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Environment and Planning B : Urban Analytics and City Science
Journal Prestige (SJR): 0.653
Citation Impact (citeScore): 2
Number of Followers: 42  
 
  Full-text available via subscription Subscription journal
ISSN (Print) 2399-8083 - ISSN (Online) 2399-8091
Published by Sage Publications Homepage  [1176 journals]
  • Exploring the relationship between daytime and nighttime mobility and park
           visitation: A case study of Austin, TX

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      Authors: Rui Zhu, Yang Song, Galen Newman
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban green space disparities persist amid rapid urbanization, widening the supply-demand gap between parks and developed area. Population density is a critical determinant in estimating park visitors, defining suitable park locations, and allocating facilities for park accessibility. Conventionally, population density data were used as a foundational basis for urban green space planning decisions, often derived from sources like the US Census Bureau, primarily reflecting “nighttime residential” distribution. However, this approach fails to capture the dynamic urban life where daily routines and mobility significantly shape park usage. This study bridges this gap by exploring the relationship between daytime and nighttime mobility patterns and their influence on park visitations across diverse park types during weekdays, using Austin, TX as study area. Methodologically, we employ a fixed effects regression analysis integrating longitudinal data from SafeGraph for park visitation and LandScan USA for daytime-to-nighttime population density ratios, within 1 km buffers around each park. Control variables encompass socio-economic factors at the block group scale, park attributes, and weather conditions. Findings suggest that neighborhood and pocket parks demonstrate positive associations with daytime population density, while district and metropolitan parks exhibit stronger ties with nighttime population density. Further, median age, unemployment rate, and higher education attainment exhibit positive correlations with park visitation, especially during daytime. Park amenities, especially playgrounds and water features, significantly contribute to increased visitation across all park types. The findings offer valuable guidance for policymakers and urban planners, informing the reimagining of park distribution strategies, optimizing facilities, and fostering inclusive park spaces accessibility.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-03-04T11:35:02Z
      DOI: 10.1177/23998083251325909
       
  • Comparative analysis of urban structures in three American Rust Belt
           cities

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      Authors: Jinmo Rhee
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This research presents a computational method to investigate the common urban structure of three Rust Belt cities—Cleveland, Detroit, and Pittsburgh—that share similar urban cultures. Understanding the urban structure of these cities is crucial for addressing their necessary restructuring and downsizing. However, there has been insufficient investigation of common spatial characteristics through comparative analysis of these cities. This research goes beyond conventional urban form analysis methods by employing a data scientific approach that segments cities into distinct parts and extracts spatial metrics from these segments. The approach involves the creation of a novel type of urban form data and utilizes deep neural networks for clustering to identify spatial characteristics common to the three cities, thereby deriving a shared urban structure. It reveals unseen insights into the restructuring of city spaces, offering a critical foundation for future urban development, and benefiting urban planners and researchers.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-03-03T04:54:23Z
      DOI: 10.1177/23998083251324982
       
  • Diving or thriving' How COVID-19 reshaped Australian short-term rental
           submarkets

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      Authors: Zhenpeng Zou, Thomas Sigler, Elin Charles-Edwards, Jonathan Corcoran
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Short-term rental markets are constantly evolving in response to dynamic market conditions. Leveraging the large-scale external market shocks resulting from the COVID-19 pandemic, this paper aims to better understand how short-term rental submarkets are formulated in response to changing market conditions. Using sequence analysis on monthly booking records between mid-2019 and the end of 2022 in Australia, this paper identifies six distinct short-term rental types underlying their varying longevities on the market. Temporal, geographic, operational and hedonic characteristics are considered to differentiate thriving from diving market trends and derive a taxonomy that narrates six submarkets. The results reveal a shifting STR market landscape from central cities and longstanding tourist destinations to peri-urban regional towns and a shift from properties run by small-scale amateur hosts toward professionally operated rentals with substantially more space and amenities. This suggests that short-term rentals have emerged as a distinct accommodation class to hotels, albeit in ways that differ based on spatial context.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-02-28T12:17:02Z
      DOI: 10.1177/23998083251324268
       
  • Enhancing digital twin technology with community-led, science-driven
           participatory modeling: A case in green infrastructure planning

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      Authors: Moira L Zellner, Dean Massey, Michelle Laboy, Daniel T O’Brien, Amy Mueller, Daniel Engelberg
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Recent research, professional, and funding agendas have re-surfaced the importance of knowledge co-production and ethical participation to address urban tensions worldwide: urbanization and rapid climate change, disproportionately impacting socially vulnerable populations. Despite the rise of Digital Twins (DT), buoyed by the growth of computational and data technologies in the past 10 to 15 years, DT have fallen short of their promise to address these tensions. We present a participatory modeling (PM) platform, Fora.ai, to build on existing strengths of DT and overcome the most prevalent limitations of data-driven technologies. This platform (i.e., a set of visualization and simulation tools and facilitation and sense-making approaches) is organized around the iterative steps in PM: problem definition and goal setting, preference elicitation, collaborative scenario-building, simulation, tradeoff deliberation, and solution-building. We demonstrate the platform’s effectiveness when set within a stakeholder-led process that integrates diverse knowledge, data sources, and values in pursuit of equitable green infrastructure (GI) planning to address flooding. The immediate visualization of simulated impacts, followed by reflection on causal and spatial relationships and tradeoffs across diverse priorities, enhanced participants’ collective understanding of how GI interacts with the built environment and physical conditions to inform their intervention scenarios. The facilitated use of Fora.ai enabled a collaborative socio-technical sense-making process, whereby participants transitioned from untested beliefs to designs that were specifically tailored to the problem in the study area and the diversity of values represented, attending to both localized flooding and neighborhood-level impacts. They also derived generalizable design principles that could be applied elsewhere. We show how the combination of specific facilitation practices and platform features leverage the power of data, computational modeling, and social complexity to contribute to collaborative learning and creative and equitable solution-building for urban sustainability and climate resilience.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-02-19T11:04:46Z
      DOI: 10.1177/23998083251323671
       
  • Cities and disasters: What can urban analytics do'

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

      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-02-18T10:37:10Z
      DOI: 10.1177/23998083251323145
       
  • Understanding pedestrian dynamics using machine learning with real-time
           urban sensors

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      Authors: Molly Asher, Yannick Oswald, Nick Malleson
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Quantifying, understanding and predicting the number of pedestrians that are likely be present in a particular place and time (‘footfall’) is critical for many academic, business and policy questions. However, limited data availability and complexities in the behaviour of the underlying pedestrian ‘system’ make it extremely difficult to accurately model footfall. This paper presents a machine learning model that is trained on a combination of hourly footfall count data from sensors across a city as well as important contextual factors that are associated with pedestrian movements such as the structure of the built environment and local weather conditions. The aims are to better understand the relationship between various contextual factors and footfall and to predict footfall volumes across a spatially heterogeneous city. The case study area is the city of Melbourne, Australia, where abundant pedestrian count data exist. Time-related variables, particularly time-of-day and day-of-week, emerged as the most significant predictors. While some built environment factors such as the presence of certain landmarks and weather conditions were influential, they were less so than temporal cycles. Interestingly the model over-estimates footfall in the years following the COVID-19 pandemic, suggesting that urban dynamics have yet to return to pre-pandemic levels (and may never do). The paper also demonstrates how the model can be used to assess the impacts that large events have had on footfall, which has implications for policy makers as they try to encourage foot traffic back into city centres.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-02-17T11:57:53Z
      DOI: 10.1177/23998083251319058
       
  • Decoding urban policies: NLP-driven concise explanations

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      Authors: Zhengyang Lu, Weifan Wang, Tianhao Guo, Yifan Li, Feng Wang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This study introduces a novel NLP-driven approach for generating accurate explanations of urban policies, addressing the critical need for communication between policymakers and the public. The proposed method integrates policy-specific fine-tuning of large language models, retrieval-augmented generation, and policy-aware prompt engineering. For the policy research, we collect the Zhihu Official Policy Q&A Dataset, a comprehensive collection of 29,151 policy-related questions and answers. Experimental results demonstrate significant improvements in explanation quality, accuracy, and relevance across various policy domains and question types. Human evaluations conducted by urban policy experts and citizens confirm the effectiveness of our method in enhancing the clarity, completeness, and usefulness of policy explanations. The potential implications for urban governance include increased policy transparency, facilitated public participation, and improved policy implementation. While acknowledging limitations such as data bias and model interpretability, this research contributes to the ongoing dialogue on smart city technologies and digital governance, highlighting the potential of NLP-driven approaches to transform urban policy communication.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-02-17T11:25:07Z
      DOI: 10.1177/23998083251321981
       
  • Erratum to “How does delivery service change food accessibility: A
           modified 2-step floating catchment area method”

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

      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-02-13T04:39:17Z
      DOI: 10.1177/23998083251319117
       
  • Digital twins versus simulation models and planning concepts: Increasing
           the resemblance between a digital twin and the modeled territory to
           facilitate the construction and evaluation of urban scenarios

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      Authors: Olivier Bonin, Pierre Frankhauser
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Digital twins are tools originally developed in the world of industry to study objects or technical systems through simulation in order to reduce the cost of experimentation. Indeed, at first sight, this approach seems promising in the field of urban planning, especially since full-scale experimentation is generally impossible. Therefore, when considering scenarios for future development, it would be interesting to explore their dynamic behaviour by confronting current results with real data. Digital twins can be used in the context of urbanism to support planners, but also for participatory planning, discussions with local politicians, etc. (Yamu, 2023). Here, we consider an approach that aims to support planners in the context of an analysis of an existing urban pattern with a view to future development. It is based on a zoning approach that links in a coherent way a wide range of scales, ranging from the metropolitan scale down to that of urban blocks, which is not currently available in existing digital twin models of cities. The simulator is primarily aimed at developers, but it can also be used in the context of resident participation. Reality is taken into account through the footprint of buildings, their height, networks, non-buildable areas and all types of amenities. It allows the design of development scenarios from the metropolitan scale down to the scale of urban blocks, the effects of which can then be simulated by the tools integrated or interfaced with a digital twin. This approach to semantising space uses spatial modelling based on a system of interlocking scales inspired by multifractal geometry. It allows us to distinguish between areas of active development and areas to be preserved. The latter are the urban spaces crossed by green corridors used for recreational activities, but also for peri-urban agriculture, for the ventilation of urbanised areas and for the maintenance of an interconnected system of natural areas to preserve biodiversity. The zoning is considered through an approach that refers to the theory of central places, which distinguishes different levels of services according to their importance and frequency for the resident population. In addition, the different zones are characterised, at different scales, by measures of accessibility to amenities as well as to different types of leisure spaces. The parameterisation is based on an exploitation of urban planning documents of master plans and allows the calculation of the satisfaction level of the inhabitants according to the importance of the amenities. This satisfaction is calculated for each zone and aggregated into a general satisfaction level. Moreover, it is possible to distribute housing according to the same logic of interlocking scales, promoting a diversity of densities at all scales, while respecting the penetration of green and blue networks in the urban blocks. Hence, the model allows on the one hand to reproduce the spatial organisation of an existing city while considering the needs of residents. For this reason, it can be considered as a digital twin of the city. The approach is structural and in this sense static, as the goal is not considering, for example, daily mobilities or the impact of climate. But the concept allows evaluating the positive or negative impact of new urbanistic projects as the development of new residential areas by adding dwellings or by adding diverse types of amenities. Shrinking cities can be considered, as well. Thus, potential future development can be evaluated in the spirit of long-term dynamics. The algorithmic formalisation is rather transparent, thus avoiding a ‘'black box’ effect.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-02-10T04:15:01Z
      DOI: 10.1177/23998083251318474
       
  • Do urban digital twins need agents'

