupation class, average building age, home repair status, and mortgage availability. This data product will allow researchers to gain a more complete picture of the HOLC’s City Survey program, and it will provide a valuable new source of historical socio-demographic data at the neighborhood level.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-10-14T08:19:10Z
      DOI: 10.1177/23998083221133112
       
  • Connectivity and centrality: Geovisualization of express networks in China

    • Free pre-print version: Loading...

      Authors: Wenjie Sun, Jin Zhang, Hao Shen, Guoqi Li, Hongjian Wang, Feng He, Feng Bi
      First page: 281
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Express delivery volume is an important indicator of intercity e-commerce trading activities, offering a new vision for glimpsing the intercity linkages. However, it has been a challenge to reveal the spatial distribution of intercity express flows due to the limitations on the use of express parcel data by most companies. The study maps the spatial pattern of intercity express connection intensity and identifies the urban centrality, supported by waybill data from China. Intercity express connections form a triangular corridor centred on the ‘Pearl River Delta–Yangtze River Delta–Beijing-Tianjin-Hebei’ urban agglomerations. Shenzhen, Guangzhou, Jinhua, Shanghai, Beijing, Quanzhou, Xingtai, etc., exhibit higher centrality for their strong consumption power or commodity production capacity. These cities also develop relatively strong connections with national central cities (Chengdu, Chongqing, Wuhan, Tianjin, etc.) and provincial capitals (Changsha, Urumqi, Hulun Buir, etc.). The cities on the western side of the Hu-line present low centrality and weak connections with the eastern cities and form sub-network with the provincial capital cities as the core.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2022-10-27T04:35:40Z
      DOI: 10.1177/23998083221136562
       
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 44.192.247.184
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-