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      Authors: Letícia Marçal Russo, Gamze Dane, Marco Helbich, Arend Ligtenberg, Gabriele Filomena, Christian P Janssen, Mila Koeva, Pirouz Nourian, Agnès Patuano, Paulo Raposo, Kristina Thompson, Senqi Yang, Judith A Verstegen
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The urban digital twin (UDT) is derived from the original digital-twin concept of a representation of physical assets. This has left the social component of the city underrepresented in UDTs. Here, we discuss what this means for the current maturity stage of UDTs and why better representing human behaviour in UDTs may diversify possibilities to support different types of planning. We contemplate operationalizing the representation of human behaviour by means of agent-based models (ABMs) integrated with UDTs and illustrate this with two concrete examples of simulating stress and safety perception in public spaces. One example shows the idea of the UDT as a live data repository for ABMs, with the ABM adding dynamism, and the other of live feedback between the city, the ABM and UDT. We discuss several epistemological, conceptual, technical, and ethical challenges that may be involved in this integration. We conclude with a future agenda to promote (1) the abandonment of the vision of a UDT as the highly detailed mirror of the city, (2) UDTs fit for sectoral (strategic) in addition to operational planning, (3) the inclusion of behavioural and social processes in UDTs by incorporating ABMs, (4) a culture of cumulative research using structured guided frameworks and reusable building blocks, (5) ABMs with explicit purposes to allow fit-for-purpose selection in UDTs, and (6) explicitly addressing epistemic, normative, and moral responsibilities. Thus, though including agents may at some point be a solution for the (currently lacking) perspective on the role of humans in shaping and being shaped by the city, several reconsiderations in the UDT and ABM communities need to take place first.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-02-07T01:45:44Z
      DOI: 10.1177/23998083251317666
       
  • Urban revitalization pathways toward zero carbon emissions through systems
           architecting of urban digital twins

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      Authors: Ishwar D Ramnarine, Tarek A Sherif, Abdulrahman H Alorabi, Haya Helmy, Takahiro Yoshida, Akito Murayama, Perry P-J Yang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Recognizing the critical role of cities in mitigating greenhouse gas emissions, many cities are adopting carbon neutrality goals as part of their climate action strategies. The efficacy of these initiatives, however, has been undermined by complexity of systemic problems, ineffectiveness in planning implementation, and lack of stakeholder engagement. Urban and community-level carbon reduction should transcend urban design and systems optimization to incorporate multi-faceted dimensions in urban contexts. To address these challenges, this paper proposes a framework of urban digital twins that includes digital representation, performance modeling, design interventions and interactive platform for decisions over temporal processes. The CANVAS, or Carbon Neutrality Architecting New Visions for Architectural Systems, is a systems architecting approach to modeling the process of urban revitalization for achieving carbon neutrality by 2050. The developed workflow integrates multidisciplinary approaches for carbon mapping, gap identification, alternative generation, Urban Building Energy Modeling (UBEM) simulation, evaluation, and decision-making to demonstrates applicability of the proposed framework through a case study of the Nihonbashi district in Tokyo. The approach revealed that Energy Use Intensity (EUI) can be decreased by 99 kWh/m2/y through reconstruction and operational improvements. Emerging photovoltaic technologies can further cut EUI by an average of 42.5 kWh/m2/y, although results vary significantly in respect to building characteristics, particularly geometry and floor area. The incremental, cyclical systems architecting approach revealed that a 97% reduction in carbon emissions could be achieved by the seventh cycle through stakeholder-centric system interventions. This paper contributes to the development of urban digital twin methodologies by integrating systems architecting concepts with UBEM as transformative tools for carbon neutral urban design and development.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-02-05T07:24:39Z
      DOI: 10.1177/23998083251318142
       
  • A multi-scale network-based topological analysis of urban road networks in
           highly populated cities

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      Authors: Assemgul Kozhabek, Wei Koong Chai
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      In this paper, we study urban road infrastructure in densely populated cities. As the subject of our study, we choose road networks from 35 populous cities worldwide, including China, India, Pakistan, Colombia, Brazil, Bangladesh, and Cote d’Ivoire. We abstract road networks as complex systems, represented by graphs consisting of nodes and links, and employ tools from network science to study their topological properties. Our multi-scale analysis includes macro-, meso-, and micro-scale perspectives, deriving insights into both common and unexpected patterns in these networks. At the macro-scale, we examine the global properties of these networks, summarizing the results in radar diagrams. This analysis reveals significant correlations among key metrics, indicating that more robust networks tend to be more efficient, while diameter and average path length show negative correlations with other properties. At the meso-scale, we explore the existence of sub-structures embedded within the road networks using two main concepts, namely, community and core-periphery structures. We find that while these densely populated city road networks show particularly strong community structures (high modularity values, close to 1.0) that are not typical to other networks, they exhibit a low level of presence of core-periphery structures, with an average coreness of 6.3%. This points to the cities being polycentric. At the micro-scale, we find nodal-level properties of the network. Specifically, we compute the various centrality measures and examine their distributions to capture the prevalent characteristics of these networks. We observe that the centrality measures present different distribution patterns. While the degree distribution demonstrates a limited range of degree values, the betweenness centrality distribution follows a power law, and the closeness centrality exhibits a binomial distribution—yet these patterns remain consistent across the studied cities. Overall, our multi-scale analysis provides valuable insights into the topological properties of urban road networks, informing city planning, traffic management, and infrastructure development in similar urban environments.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-02-05T02:35:00Z
      DOI: 10.1177/23998083251318067
       
  • Construction enthusiasts versus demolition giants: Insights from building
           footprint data in England

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      Authors: Xinyi Yuan, Ziqi Li, Ana Basiri, Mingshu Wang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This study uses building footprint data from the Ordnance Survey MasterMap to analyze construction and demolition activities across England from 2017 to 2023. By comparing the Topographic Object Identifiers (TOIDs) of each building between years, we identified newly constructed and demolished buildings, quantified changes, and used the bivariate color maps to visualize spatial patterns across England and within its five major cities. The study highlights the effectiveness of building footprint data in providing insights into urban changes and development trajectories, which are vital for urban planners and policymakers to understand dynamic urban processes and inform decision-making toward sustainable urban development.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-31T12:07:00Z
      DOI: 10.1177/23998083251317573
       
  • Barrios 4D: Semi-automated morphology analysis of human settlements using
           mobile laser scanning

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      Authors: Jason Alejandro Castaño-López, Juan C Perafán-Villota, Nicolas Llanos-Neuta, Simone Mora, Victor Romero-Cano
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Civil or government organizations base human settlement transformation decisions on limited and sparse data. However, broader and denser information is necessary. Camera and LiDAR data processing is a more effective, automatic, and affordable method to fully characterize the morphological structure of human settlements. This work presents a system for estimating metrics about relevant morphological characteristics of human settlements using LiDAR data. We provide a quantitative analysis of these metrics obtained in the city of Cali, Colombia. Additionally, we enable the automatic calculation of urban metrics such as the street canyon ratio, which relates building height to street width, a metric highly correlated with air quality. Moreover, we extrapolate findings from existing literature to compare our results and understand how indirectly measured variables, such as thermal sensation and perceived beauty of the environment, might behave Our system can potentially be used by civil and government organizations to develop informed and precise urban planning and transformation strategies, including land use zoning, infrastructure development, and addressing issues related to housing, transportation, and environmental sustainability.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-28T11:45:53Z
      DOI: 10.1177/23998083251315966
       
  • Generating conceptual landscape design via text-to-image generative AI
           model

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      Authors: Xinyue Ye, Tianchen Huang, Yang Song, Xin Li, Galen Newman, Dayong Jason Wu, Yijun Zeng
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This study explores the integration of text-to-image generative AI, particularly Stable Diffusion, in conjunction with ControlNet and LoRA models in conceptual landscape design. Traditional methods in landscape design are often time-consuming and limited by the designer’s individual creativity, also often lacking efficiency in the exploration of diverse design solutions. By leveraging AI tools, we demonstrate a workflow that efficiently generates detailed and visually coherent landscape designs, including natural parks, city plazas, and courtyard gardens. Through both qualitative and quantitative evaluations, our results indicate that fine-tuned models produce superior designs compared to non-fine-tuned models, maintaining spatial consistency, control over scale, and relevant landscape elements. This research advances the efficiency of conceptual design processes and underscores the potential of AI in enhancing creativity and innovation in landscape architecture.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-27T11:43:56Z
      DOI: 10.1177/23998083251316064
       
  • (Ac)counting for night shift workers: Insights from Australian cities.

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      Authors: Michele Acuto, Anna Edwards, Jesse Mentha, Alison Young
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Recognition for the importance of the night-time economy (NTE) in cities is mounting in both academia and policy. Yet, much of this discourse is centred on the consumption side of the NTE. Analytical and policy insights into the role of those who work to keep our cities ticking 24/7 and the NTE flourishing is still severely limited. Just how many people work at night' And how can we count them' Current assessments, where at all present, often diverge drastically, whilst cities and countries step up more and more policy efforts to grow the NTE. We present here a case study, centred on the task of assessing the Australian night-time economy’s workforce, to underscore continuing challenges in accounting for night shift workers. We underline how counting night shift workers provides for a more effective evidence base for urban policy. We demonstrate both definitional difficulties and data limitations, arguing for the pressing need for more precise urban science of the night, and of the NTE specifically, as a precondition to stepping up our engagement with night shift workers, in order to account for them in policymaking.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-18T02:48:59Z
      DOI: 10.1177/23998083251315796
       
  • Using a machine learning framework for natural language processing to
           create a high-resolution carbon emission map for urban manufacturing

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      Authors: Tinyu Wang, Fengying Yan, Jian Ma, Xiaoping Zhang, Liang Dong
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Managing carbon emissions from the manufacturing sector is crucial for sustainable development, and effective identification of manufacturing land is key to achieving this goal. However, current methods for identifying urban manufacturing land remain inadequate. In this study, we employ a fine-tuned, pre-trained natural language processing model based on Bidirectional Encoder Representations from Transformers to classify points of interest data into manufacturing industry categories. This approach enables us to identify manufacturing land and allocate corresponding carbon emissions data to specific parcels. The global Moran’s Index and local Moran’s Index are applied to analyze the relationship between manufacturing concentration and carbon emission intensity. The results demonstrate that the fine-tuned model achieved an accuracy rate of 91.6% on the test set, successfully identifying 98.72% of the manufacturing land in the study area. The intensity of carbon emissions from manufacturing exhibits a significant positive spatial correlation, with urban areas characterized by high-high and low-low clustering of emissions. In rural areas, high-emission manufacturers tend to be co-located with low-emission enterprises. Within individual manufacturing sectors, most exhibit low-low clustering, suggesting a potential relationship between such clustering and lower carbon emissions. This study provides detailed spatial data for the management of carbon emissions in the manufacturing sector and addresses the gap in micro-scale research on the correlation between manufacturing concentration and carbon emissions.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-13T09:26:46Z
      DOI: 10.1177/23998083241312948
       
  • Exploring the associations between street-view green space quantity and
           quality, and influenza in Guangzhou, China through machine learning and
           spatial regression: A socio-economic equity perspective

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      Authors: Ruoyu Wang, Ming-Kun Sun, Shengao Yi, George Grekousis, Guang-Hui Dong
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Existing studies have highlighted that green space is associated with non-communicable diseases. However, scant attention has been paid to the association between green space quantity and quality with communicable diseases. Here, we explore the relationships between green space and influenza cases in Guangzhou, China, using street-view green (SVG) space quantity and SVG-quality indicators, which offer a better assessment of urban green space than traditional remote sensing metrics. Influenza cases were collected from hospitalization records, while street-level green space was measured by street-view data and deep neural networks. The neighbourhood deprivation index (NDI) was also used as a proxy for neighbourhood-level socio-economic status. We employed the Random Effects-Eigenvector Spatial Filtering (RE-ESF) regression model because of its usefulness in handling spatial dependence. Findings showed that higher levels of SVG-quantity and quality are associated with a lower number of influenza cases, implying a negative relationship. Specifically, the marginal effects for SVG indicate that influenza may decrease by 145 cases for every unit increase in SVG-quantity, and by 11 cases for every unit increase in SVG-quality. In terms of planning, this could mean that though green quality is essential for the aesthetic part of urban life, quantity is much more critical concerning the containment of influenza. In addition, SVG-quantity and quality moderated the positive association between NDI and influenza cases. In other words, people in more deprived neighbourhoods were more influenced by SVG-quantity and quality compared to people living in less deprived areas. This means that more green space should be added to such neighbourhoods. We also observed that the association between SVG-quality and influenza cases was weaker for females, people aged between 18 and 45, and employed people. Because influenza is the most common pandemic worldwide, green space at the street level should be considered when promoting equitable public health and this study provides quantifiable evidence for the negative effect of green space quantity and quality over influenza cases.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-13T07:09:26Z
      DOI: 10.1177/23998083241312272
       
  • Assessing the impact of greenery on urban heat using opportunistic
           drive-by sensing

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      Authors: Elina Merdymshaeva, Simone Mora, Yuki Machida, Fan Zhang, Fábio Duarte, Sanjana Paul, Carlo Ratti, Ulla Mörtberg
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The urban heat island (UHI) phenomenon is recognized as a main urban sustainability problem in the face of a changing climate, affecting human health, energy consumption, and other socio-economic considerations. The UHI can be mitigated by urban greenery, but it needs further investigation of detailed impacts across the urban landscape. The aim was to study UHI and model the relation to greenery in combination with urban grey structures, at a high spatiotemporal resolution across the urban landscape, in Stockholm. Temperature data was collected through opportunistic drive-by sensors on electric three-wheeled taxis. Data on greenview and skyview factors were used to inform on greenery and building density along the roads. During night and morning hours, the surface temperature was in general higher than air temperature, indicating that some densely built-up environments stored heat overnight. Hot zones were unevenly distributed throughout the city, while greenery had a cooling effect, especially when combined with skyview as an inverse measure of building density. Our results provide information on the spatiotemporal distribution of heat that can be used to inform efforts to use greenery for mitigating impacts of UHI on urban residents.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-13T06:12:23Z
      DOI: 10.1177/23998083241311068
       
  • A high-resolution global time series of street-network sprawl

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      Authors: Christopher Barrington-Leigh, Adam Millard-Ball
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Systems of street networks form a backbone for many aspects of human life and, once laid down, urban streets represent a nearly immutable influence on future urban form and concomitant travel, energy, and social outcomes. Moreover, as humanity is currently passing through its peak urbanization rate, decisions about how to design such networks at the local scale are being made faster than ever before. In this work, we quantify local street connectivity and provide a global, high-resolution time series of our Street Network Disconnectedness Index (SNDi) as an open data set. We derive a stylized version of the actual geographic road network from the 2023 vintage of OpenStreetMap by simplifying complex intersections, divided roads, and offset intersections. Using this functional representation of the network corrects systematic biases in derived properties of the network. We couple this simplified network with a newly available time series of urbanization in order to compute SNDi and provide a dynamic analysis to the year 2019 and a cross-sectional analysis for 2023. We release our data as the raw network of edges and nodes and as aggregates to a 1 km grid, to countries, and to five subnational administrative levels. We also provide interactive visualizations at sprawlmap.org. Overall, our findings present a picture of rapidly worsening street-network connectivity in many regions of the world.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-13T04:15:00Z
      DOI: 10.1177/23998083241306829
       
  • How does delivery service change food accessibility: A modified 2-step
           floating catchment area method

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      Authors: Grace Jia, Cynthia Chen, Ram Pendyala
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Existing methodology on food accessibility predominately focuses on on-premise services, that is, dine-in and shopping at stores, which assumes a linear distance decay property (the closer, the higher accessibility). Access to delivery services is fundamentally different from that to on-premise stores. Stores with close proximity (within an inner boundary) are less desirable for delivery due to delivery fees, and there is an outer boundary beyond which deliveries are unavailable, both challenging the assumption of increasing impediment with distance. These two boundaries form a donut shape for delivery services. We propose a modified 2-step floating catchment area method that incorporates the donut shape, accounts for both demand and supply, and examines the diversity of food options. Using Seattle as a case study, our results show that delivery services increase restaurant and fast-food accessibility in areas where there is already good accessibility (e.g., downtown Seattle for restaurants and South Seattle for fast-food). Given South Seattle is where low-income and low-access households concentrate, the increase in accessibility to fast-food may not be desired. Interestingly, with delivery services, more low-income or low-access households (those who live far from grocery stores) have better accessibility to fresh produce from grocery stores compared to the rest of the population. And the newly created Supplemental Nutrition Assistance Program (SNAP) online program appears to miss low-access households. These findings have important implications for policymakers and stakeholders seeking to improve food accessibility in urban areas through delivery services.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-06T05:54:22Z
      DOI: 10.1177/23998083241312369
       
  • Quantifying the benefits of urban amenities in Singapore with
           consideration of the effects of spatial heterogeneity

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      Authors: Jie Song, Jeremy Oon, Rakhi Manohar Mepparambath, Diem Trinh Thi Le, Hoai Nguyen Huynh
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Studying urban amenities is crucial for understanding their impact on quality of life, social equity, and sustainable city development. However, the valuation of urban amenities on a holistic level is understudied. This paper builds upon the framework of isobenefit lines, where residents supposedly receive the same level of combined benefits from all urban amenities. Specifically, our proposed approach takes into account the spatial heterogeneity of amenities and the proxy data of property transaction prices in Singapore to estimate their underlying monetary values. These monetary values were quantified using geographically weighted regression (GWR) that can adequately address spatial autocorrelation issues. Our results show that GWR outperforms the global linear regression model by approximately 150% increase in the R-square value, demonstrating a much better goodness of fit when dealing with spatial data sets. Additionally, the signs of the average coefficients of GWR are largely consistent with those of the global model, while the signs and magnitude of the GWR coefficients vary spatially. The spatial variations of modeling performance tend to intensify from older to younger towns. The results reveal that the central regions of Singapore are among the top spots that receive the highest levels of composite benefits. It is also observed that a spatial structure with multiple centers with high benefit scores emerges in the younger towns located in the peripheral rings of the city. This observation demonstrates the efforts of local authorities to promote a city with several regional centers of diverse functions. As the first study that applies the concept of isobenefit lines in a real urban setting, we demonstrate that the developed framework can be a useful addition to the existing toolbox of urban and infrastructure planners.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-04T10:14:48Z
      DOI: 10.1177/23998083241312953
       
  • CITYLID: A large-scale categorized aerial lidar dataset for street-level
           research

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      Authors: Deepank Verma, Olaf Mumm, Vanessa Miriam Carlow
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban point cloud datasets are crucial for understanding the depth and physical structure of environmental features. These details hold significance in urban planning, providing precise measurements of the space upon which novel development plans and strategies can be formulated. However, such datasets, when uncategorized, lack information, rendering them much less helpful in utilizing them in urban planning and design projects. This documentation provides a methodical framework to create the CITYLID dataset, which uses an openly available citywide aerial Lidar dataset, categorizes it with standard urban classes such as buildings, trees, and ground, and fuses with it detailed street features information such as driveways, medians, bikepaths, walkways, and on-street parking. Since the point cloud provides the required height information, shadow maps are also generated utilizing the entire point cloud dataset and further integrated with the point clouds. The resulting dataset includes 3 standard and 5 street feature classes, along with 5 classes representing shadows. Apart from the categorized point cloud dataset, we additionally provide the detailed methodology to generate Lidar categorization and starter codes to extract subsets of point clouds, which can be used to analyze and study urban environments such as street cross-sections, neighborhood comparisons, tree inventory, etc.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-04T02:11:33Z
      DOI: 10.1177/23998083241312273
       
  • Exploring the relationship between income inequality and crime in Toronto
           using frequentist and Bayesian models: Examining different crime types and
           spatial scales

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      Authors: Renan Cai, Su-Yin Tan
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Income inequality, which refers to the uneven distribution of income in a population, has been linked to many societal problems, including crime. Although environmental criminology theories, such as rational choice theory, suggest a positive association between income inequality and crime, previous empirical studies have reported divergent results based on different crime types, statistical models, and spatial units of analysis. This study employs non-spatial and spatial regression models using frequentist and Bayesian modelling frameworks to explore the impacts of within-area and across-area income inequality on five types of major crimes in the City of Toronto at the census tract and dissemination area scales. The use of spatial regression models improves the model fit in both frequentist and Bayesian frameworks. The Bayesian shared component model, which accounts for the interactions between different types of crimes, further enhances model performance. Results obtained from the best-fitting frequentist and Bayesian models are inconsistent but do not conflict in terms of the relationship between crime and income inequality, where within-area income inequality generally increases major crime rates, while across-area income inequality has varying effects dependent on crime type and spatial scale. The discrepancies between spatial scales are a manifestation of the modifiable areal unit problem (MAUP).
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-03T10:07:03Z
      DOI: 10.1177/23998083241311969
       
  • Studying tech adoption with “text-as-data”: Opportunities, pitfalls,
           and complementarities in the case of transportation

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      Authors: Shih-Hung Chiu, Tianyu Han, Alison E Post, Ishana Ratan, Kenichi Soga
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The rapid digitization and publication of local government records presents researchers with an unprecedented chance to study governance processes. In tandem, advances in computer science and statistics—alongside significant increases in computational power—have led to the development of “text-as-data” methods and their application to social science and policy research. This paper evaluates the potential utility of digitized public meeting minutes and video recordings for studying decision-making about technology adoption by local public agencies, using survey data on the same topic as a benchmark. Focusing on transit agencies in California, we evaluate surveys and digitized meeting records with respect to overall data availability, bias in data availability, and the types of information about technology adoption contained. We find that meeting minutes and video recordings are available for more than twice as many agencies than for a state transit agency-sponsored survey, and that the availability of digitized records is not skewed toward larger agencies, as is the case for survey data. Meanwhile, we find important complementarities with respect to the type of information available about technology adoption in these three data sources.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2025-01-03T09:50:09Z
      DOI: 10.1177/23998083241311039
       
  • Four decades of population expansion and shrinkage across Chinese cities

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      Authors: Yonghua Zou, Xingyu Zhu, Chengyan Pu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Based on the latest three Chinese censuses and the population prediction model, we use four cartograms to reveal the population expansion and shrinkage across the prefecture-level cities in mainland China from 2000 to 2040. The cartograms demonstrate a difference in the spatial distribution of cities that expand and shrink in four decades. Especially, the cartograms reveal that the proportions of cities with shrinking populations in these four decades are 29%, 44%, 77%, and 88%, respectively, suggesting that Chinese policymakers need to adjust the former urban development strategies that prioritize population expansion.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-12-24T02:24:01Z
      DOI: 10.1177/23998083241309154
       
  • Clustering moves: Spatial network analysis in residential mobility

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      Authors: Susannah Cramer-Greenbaum
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      In the past sixty years, network analysis has become a valuable analytic tool in the study of interpersonal relationships and also in the construction of spatial relationships within urban geographies. Researchers have applied network analysis in a wide array of spatial applications; however, the power of network analysis has yet to be applied to understanding patterns in residential mobility. Residential movement patterns take place over longer time scales and potentially greater distances than daily journeys or commutes, but equally create networks connecting places and people. This research demonstrates how applying network analysis to residential moves may lend insight to open questions in the study of residential mobility, using fine-grained data on residential moves held by the city of Zurich, Switzerland. By creating a weighted directed network linking locations on a 400 meter coordinate grid with residents moving between them, the work demonstrates that network analysis can reveal geographies that overwrite the political boundaries commonly used to categorize residential spaces in the city. The new geographies produced by this method capture a wholistic picture of moving behaviour independent of reported residential choices. By tracking completed moves rather than stated aims, the uncovered mobility geographies sidestep the common categorisation of voluntary versus structurally determined residential choices, aggregating accumulated choices to demonstrate some of the geographic specificities of residential moving behaviour.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-12-19T08:57:39Z
      DOI: 10.1177/23998083241309992
       
  • Assessing the suitability of settlement delineations for monitoring
           infilling: A web- and GIS-based expert evaluation approach

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      Authors: Sebastian Eichhorn, Oliver Harig, Stefan Siedentop, Robert Hecht
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      21st century urbanisation features not only the growth of city populations but also the emergence of densification (infilling) as significant trends in urban development. While urban sprawl has long been acknowledged for its adverse effects, understanding densification remains challenging due to inadequate empirical and statistical frameworks. This study investigates the suitability of different geospatial datasets and methods for delineating settlement areas and assessing infill housing, an aspect crucial for urban planning and development. Quantitative and qualitative analyses reveal notable variations in the classification of settlement areas and infilling across datasets. Quantitatively, the study shows distinct differences in the delineation of settlement areas, with the share of infilling varying significantly. Qualitatively, expert assessments highlight the strengths and weaknesses of datasets regarding their accuracy and consistency, revealing that the method to delineate settlement areas significantly impacts the balance between infilling and greenfield development. The study underscores the need for a nuanced approach to conceptualising densification measurement, particularly in defining urban boundaries.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-12-18T04:55:50Z
      DOI: 10.1177/23998083241308407
       
  • Residential concentration of the new elite class between 2010 and 2020 in
           South Korea

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      Authors: Jihan Park, Donghyun Kim
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Recently, a new elite class, often called the upper-middle class, has emerged as a distinct social group. This study aims to identify the spatial distribution of this new elite class in South Korea in the years 2010 and 2020. Using data from the Korean Labor and Income Panel Study, we defined new elites as those in 3-digit managerial and professional occupations with high wages (top 50%) and low property levels (bottom 50%). We utilized the Population and Housing Census to identify the spatial distribution of elite roles at the district level and visualized them using cartograms. We identified consistent elite concentrations in Seoul and southern Gyeonggi, but their presence was restricted to specific districts by 2020. Sejong emerged as an administrative hub attracting new elites. Moreover, Busan and Ulsan experienced increasing elite populations, whereas Gwangju and Daegu witnessed a decline. These findings highlight the growing spatial polarization of the new elite class. Our study provides a basis for policies aimed at improving educational opportunities and promoting social mobility.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-12-17T07:47:22Z
      DOI: 10.1177/23998083241308653
       
  • Beyond green: Unveiling the impact of urban park quality and greenery on
           children’s physical activity

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      Authors: Ming Gao, Xinting Cheng, Yu Bao, Xudan Zhou
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban green spaces facilitate children’s physical activities by providing opportunities for engagement with natural settings. However, there is a lack of empirical research examining the nexus between the greenery features and spatial quality in urban parks and park-based physical activities among children. Moreover, the influence of children’s perceptions of their environment has been overlooked. Through the application of remote sensing and field surveys, we evaluated the greening and quality of 34 play spaces within 20 urban parks, employing on-site measurements and unmanned aerial vehicle observations to identify and quantify the intensity and density of children’s physical activities. Utilizing Hierarchical Linear Modeling and Simple Mediating Modeling, we investigated the mediating effects of green spaces on physical activity and perceived environmental qualities. Our findings indicate a curvilinear (inverted U-shaped) relationship between urban park greening metrics, such as vegetation diversity and green view index, and the dosage of children’s physical activity. The interplay between the quality of space and greening level in shaping physical activity demonstrates complex dynamics of synergy and competition. The greening level of play spaces positively impacts the intensity and density of children’s physical activities and is partly moderated by perceived environmental factors, notably safety and attractiveness. These insights contribute empirical evidence and decision-making guidance for urban greening and the development of child-friendly urban spaces.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-12-16T11:51:11Z
      DOI: 10.1177/23998083241304258
       
  • Urban scaling theory: Answers to frequent questions

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      Authors: José Lobo, Luís Bettencourt, Scott G Ortman
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Since its start about 15 years ago, urban scaling research has become a vibrant component of the emerging field of urban science. Initially, this work focused on the identification of nonlinear relationships in urban quantities relative to population size, but more recently it has expanded to include efforts to explain observed scaling relationships in terms of new theory. We find that some misunderstandings have arisen in the literature concerning the nature and purpose of this work. Here, we address several persistent questions that have been raised with respect to urban scaling theory, clarify what we perceive to be its achievements and distinctiveness, and highlight questions and areas of opportunity for future work.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-12-11T11:58:18Z
      DOI: 10.1177/23998083241308418
       
  • Selecting building height control indicators of landmark skylines: A
           visual perception experiment

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      Authors: Gao Yuan, Wei Yuyao, Yu Miao
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The landmark skyline contains a modern high-rise landmark taller than neighboring buildings. Landmark prominence and overall volatility are two essential environmental features connecting to skyline building height control, described in previous research by several indicators. A visual perception experiment is conducted in this study to assess these indicators. The experiment involves a correlation analysis between physical attributes calculated from sample images and relevant perceptions acquired by semantic differential questionnaires. The results reveal that A2 (landmark primacy by second tallest height) and A4 (landmark primacy by average height) are suitable indicators for describing the perception of landmark prominence, and B4 (average adjacent height difference) is a better indicator for the perception of overall volatility. Concerning relations, high landmark prominence and high overall volatility perceptions are incompatible. High overall volatility may suppress the perception of high landmark prominence. In addition, increasing the height of the landmark can effectively improve landmark prominence perception, while improving overall volatility perception requires regulating the heights of more buildings and conducting more precise height controls.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-12-10T05:48:03Z
      DOI: 10.1177/23998083241304250
       
  • Participation matters: The social construction of digital twins for cities

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      Authors: Timea Nochta, Kwadwo Oti-Sarpong
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      In this commentary, we trace processes of ‘social construction’ in the design and implementation of digital twins for cities. We discuss how the layering of a Social Construction of Technology (SCOT) lens on top of already existing perspectives in smart cities and urban planning can help to develop a more nuanced account of participation, inclusion and exclusion. The aim being to facilitate critical reflection on the development trajectory of the UDT concept and highlight that much of what is often described as the natural, inevitable advancement of the technology in fact serves particular interests, with privileged access. We also emphasise that alternative interpretations exist, and should be sought out by technology developers, to facilitate progress in UDT design and implementation.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-12-09T05:18:07Z
      DOI: 10.1177/23998083241305695
       
  • Redefining urban digital twins for the federated data spaces ecosystem: A
           perspective

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      Authors: Jorge Gil, Dessislava Petrova-Antonova, Graham JL Kemp
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban Digital Twins (UDTs) promise to facilitate the transition to a smarter planning and decision-making process, but they face many challenges to meet stakeholders’ expectations and to support delivering a better living environment for citizens. Their full potential can only be reached through more flexible sharing and integration of data and data models. From this perspective, we argue that UDTs can be realised in an ecosystem of data spaces that support a federated data architecture. We present the conceptual architecture for UDTs in a federated data spaces ecosystem, describe the different components and layers, and reflect on the UDT mediator role in relation to other actors in the ecosystem. We aim to contribute to the field of UDTs by showing the way forward for their development, connected to the concepts of data spaces and federated database systems, and to the field of data spaces by introducing UDTs as a new component playing a mediator role.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-12-04T10:00:35Z
      DOI: 10.1177/23998083241302578
       
  • Three-dimensional embodied visibility graph analysis: Investigating and
           analyzing values along an outdoor path

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      Authors: Sara Omrani Azizabad, Mohammadjavad Mahdavinejad, Mahyar Hadighi
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      In visibility analysis, a major focus is the relationship between people and the environment, and one of the most important spatial concepts is Isovist. Although typically represented in two dimensions in architecture, this concept has recently been computed in a three-dimensional environment. However, embodied 3D isovist Theory as developed to date does not account for locomotion. In this paper, therefore, we combine that theory with 3D visibility graph theory to develop and propose the Three-Dimensional Embodied Visibility Graph (3D E-VGA). To present and evaluate the proposed model in an architectural environment, we analyze the three-dimensional scene of a pedestrian moving along a path in an outdoor environment, specifically that of a container housing design project in Cairo known as “Sheltainer.” Further, we investigate the relationships between the t-d ratio, the v-h ratio, vertical jaggedness, connectivity, and integration values and conclude that of these the last three-vertical jaggedness, connectivity, and integration- are significantly correlated with each other. However, the relationship between v-h, t-d, and connectivity and integration values has not been determined. Therefore, analyzing both values related to embodied 3D isovist and 3D visibility graph provides us with a more comprehensive and effective analysis of pedestrians’ visual perceptions along a path.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-12-04T09:14:51Z
      DOI: 10.1177/23998083241303199
       
  • Global Healthy and Sustainable City Indicators: Collaborative development
           of an open science toolkit for calculating and reporting on urban
           indicators internationally

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      Authors: Carl Higgs, Melanie Lowe, Billie Giles-Corti, Geoff Boeing, Xavier Delclòs-Alió, Anna Puig-Ribera, Deepti Adlakha, Shiqin Liu, Júlio Celso Borello Vargas, Marianela Castillo-Riquelme, Afshin Jafari, Javier Molina-García, Vuokko Heikinheimo, Ana Queralt, Ester Cerin, Eugen Resendiz, Dhirendra Singh, Sebastian Rodriguez, Esra Suel, Marc Domínguez-Mallafré, Yang Ye, Amanda Alderton
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Measuring and monitoring progress towards achieving healthy, equitable and sustainable cities is a priority for planners, policymakers and researchers in diverse contexts globally. Yet data collection, analysis, visualisation and reporting on policy and spatial indicators involve specialised knowledge, skills, and collaboration across disciplines. Integrated open-source tools for calculating and communicating urban indicators for diverse urban contexts are needed, which provide the multiple streams of evidence required to influence policy agendas and enable local changes towards healthier and more sustainable cities. This paper reports on the development of open-source software for planning, analysis and generation of data, maps and reports on policy and spatial indicators of urban design and transport features for healthy and sustainable cities. We engaged a collaborative network of researchers and practitioners from diverse geographic contexts through an online survey and workshops, to understand and progressively meet their requirements for policy and spatial indicators. We outline our framework for action research-informed open-source software development and discuss benefits and challenges of this approach. The resulting Global Healthy and Sustainable City Indicators software is designed to meet the needs of researchers, planners, policy makers and community advocates in diverse settings for planning, calculating and disseminating policy and spatial urban indicators.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-12-03T06:58:21Z
      DOI: 10.1177/23998083241292102
       
  • The importance of the social environment on leisure destination choice: A
           mixed multinomial analysis of homophilic preferences

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      Authors: Benjamin Gramsch-Calvo, Kay W Axhausen
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Individuals are fond of belonging to a social environment with a similar social background, which can impact the individual’s decision to visit specific venues for leisure activities. Using data from Zurich, we have measured the preference for a social environment in four categories of leisure venues: restaurants, cafes, bars, and nightclubs; the estimation was performed using a mixed multinomial logit model to see how homophily for socioeconomic characteristics can impact the decisions of choosing a leisure venue. The models included three homophilic preferences: age, income, and cultural origin as variables of interest. The results show a positive impact of the three variables in different degrees: age is the most relevant in the two venue categories, income only impacts when individuals choose restaurants or cafes, and cultural background is more relevant for nightlife venues. These results show that the sociodemographic characteristics of the social environment are relevant for the choice of leisure destinations. These findings can contribute to the formulation of policies to create more diverse leisure environments and socially cohesive communities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-30T07:17:18Z
      DOI: 10.1177/23998083241303198
       
  • Shortest-path tree-based method for calculating visible area with time-
           and memory-saving preprocessing

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      Authors: Shota Tabata
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Visibility has extensive application in areas such as architecture, urban planning, and security. This study proposes a novel approximation method, called the shortest-path tree-based method (SPT-based method), for calculating the visible area using a random Delaunay network on a 2D plane. Various methods are available for calculating the visible area, including exact and approximation methods. However, it is difficult to calculate the visible area repeatedly in a space that has a vast number of obstacles while achieving efficient time and memory usage. The SPT-based method focuses on time- and memory-saving preprocessing. To achieve an efficient calculation of the visible area, we discretised a plane using a random Delaunay network and approximated the visible area using Dijkstra’s method. To evaluate the efficiency of the proposed method, we compared the calculation time, accuracy, and memory usage of the plane-sweep, ray-trace, brute-force, and SPT-based methods while considering the influence of the number of obstacles. This study provides valuable insights for researchers and practitioners for choosing the most suitable approach for their specific needs. Overall, the proposed method offers a time- and memory-efficient solution for calculating the visible area, making it suitable for a detailed analysis of the visual environment and providing a heuristic solution to the art gallery problem requiring repetitive calculations.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-23T04:17:13Z
      DOI: 10.1177/23998083241302570
       
  • Airbnb and the COVID-19 pandemic: A geospatial analysis of Greater London

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      Authors: Nan Wang, Stephen Hincks
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This paper examines the response of the Airbnb ‘market’ to the shock of COVID-19, exploring the spatio-temporal variations in Airbnb listings, revenues, and hosting patterns in Greater London over the pre-lockdown, lockdown, and post-lockdown periods. At an aggregate level, Airbnb listings and revenues were found to have declined during the pandemic with disruptions differentiated according to the professional or amateur status of hosts. We then disaggregate these global trends to neighbourhood level. We explore the relative importance of socio-demographic, accessibility and neighbourhood amenities to Airbnb revenue levels across the Capital over the course of the pandemic. In doing so, we expose patterns in the Airbnb market as a result of the COVID-19 shock, revealing a geography of spatial clustering in Airbnb revenue levels over time and variations and volatility based neighbourhood deprivation. While COVID-19 certainly delivered a disruptive effect on Airbnb in Greater London, the pandemic did not de-stabilise existing geographies of Airbnb, especially in Inner London, where Airbnb remains spatially entrenched and challenges around housing affordability and neighbourhood gentrification are acute.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-23T02:09:57Z
      DOI: 10.1177/23998083241302557
       
  • Valuing the ‘new normal’' Housing markets under COVID-19: Insights
           from a hybrid hedonic repeat sales model

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      Authors: Stephen Hincks, Chris Leishman, Hung Pham, Jenny Preece
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This study considers the impact of the COVID-19 pandemic on sub-national housing markets in Wales, focusing on the contribution of environmental and productivity attributes on house price change. Using a hybrid hedonic/repeat sales framework, we examine trends before, during, and after the pandemic. Initially, higher-quality environmental and productivity attributes were associated with a positive premium in price growth, while lower quality attributes were associated with a negative premium. However, during the pandemic’s second phase, these effects reversed but positive premiums for higher-quality attributes did not fully unwind during the transition to less acute phases of the pandemic. When we disaggregate the analysis for the urban-rural gradient, we find that both contexts placed a premium on high quality environmental housing, but lower quality productivity attributes negatively affected urban areas. The contribution of the study lies in revealing the complex, evolving and unequal relationship between the COVID-19 pandemic, housing preferences, and prices that, in our study context, have been subject to much conjecture but with little empirical investigation.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-22T03:59:10Z
      DOI: 10.1177/23998083241301846
       
  • Understanding intracity housing market dynamics: A state-space model with
           Bayesian nonparametric clustering approach

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      Authors: Yaopei Wang, Yong Tu, Wayne Xinwei Wan
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Understanding the intracity heterogeneities in housing market dynamics across microgeographic areas is important but challenging due to infrequent transactions. Unlike traditional methods that use trend-based clustering to improve the accuracy of local housing price and rent indices, we propose a novel hybrid model that combines the state-space model and the Bayesian nonparametric clustering approach to cluster neighbourhoods according to their temporal price volatility. We show that our methods improve the performance of traditional methods by 10-40%, using over 889,428 housing transactions in Singapore between 2006 and 2018. We also demonstrate a practical application of our method – monitoring neighbourhoods’ distinct market reactions to macroeconomic or policy shocks, which has important implications for urban planning and housing investment.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-22T03:36:52Z
      DOI: 10.1177/23998083241302373
       
  • Impact of urban satisfaction on settlement intention: Differences in
           household registration and city size

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      Authors: Yunxiao Dang, Dongsheng Zhan, Li Chen, Wenzhong Zhang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban satisfaction plays a crucial role in improving the settlement intention of urban residents. The household registration system has complicated the relationship between urban satisfaction and settlement intention, especially considering the diversity cities of different population size during the process of urbanization in China. Based on a large-scale survey in 2020 from the Ministry of Housing and Urban-Rural Development in 36 cities, this paper explores the impact of urban satisfaction on residents’ settlement intention, and the moderating impacts caused by household registration status and city population size. Multilevel model, multinomial logistic model, and Heckman two-stage method are used for the analysis. The results indicate that urban satisfaction is positively associated with settlement intention. Both the impacts of individual characteristics and city attributes on settlement intention varies with household registration status. Besides, there is a U-shaped relationship between urban population and settlement intention, and residents of cities with the smallest populations report high settlement intention. This research contributes to understanding the role of household registration system in moderating the relationship between urban satisfaction and settlement intention, and it offers insights into urban population introduction policy and healthy urbanization in China.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-21T09:05:49Z
      DOI: 10.1177/23998083241302188
       
  • Deep reinforcement learning for spatial resource allocation: A case study
           of school districting

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      Authors: Di Zhang, Senlin Mu, Joseph Mango, Xiang Li
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Spatial resource allocation is a multi-objective spatial optimization problem with multiple constraints. The division of school districts is a classic problem of spatial resource allocation. This paper proposes a new dynamically districting optimization method based on deep reinforcement learning to optimize the global effect of school districting. In the proposed method, the school district’s constantly adjusted allocation process is regarded as a multi-step Markov decision-making process. The method combines the advantages of a deep convolutional neural network with reinforcement learning for real-time response and flexibility, and directly learns behavioural policies based on the input of changing school district states. According to various constraints, this algorithm optimizes the distance of students to school and the utilization rate of schools, and it proposes a better allocation plan. To demonstrate its validity, the proposed method was evaluated using real datasets of two school districts in the United States. The experimental results studied in six different scenarios show that, compared with traditional algorithms, the new proposed method requires less prior knowledge and is globally optimal, and can provide a better allocation plan for school districting, which reduces the distance between students and schools and balances the utilization rate of schools.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-21T02:27:18Z
      DOI: 10.1177/23998083241302187
       
  • Assessment of carbon emission reduction potential in new-type urbanization
           policy: A perspective on carbon rebound effect

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      Authors: Qiaoru Wang, Zhenghao He, Tingyu Liu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      In this research, we utilize a refined model for carbon emissions, known as the Stochastic Frontier Approach (SFA), to measure the extent of the carbon rebound effect across a sample of 231 urban areas in China, spanning the years 2011 through 2019. Additionally, the study explores the impact that policies associated with the advancement of new urbanization have had on the aforementioned carbon rebound phenomenon. The findings of this thesis indicate that this policy can reduce carbon emission volumes effectively; however, there is also a significant carbon rebound effect, making the reduction less efficient than expected. After several robustness tests, the main conclusions remain consistent and reliable. Our investigation into the underlying mechanisms reveals that policies aimed at fostering new urbanization may attenuate the carbon rebound effect by enhancing the efficiency and composition of industrial sectors. However, technological advancements and the degree of energy efficiency remain pivotal in potentially escalating the carbon rebound effect. The analysis of variations across different scenarios demonstrates that the policy’s impact on the carbon rebound effect is subject to variation depending on several factors, including geographical contexts like provincial boundaries, the administrative hierarchy of cities, transportation infrastructure, and the constraints imposed by resource availability. As a multi-target policy, although this policy has a carbon rebound effect, it also has a significant social welfare effect, which coincides with the development goal of China. Ultimately, some suggestions are offered to enhance the role of this policy in promoting carbon emission reduction and to foster a virtuous interaction between this policy and economic growth.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-19T02:59:14Z
      DOI: 10.1177/23998083241301855
       
  • Predicting habitat functionality using habitat network models in urban
           planning

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      Authors: Oskar Kindvall, Meta Berghauser Pont, Ioanna Stavroulaki, Emy Lanemo, Lena Wigren, Monika Levan
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Recently, the European Union adopted a Nature restoration law that aims to stop the ongoing decline of biodiversity and even bring back nature to cities. This is challenging as urbanization is an ongoing process that thrives for more land and densification. In this paper we describe a new Open-Source GIS-tool that automates habitat network analyses and simultaneously generates several maps that can be used for assessments, targeting species survival in urban environments. One result of particular interest is the habitat functionality map that combines values of habitat quality and connectivity. We tested the tool’s ability to predict habitat functionality using amphibian occurrence data observed from the city of Gothenburg in Sweden. Our evaluation shows that habitat functionality was generally a good predictor of amphibian distribution. However, the predictability was sensitive to the cartographic representativity of the input biotope map used. Also, predictions of habitat functionality improved when estimating dispersal probabilities using the Cost-distance algorithm, compared to when using Euclidean distance from reproductive habitats. This finding supports the need to use connectivity models that are responsive to variation and changes in roads, traffic volumes and buildings when performing effect analyses on biodiversity in cities. Finally, we demonstrate how the tool can be used to easily identify areas where restoration measures can effectively increase habitat functionality for target species. This can help planners to find efficient solutions for increasing biodiversity within urban areas.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-11T02:11:18Z
      DOI: 10.1177/23998083241299165
       
  • CHASM: A configurational measure of socio-spatial residential segregation

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      Authors: Renato Tibiriçá de Saboya, Otavio Martins Peres
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Despite recent advances in the quantification of residential segregation, several important limitations persist. Zone-based measures have low resolution and treat all locations inside a zone as identical; oversimplify the possibility of interaction between zones; and underestimate the role of the street layout and how it can shape potential movement and exposure. Here, we propose a new measure of socio-spatial residential segregation called CHASM that estimates potential exposure between different social groups based on their positions in the street grid and comparing them to a hypothetical scenario in which all groups are evenly distributed (i.e., a situation of non-segregation). Depending on the type of centrality chosen for the analysis, its scores represent the degree to which the distances of a street segment to the different social groups are unevenly distributed or, alternatively, the degree to which different social groups tend to avoid sharing the same street segments in their trips. We tested CHASM’s validity through a random permutation test in a hypothetical scenario and a comparison with more traditional measures in a medium-sized Brazilian city. The results suggest that CHASM is indeed able to quantify residential segregation and: (a) better estimates distances, connections, and continuities between different areas of the city, including the implications of barriers that are overlooked in zone-based measures; (b) minimizes distortions introduced by zones’ arbitrary shapes; and (c) opens up new possibilities for testing alternative designs for the street system.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-07T08:13:15Z
      DOI: 10.1177/23998083241287701
       
  • Data requirements for a systematic analysis of urban food flows and their
           sustainability outcomes

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      Authors: Louise Guibrunet, Paul Hoekman, Andrea Bortolotti, Jane Battersby
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This paper systematically assesses the quantity and quality of existing secondary data on urban food flows, as well as its potential use to analyse the impacts of such flows on human health and environmental sustainability. To do so, the authors built a digital, open-access platform to systematise, store and visualise urban food flows data. Given the importance of systematically understanding diverse urban food systems, the objective of the platform is to ease the analysis and comparison of food flows across cities, and to provide a panorama of the quality of datasets and data gaps. By developing an accessible methodology that allows for effortless generation of data visualisations, additional urban food datasets can be included in the platform in order to enhance our common understanding of contemporary urban food metabolisms. The paper presents data on key nodes of urban food systems: production, imports, exports, processing, wholesale, retail, consumption, and food loss and waste. The platform also estimates the environmental impacts of each city’s diet and how much such a diet differs from a sustainable and healthy diet. To illustrate how the platform works, we present a preliminary analysis of four cities: Cape Town (South Africa), London (United Kingdom), Mexico City (Mexico) and Milan (Italy). We systematise and analyse pertinent secondary data for each city, and assess data quality and data gaps. We conclude with a reflection on the strengths and limitations of the online platform, and with an open invitation to use the platform to analyse other cities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-07T06:11:18Z
      DOI: 10.1177/23998083241298431
       
  • Creating an endless visual space: An Isovist analysis of a small
           traditional Chinese garden

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      Authors: Huishu Chen, Yangluxi Li, Li Yang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Traditional Chinese private gardens, as a unique spatial typology, create a maze-like quality through the arrangement of sightlines and pathways, offering occupants a sense of perpetual circulation and boundless time. The rich experiential nature cultivated within these confined spaces, alongside the ecological worldview of “harmony between heaven and humanity,” holds significant relevance for urban landscape design and the sustainable development of urban environments. While there is ample research literature on various aspects of garden spaces, studies exploring how private gardens generate visually infinite and cyclic spatial experiences within limited areas often remain confined to intuitive analysis, lacking concrete and rational explanations. This study employs the method of Isovist Analysis to test the validity of the spatial consciousness of “Limitless vision, Endless recurrence” within the spatial layout and tour organization of traditional private gardens, using the analysis of Isovists at eight scenic spots within the Xiaocanglang Water Courtyard, as well as an examination of visual-spatial changes along both primary and secondary pathways in different tour directions. It is hoped that this research method will serve as a tool for urban designers and landscape architects to assess spatial-visual characteristics and experiences during the design phase.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-06T07:01:49Z
      DOI: 10.1177/23998083241298739
       
  • What is civic participation in artificial intelligence'

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      Authors: Renée Sieber, Ana Brandusescu, Suthee Sangiambut, Abigail Adu-Daako
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      There are increasing calls across disciplines and sectors that the public should participate in decisions about the use of artificial intelligence (AI). Public input in governmental decision-making is particularly crucial to promoting a well-functioning democracy and mitigating harms from AI. However, AI’s opacity, mutability, and resource requirements impede meaningful civic engagement particularly in urban environments. Many prior systematic reviews of civic participation and AI draw on the smart city literature. However, several other disciplines influence civic participation in AI so a siloed disciplinary focus offers only partial guidance for participation’s future role in AI. Our multi-disciplinary analysis blends works in smart cities, and in public policy, communication and, importantly, computer science to reveal distinct and highly variable pathways for civic participation. We use a sequence of manual and automated steps to conduct a structured literature analysis beginning with over 3,000 articles. We categorize authors’ work on participation in AI into five themes: participation as a natural byproduct of automating government, participation facilitated through the medium of AI, participation in AI as quantification, participation as a technocracy of trust, and participation as meaningful. With few exceptions, authors seemed not to challenge the status quo nor diminish the authority of the experts.
      Authors focused on the processual without the influence and AI aided in that process orientation. We conclude that the future of public participation in AI requires careful attention to become meaningful including recognition of neoliberal intent and power differentials.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-11-01T11:12:31Z
      DOI: 10.1177/23998083241296200
       
  • Discovering the common latent structure of commercial districts focusing
           on the spatial co-occurrence relationship between stores

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      Authors: Kazuya Inagaki, Yusuke Hara
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Store agglomeration in a commercial district is considered to follow synergistic and complementary relationships between stores. The micro-interactions, that is, co-occurrence relationships, between stores are thought to create commercial districts’ universality and characteristics. This study aims to empirically identify latent attributes that can explain the mechanism of store agglomeration from the co-occurrence relationships between stores in commercial districts, and to identify universal characteristics in store agglomeration. We represented store agglomeration as a store co-occurrence network with stores as nodes and co-occurrence relationships between stores as links in 10 major commercial districts in Japan. We estimated latent attributes of stores that generated the store co-occurrence network and empirically clarified the quantitative and qualitative nature of store agglomeration. The co-occurrence networks of stores with estimated latent attributes were compared across those of districts, and the co-occurrence patterns common to latent attributes were clarified. The estimated latent attributes were empirically shown to have more explanatory power for the store agglomeration than the conventional business category classification, suggesting their usefulness as a new classification axis for stores. In addition, by comparing 10 districts, common co-occurrence relationships were extracted, and the universal spatial structure of store agglomeration was empirically clarified.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-10-25T12:35:49Z
      DOI: 10.1177/23998083241294111
       
  • How the marketing of real estate properties explains mortgage applicants
           by race and income

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      Authors: Isabelle Nilsson, Elizabeth C Delmelle
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      In this article, we study how the marketing of single-family homes explains the racial and income makeup of mortgage applicants in a neighborhood. We use a case study of the robust housing market of Charlotte, North Carolina, and annual, longitudinal real estate listing advertisements alongside mortgage lending data, to demonstrate how the share of properties advertised a certain way in a neighborhood in 1 year explains shares of mortgage applicants by race and income the following year. We classify property advertisement text using a semi-supervised learning algorithm into five categories following a housing investment and disinvestment to renewal continuum. We find stark racial disparities in mortgage applicants by housing type, even after controlling for income. We find that Black applicants nearly exclusively apply for mortgages in neighborhoods with a high share of properties advertised as disinvested with little profit-making promise. High-income White applicants rise as the share of advertised properties becomes more homogenous.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-10-24T12:12:11Z
      DOI: 10.1177/23998083241287956
       
  • Mismatch between flood risk and insurance protection: A county-level
           analysis in the contiguous United States

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      Authors: Yang Xue, Xinyu Fu, Chaosu Li
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Flood insurance plays a pivotal role in disaster management, providing the financial safety net for individuals and communities at risk. However, flood insurance penetration may not align with the actual flood risk over space. Using the National Risk Index and the National Flood Insurance Program (NFIP) Datasets, this study examines the county-level mismatch between flood risk and insurance protection across the contiguous United States, with an emphasis on both coastal and riverine flooding. Our findings indicate that, while a very limited number of high-risk counties are underinsured for coastal flooding, several high-risk counties experienced inadequate insurance protection for riverine flooding. These findings underscore the need for targeted policy interventions to improve flood risk awareness and insurance access in vulnerable areas facing the increasing impacts of climate change.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-10-24T07:23:49Z
      DOI: 10.1177/23998083241294113
       
  • tscluster: A python package for the optimal temporal clustering framework

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      Authors: Jolomi Tosanwumi, Jiazhou Liang, Daniel Silver, Ethan Fosse, Scott Sanner
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Temporal clustering extends the conventional task of data clustering by grouping time series data according to shared temporal trends across sociospatial units, with diverse applications in the social sciences, especially urban science. The two dominant methods are as follows: Time Series Clustering (TSC), with dynamic cluster centres but static labels for each entity, and Sequence Label Analysis (SLA), with static cluster centres but dynamic labels. To implement the universe of models spanning the design space between TSC and SLA, we present tscluster, an open-source Python framework. tscluster offers: (1) several innovative techniques, such as Bounded Dynamic Clustering (BDC), that are not available in existing libraries, allowing users to set an upper bound on the number of label changes and identify the most dynamically evolving time series; (2) a user-friendly interface for applying and comparing these methods; (3) globally optimal solutions for the clustering objective by employing a mixed-integer linear programming formulation, enhancing the reproducibility and robustness of the results in contrast to existing methods based on initialization-sensitive local optimization; and (4) a suite of visualization tools for interpretability and comparison of clustering results. We present our framework using a case study of neighbourhood change in Toronto, comparing two methods available in tscluster. Supplemental materials provide an additional case study of local business development in Chicago and a detailed mathematical exposition of our framework. tscluster can be installed via PyPI (pypi.org/project/tscluster), and the source code is accessible on Github (github.com/tscluster-project/tscluster). Documentation is available online at the tscluster website (tscluster.readthedocs.io).
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-10-23T07:05:09Z
      DOI: 10.1177/23998083241293833
       
  • Revisiting building height restriction policy in the historic center of
           Seoul: Exploring performance-based height management using view shadow
           simulation

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      Authors: Jae Min Lee, Justin Heejoon Lim, Jayun Heo
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This study empirically explores 3D isovists to explore an alternative approach to a 90 m height cap in Seoul’s historic center. We introduced the concept of “view shadow” in the city center to explore potential room for growth: (1) areas hidden by existing buildings and (2) areas visible but not altering the current skyline. The proposed approach integrates the concept of view shadow cast by existing towers to minimize visual impact and preserve iconic and historic views. The simulation findings indicate that a significant portion, approximately 31 sites or 58.5% of the total, can accommodate taller towers than 90 m without compromising the integrity of the historic skyline. The study demonstrates the ability to increase the floor area by 74% and up to 137% from existing conditions to revitalize Seoul’s historic center.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-10-23T01:57:51Z
      DOI: 10.1177/23998083241293866
       
  • Exploring the coherence and divergence between the objective and
           subjective measurement of streetscape perceptions at the neighborhood
           level: A case study in Shanghai

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      Authors: Qiwei Song, Yuxian Fang, Meikang Li, Jeroen van Ameijde, Waishan Qiu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Understanding micro-level perceptions of street scenes is highly concerned with residents’ behaviors and socioeconomic outcomes. While many studies rely on objective measures, such as physical features extracted from Street View Imagery (SVI) to proxy perceptions using derived formulas, others employ subjective measures from visual surveys to capture more subtle human perceptions. We argue that the two measurements can diverge significantly over the same perception concept, which might lead to opposite spatial implications in policy if not properly understood. Moreover, as perceptions are often examined individually, few studies have investigated their joint distribution patterns to reflect perceptions’ multi-dimensional nature. To fill the gaps, we collected five pairwise perceptions from SVIs (i.e., complexity, enclosure, greenness, imageability, and walkability) at the neighborhood level in Shanghai. Each perception consists of pairwise values subjectively measured using a GeoAI-based approach and objectively quantified using formulas. We statistically and spatially compared the coherence and divergence of the two measures, further examining the perceptual differences. Advanced techniques including cluster analysis and factor analysis were employed to jointly evaluate their spatial distribution discrepancy. Our results revealed more differences than similarities between the two measures statistically and spatially, confirming any spatial implications concluded from one approach can vary significantly from the other. The joint spatial pattern further corroborated our conclusions. Our study enriches the literature on micro-level street perception measures, uncovers their critical differences to guide future comparative studies, and offers new approaches for urban perception mapping.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-10-16T02:05:52Z
      DOI: 10.1177/23998083241292680
       
  • Can urban agglomeration policies promote regional economic agglomeration'
           Evidence from the Yangtze River Economic Belt in China

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      Authors: Peipei Hu, Yingjun Huang, Qiankun He, Gencheng Zhang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The impact of implementing urban agglomeration policies (UAPs) on regional economic agglomeration is crucial for achieving coordinated regional development. This study examines the effects of UAPs on economic agglomeration in the Yangtze River Economic Belt (YREB) in China using panel data from 108 cities spanning from 2006 to 2020. Various research methodologies, such as spatio-temporal variation analysis, Differences-in-Differences (DID), Propensity Score Matching DID (PSM-DID), and Spatial Autocorrelation DID (SACDID) models, are employed. The results indicate a diffusion effect in economic agglomeration of the YREB, leading to a transition from a multilevel center-periphery structure to a contiguous clustering pattern. UAPs have, however, resulted in the concentration of the regional economy towards central cities. Urban agglomerations exhibit an internal siphon effect and a diffusion effect on their exterior. The combination of these two effects manifests itself as a certain degree of siphon. Specifically, UAPs have caused both siphon and diffusion effects in the middle region of the YREB, with less significant impacts in the eastern and western regions. The siphon effects of central cities are influenced by both geographical distance from other cities and, more importantly, economic disparities between them. During the study period, the UAPs served as the indirect rather than direct factor of regional economic coordination.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-10-15T06:46:24Z
      DOI: 10.1177/23998083241293217
       
  • Long-term validation of inner-urban mobility metrics derived from
           Twitter/X

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      Authors: Steffen Knoblauch, Simon Groß, Sven Lautenbach, Antonio Augusto de Aragão Rocha, Marta C González, Bernd Resch, Dorian Arifi, Thomas Jänisch, Ivonne Morales, Alexander Zipf
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban mobility analysis using Twitter as a proxy has gained significant attention in various application fields; however, long-term validation studies are scarce. This paper addresses this gap by assessing the reliability of Twitter data for modeling inner-urban mobility dynamics over a 27-month period in the. metropolitan area of Rio de Janeiro, Brazil. The evaluation involves the validation of Twitter-derived mobility estimates at both temporal and spatial scales, employing over 1.6 × 1011 mobile phone records of around three million users during the non-stationary mobility period from April 2020 to. June 2022, which coincided with the COVID-19 pandemic. The results highlight the need for caution when using Twitter for short-term modeling of urban mobility flows. Short-term inference can be influenced by Twitter policy changes and the availability of publicly accessible tweets. On the other hand, this long-term study demonstrates that employing multiple mobility metrics simultaneously, analyzing dynamic and static mobility changes concurrently, and employing robust preprocessing techniques such as rolling window downsampling can enhance the inference capabilities of Twitter data. These novel insights gained from a long-term perspective are vital, as Twitter - rebranded to X in 2023 - is extensively used by researchers worldwide to infer human movement patterns. Since conclusions drawn from studies using Twitter could be used to inform public policy, emergency response, and urban planning, evaluating the reliability of this data is of utmost importance.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-10-14T10:21:18Z
      DOI: 10.1177/23998083241278275
       
  • Can regionalization enhance the performance of land-use change models in
           rapidly urbanizing areas'

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      Authors: Gustavo Manuel Cruz-Bello, Martín Enrique Romero-Sánchez, José Mauricio Galeana-Pizaña
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The performance of Land Use Change (LUC) models is influenced by the regional spatial characteristics that trigger the changes. However, the literature on LUC models generally reports validation results for entire regions without considering subregions that differ significantly in their LUC drivers. This research explores how the LUC driving forces differ among subregions and whether regionalization can improve the performance of LUC models in areas undergoing rapid urbanization. We analyzed the Geomod, Cellular Automata-Markov, and Land Change Modeler models across rural and urbanized subregions on the western edge of Mexico City. Regionalization significantly enhanced the overall accuracy of the models and the concordance of spatial patterns with the reference data in rural regions but was of limited benefit in urbanized regions. This shows the need to consider regionalized modeling to improve the performance of LUC models when there are noticeable differences in LUC drivers between subregions. These findings will enhance the usefulness of LUC models for urban planning and land management policies, promoting more precise and effective decision-making.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-10-14T07:21:32Z
      DOI: 10.1177/23998083241292927
       
  • Unveiling multifaceted resilience: A heterogeneous graph neural network
           approach for analyzing locale recovery patterns

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      Authors: Jiaxin Du, Xinyue Ye, Xiao Huang, Yi Qiang, Chunwu Zhu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Resilience, denoting the capacity to swiftly recover to a state of normalcy subsequent to the occurrence of a disaster, constitutes a multifaceted phenomenon necessitating in-depth investigation. This study undertakes the quantification of resilience pertaining to specific locales through the utilization of heterogeneous data encompassing visitation patterns, demographic particulars, and points of interest (POI). A heterogeneous graph neural network is applied to model the resilience of these locales in Galveston, TX, USA. Our model outperforms regression models and other homogeneous baseline methodologies. Subsequent analysis unveils discernible resilience patterns intertwined with metrics such as visitation frequencies, visitors’ travel behaviors, and geographical attributes. In comparison to resilience investigations solely predicated upon visitation counts, our approach captures a more extensive array of information, thereby yielding a comprehensive understanding of the locale’s resilience.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-10-03T07:23:11Z
      DOI: 10.1177/23998083241288689
       
  • Digital twin for supporting decision-making and stakeholder collaboration
           in urban decarbonization processes. A participatory development in
           Gothenburg

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      Authors: Daniela Maiullari, Claudio Nageli, Andreas Rudena, Åsa Isacson, Giliam Dokter, Ilse Ellenbroek, Holger Wallbaum, Liane Thuvander
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      City Digital Twins have emerged as pivotal tools for representing and modelling urban systems. While existing literature emphasizes technological and framework development, limited attention has been given to the practical usability of digital twins in urban planning and decision-making processes. This paper addresses this gap by presenting a participatory approach for a city digital twin (CDTE) development, specifically tailored for supporting stakeholder communication and decision-making in the urban energy transition domain. The study, conducted in three phases, utilizes participatory methods, involving local stakeholders in the development process. The focus is on the Swedish city of Gothenburg, which is actively pursuing climate-neutral goals by 2030. The research integrates quantitative energy modelling and the creation of a web-based interface for the CDTE. The scenarios, grounded in local needs and challenges, explore the impacts of urban development models, climate warming and renovation measures on the building stock. The CDTE, developed and tested through workshops with diverse stakeholders, proves to be effective for the visualization and the discussion of various decarbonization scenarios. Key findings from users’ assessments underscore the significance of clarity and readability in scenario content and user interface for fostering interactions among different administrative spheres. This research contributes to the broader discourse on leveraging City Digital Twins for informed decision-making in urban contexts, providing insights into the practical application of digital twins in addressing the complex challenges of urban energy transition.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-10-01T11:02:11Z
      DOI: 10.1177/23998083241286030
       
  • What amenities drive footfall in UK town centres' A machine learning
           approach using OpenStreetMap data

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      Authors: Viriya Taecharungroj, Nikos Ntounis
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      In the United Kingdom, town centres face significant economic and social challenges, with amenities playing a crucial role in their vitality. However, no existing study has thoroughly investigated the relationship between amenities and footfall, a key measure of place vitality. This research addresses this gap by examining which amenities drive footfall in UK town centres. The study employs the random forest modelling, to analyse data from OpenStreetMap (OSM) and footfall data from 960 counters across the United Kingdom. Our findings reveal that OSM data can effectively predict footfall, highlighting the importance of diverse amenities. Key amenities identified include hotels, pedestrian ways, and retail establishments. Furthermore, the study identifies critical inflection points where the presence of certain amenities significantly boosts urban vitality. These insights offer valuable guidance for urban planning and development, suggesting that a mix of diverse amenities at appropriate levels can enhance the attractiveness and vitality of town centres.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-10-01T07:03:38Z
      DOI: 10.1177/23998083241290343
       
  • Toward volumetric urbanism: Analysing the spatial-temporal dynamics of 3D
           floor space use in the built environment

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      Authors: Yi-Ya Hsu, Hoon Han
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban studies have gradually expanded their vision from horizontal to volumetric dimensions, responding to the growing compactness and density of cities. Though land use study has a long history, the study of urban space use from a volumetric perspective remains limited. However, vertical spatial difference is as substantial as horizontal spatial variance, especially in mixed-use developments. Addressing this, the research analyses 3D floor space use dynamics in the City of Sydney between 2007, 2012, and 2017 using ArcGIS Pro and visualising results with Plotly. Utilising Voxel Automata and Markov transition logic in Netlogo3D, we simulate potential future 3D urban structures. The model transforms floor spaces into voxels, assigns varying transition probabilities to voxels based on self-state, and applies the influence of neighbourhood state. The research underscores the challenges in developing varied transition probabilities for different floors, revealing the complexity of modelling 3D space use dynamics. The findings provide a more realistic understanding of the complex urban system and cities’ volumetric development. Additionally, the utilised 3D visualisation method can extend its utility beyond floor usage types to other spatial variables. Consequently, the research highlights the importance of 3D system thinking in future urban growth and expansion studies, and suggests more precise transition rules for modelling specific time points, benefiting future smart governance.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-09-21T11:48:02Z
      DOI: 10.1177/23998083241286592
       
  • Radial analysis and scaling of housing prices in French urban areas

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      Authors: Gaëtan Laziou, Rémi Lemoy, Marion Le Texier
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban scaling laws summarize how attributes evolve with city size. However, one limitation concerns the aggregate view of this approach, which leads to neglecting the internal structure of cities. This is an important issue regarding housing prices, given their significant variations across space. Based on a dataset compiling millions of real estate transactions over the period 2017–2021, we investigate the regularities of the radial (center-periphery) profiles of housing prices across cities, with respect to their size. Results are threefold. First, they corroborate prior findings in the urban scaling literature stating that largest cities agglomerate higher housing prices. Second, we find that housing price radial profiles scale in three dimensions with the power 1/5 of city population. After rescaling, great regularities between radial profiles can be observed, although some locational amenities have a significant impact on prices. Third, it appears that our approach with rescaled profiles fails to explain housing price variations in the city center across cities. In fact, prices near the city center rise much faster with city size than in the periphery. This has strong implications for low-income households seeking homeownership because prohibitive prices in the center may contribute to pushing them out into peripheral locations, especially in large cities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-09-19T07:01:12Z
      DOI: 10.1177/23998083241281890
       
  • Investigating urban morphological drivers of household water use in
           developing economies: A structural equation model approach

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      Authors: Tazyeen Alam, Ankhi Banerjee
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban populations are snowballing, increasing household (HH) water consumption. The growing housing density, the expanding infrastructure, and altered land use patterns place increasing pressure on the water supply and usage. This makes it harder for urban HHs to obtain clean water and worsens water scarcity, with infrastructural and environmental implications for highly populated metropolitan areas. This study aims to quantitatively evaluate the impact of urban morphology on household water use in a developing economy using a Structural Equation Model (SEM), specifically within the growing urban centres surrounding Kolkata in South Bengal. The primary hypothesis projects an increase in urban morphological indicators and HH characteristics that significantly affect water use. The findings reveal that increases in urban morphological indicators are associated with a 34.2% decrease in HH water use, highlighting the importance of urban planning strategies that emphasize compact and diverse urban forms. This work highlights new ways of building cities that consider morphological aspects and allow cities to expand in a way that conserves HH water while being resilient to rapid urban change.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-09-16T10:03:50Z
      DOI: 10.1177/23998083241284824
       
  • The behavioural house indicator: A faster and real time small-area
           deprivation measure for England

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      Authors: Eduardo Viegas, Tim S. Evans
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Researchers have been long preoccupied with the measuring and monitoring of economic and social deprivation at small scales, neighbourhood, level in order to provide official government agencies and policy makers with more precise data insights. Whist valuable methodologies have been developed, the exercise of data collection associated with these methods tends to be expensive, time consuming, published infrequently with significant time delays, and subject to recurring changes to methodology. Here, we propose a novel method based on a straightforward methodology and data sources to generate a faster and real time indicator for deprivation at different scaling, small to larger areas. The results of our work show that our method provides a consistent view of deprivation across the regions of England and Wales, which are in line with the other indexes, but also highlight specific flash points of deep rural and highly dense urban deprivation areas that are not well captured by existing indexes. Our method is intended to aid researchers and policy makers by complementing existing but infrequent indexes.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-09-16T08:27:11Z
      DOI: 10.1177/23998083241283124
       
  • Towards a more realistic estimation of urban land take by combining
           cadastral parcels and building footprints

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      Authors: Apostolos Lagarias, Demetris Stathakis
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Despite its importance as a research issue, a widely accepted methodology of estimating land take resulting from urbanization has not yet been reached. Accurate geospatial datasets are currently available at a European and global level; however, different methods of quantifying urban land take could lead to diverse outputs, potentially resulting in underestimation. This can be alarming as encroaching urban sprawl is emerging as a major environmental challenge by destroying natural habitats, consuming productive agricultural land, and contributing to climate change by increasing energy demands. To address this knowledge gap, we propose an estimation of urban land take that combines cadastral parcels and building footprints. Land parcels can be considered as a suitable minimum mapping unit as they are directly related to the spatial level where economic decisions on land use conversion are made. The proposed geospatial method is compared to methods that depend on datasets of High Resolution Layer Imperviousness, Global Building Footprints (alone), Corine Land Cover, Urban Atlas, and Global Human Settlement Layer. The method is exemplified in case studies in Greece, specifically: (a) two islands of the South Aegean Region (Mykonos and Thera), that are heavily impacted by tourism development and sprawl and (b) a peri-urban zone (Thermaikos-Michaniona) within the metropolitan area of Thessaloniki, impacted by intense suburbanization. Results show that urban land consumes important shares of available land since the mid-20th century, this fact highlighting the dynamic encroachment of urban development. Calculation shows that other methods could underestimate urbanized areas by up to 80%–90%. In the discussion section, the advantages of shifting the focus from the pixel to the parcel are further justified, while explicit links to spatial planning policies for sprawl containment are drawn. Such policies could be informed by more realistic estimations of urban land take, in order to proceed with strategic and regulatory measures to support the ‘no net land take’ policy of Europe.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-09-14T10:24:17Z
      DOI: 10.1177/23998083241282092
       
  • A sidewalk-level urban heat risk assessment framework using pedestrian
           mobility and urban microclimate modeling

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      Authors: Nicola Colaninno, Rounaq Basu, Maryam Hosseini, Abdulaziz Alhassan, Liu Liu, Andres Sevtsuk
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Climate change and the associated increase in heat-related hazards pose a pressing threat to urban residents’ health and well-being. People, when walking in particular, are at risk of experiencing heat stress as they navigate urban environments. This study proposes a novel heat risk assessment framework combining pedestrian mobility modeling with urban microclimate modeling. Using this framework, we assessed pedestrian heat-related exposure and risk in urban areas by integrating the Universal Thermal Climate Index (UTCI) as the hazard and pedestrian trips to critical destinations as exposure. We considered temporal variation, in both hazard and exposure, by examining different time periods during the day—morning peak, midday, and evening peak. In addition to hazard and exposure, we also considered vulnerability by focusing on young children and older adults. We contribute to improving the spatial resolution of heat risk assessment by analyzing the hazard for pedestrian trips between home locations and five critical destinations—bus stops, rail stations, parks, schools, and commercial amenities—at the address-point level and using a pedestrian network comprising sidewalks and crosswalks. Our framework helps identify sidewalks with high heat exposure levels as well as home locations with high cumulative heat risk, accounting for walking trips to critical destinations along feasible routes. We demonstrated the effectiveness of this framework by applying it to a 36-square-kilometer area of central Los Angeles, CA. Our findings offer valuable information to urban planners and policy-makers, supporting evidence-based prioritization of intervention sites, climate adaptation strategies, and policy decisions essential for climate-proof planning. By implementing targeted interventions in areas where heat hazard is expected to affect the most vulnerable pedestrians, planners can create heat-resilient, pedestrian-friendly environments while prioritizing the health and well-being of vulnerable groups. This study contributes to the growing knowledge of robust risk assessment methodologies for climate-proof planning, specifically with regard to addressing outdoor heat-related risks during extreme heat events.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-09-08T10:46:58Z
      DOI: 10.1177/23998083241280746
       
  • Mapping sense of place as a measurable urban identity: Using street view
           images and machine learning to identify building façade materials

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      Authors: Xinghan Chen, Xiangwen Ding, Yu Ye
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Sense of place, as an intangible perception, is widely recognized as an urban identity and of great value in both cross-cultural studies and contemporary urbanism. Building façade material can effectively capture sense of place due to its combination of physical and social attributes. Nevertheless, there are no widely implementable and high-resolution approaches to identify façade materials on a large scale. As a response, this study proposes a method using street view images (SVIs) and a set of deep Convolutional Neural Networks (CNNs) to identify building façade materials. Specifically, a large cross-cultural training set was built to promote generalizability. Buildings within SVIs were divided into high-resolution rectangular images and classified using a well-trained Residual Network-50 (ResNet-50) model. Sense of place and its spatial patterns were then depicted by measuring façade material and analytical indicators including diversity and continuity. Eight cities worldwide with distinctive urban identities were examined. The findings revealed that compared to Asian cities, New York City, Chicago, and London are similar, while Paris and Tokyo are more distinctive. While challenges persist in comprehensively measuring the sense of place, the analysis of façade materials offers an insightful indicator that can assist in enhancing urban identity for contemporary urbanism. This study not only promotes the fine development of urban science through the empowerment of intelligent algorithms but also introduces a new perspective on exploring unmeasurable qualities based on the objective physical environment.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-09-01T03:59:28Z
      DOI: 10.1177/23998083241279992
       
  • The impact of urban form on physical change: A quantitative and diachronic
           analysis of urban form evolution in Midtown Manhattan

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      Authors: Onur Tümtürk, Justyna Karakiewicz, Fjalar J de Haan
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The importance of urban form as a key factor affecting future development and transformation patterns is well-recognised in urban morphology. However, despite the need for a diachronic approach to rigorously understand the form-change relationship, studies utilising longitudinal datasets remain scarce, and only a small fraction employs quantitative methodologies and morphometric approaches. This paper aims to quantitatively examine how the character of urban form elements and their spatial arrangements influence patterns of physical change, and to assess the performance of geometric and configurational urban form measures of plots, buildings, and streets in explaining physical change patterns over time. We hypothesise that configurational measures, being more sensitive to the relations between urban form elements, can better explain physical changes compared to conventional geometric measures predominantly adopted thus far. To test this hypothesis, we present a diachronic and quantitative methodology to measure urban form conditions and the patterns of physical change in Midtown Manhattan through four time frames (1890, 1920, 1956, and 2021), using a longitudinal geospatial database generated from historical cartographic resources and recent digital datasets. The association between urban form and physical change is demonstrated through statistical analysis. The findings prove that while the prevailing hypotheses emphasising the effect of geometric measures, such as size and shape, are often off the mark, configurational and access-based measures of plots and streets can accurately describe the dynamic relationships between form and change. The character of urban form patterns and structures measured by configurational variables is more reliable than the individual and geometric quality of urban form elements in explaining the dynamics of physical change and persistence. Our empirical findings add to the rapidly expanding fields of urban morphometrics and provide data-informed insights to improve the resilience and adaptive capacity of urban spaces.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-30T11:33:26Z
      DOI: 10.1177/23998083241272096
       
  • From urban modelling to city digital twins – Reflections from the
           applied urban modelling (AUM) symposia

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      Authors: Li Wan, Ying Jin, Marcial Echenique, Michael Batty, Michael Wegener
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      City digital twins (CDTs), as digital replica of urban systems and development processes, have been heralded as the next-generation technology for urban planning and management. Arguably, the concept of CDTs is not new. Prior to CDTs, applied urban modelling has been playing a pivot role in supporting city and infrastructure planning since the 1960s. Examining CDTs in relation to conventional urban models can thus offer valuable insights into their nature, potential, and challenges. Such a comparative, reflective exercise, however, remains rare. This commentary aims to share insights and reflections from a dedicated applied urban modelling (AUM) community. It is argued that to substantiate the power of CDTs, a theory-driven modelling strategy is essential for both practical policy analysis and knowledge discovery. Modellers must think beyond the technical perspective and exploring novel use of CDTs beyond optimisation. A blind pursuit for data without building on and expanding existing domain knowledge remains an existential risk for CDTs.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-30T04:23:05Z
      DOI: 10.1177/23998083241279601
       
  • Interdependence and coordination challenges: EV charging infrastructure
           and carbon emissions in the Yangtze River Delta

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      Authors: Qiqi Huang, Changying Xiang
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The ambition towards net-zero emission fuels the significance of electric vehicle charging infrastructure (EVCI) as a strategic asset. Yet, a conspicuous gap remains in the comprehensive quantitative analysis of its impact on carbon emissions stemming from fossil fuel combustion, referred to as ODIAC-CE. This study embarks on a longitudinal comparison of EVCI and ODIAC-CE data in 2018 and 2020, further classifying cities by scale to analyze the association between expansion of EVCI and ODIAC-CE change. Utilizing a battery of analytical tools, including correlation analysis, spatial autocorrelation, and coupling coordination analysis, the study dissects the evolving relationship between EVCI and ODIAC-CE within Yangtze River Delta in China. The results underscore a growing interdependence between EVCI expansion and ODIAC-CE change, yet pronounced heterogeneities in coupling coordination are evident across urban scales. Megacity and supercity exhibit quality coordination between rapid expansion of EVCI and ODIAC-CE dynamics. However, in most large, medium-sized, and small cities, the impact of EVCI growth on ODIAC-CE change has proven to be inconsistent or mismatched, affected by various factors such as location and infrastructure, industrial and technological patterns, and social practice and awareness. The study provides systematic insights into potential solutions for decarbonization through EVCI deployment at regional and city levels.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-26T09:00:44Z
      DOI: 10.1177/23998083241277865
       
  • Integrating green space measures into future town planning in Zhejiang,
           China

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      Authors: Yuanzhao Wang, ChengHe Guan
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Various spatial indices have been used by scholars to evaluate the built environment of towns. However, previous analysis has fallen short in systematically addressing the distribution of green space in future town planning. This paper fills the gap by integrating green space indices in an expanded urban intensity framework and comparing existing conditions (2018) and future planning schemes (2030) of eleven towns in Zhejiang Province, China. In this paper, we computed spatial indices in ARCGIS and FRAGSTATS, used correlation analysis in STATA for statistical analysis, and adopted demographic, economic, and environmental variables to validate the selected indices. The results show that: (1) The future planning schemes can result in either reduction of green spaces in town centers or uneven distribution of green spaces; (2) Validation of green space indicators reveals observable association with the normalized difference vegetation index (NDVI), which implies that the chosen framework can effectively reflect the condition of greenery; and (3) The regulatory detailed planning does not always improve the future spatial layout of towns, especially after considering green space distributions. These findings emphasize the importance of suitable spatial layouts of green spaces over large monolithic blocks for effective planning. Moreover, achieving optimal urban intensity necessitates a balanced distribution of the built and green spaces. Finally, the integration of green space factors and the adoption of a comprehensive approach, as highlighted in this study, can serve as a valuable guide for town planners and policymakers in different jurisdictions to achieve more desirable spatial layouts.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-24T08:01:07Z
      DOI: 10.1177/23998083241274913
       
  • Rail journey cost calculator for Great Britain

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      Authors: Federico Botta
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Accessibility of different places, such as hospitals or areas with jobs, is important in understanding transportation systems, urban environments, and potential inequalities in what services and opportunities different people can reach. Often, research in this area is framed around the question of whether people living in an area are able to reach certain destinations within a prespecified time frame. However, the cost of such journeys, and whether they are affordable, is often omitted or not considered to the same level. Here, we present a Python package and an associated data set which allows to analyse the cost of train journeys in Great Britain. We present the original data set we used to construct this, the Python package we developed to analyse it, and the output data set which we generated. We envisage our work to allow researchers, policy makers, and other stakeholders, to investigate questions around the cost of train journeys, any geographical or social inequalities arising from this, and how the transport system could be improved.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-24T05:24:44Z
      DOI: 10.1177/23998083241276569
       
  • Multidimensional factors correlated with population changes according to
           city size in Japan

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      Authors: Haruka Kato
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Many developed countries need to plan urban policies based on multidimensional factors related to population change. However, empirical research has been inconsistent with respect to identifying these factors, including economic-, social-, and urban-planning-related factors. The purpose of this study is to clarify the nonlinear multidimensional factors that are correlated with population changes according to the city size. In the analysis, the population change rate was defined as the outcome variable, and 269 economic, social, and educational index (ESE index) were used as predictor variables. Data were stratified according to three city sizes. Using the ESE index, the XGBoost algorithm was used to analyze the nonlinear relationship between the population change rate and multidimensional data. As a key result, population changes were strongly correlated with social-related indicators, such as the population change rate among persons ages 0–14 years in small-sized cities, the natural population change rate in medium-sized cities, and the migration change rate in large-sized cities. Regarding the population decline, Japan has 1304 shrinking cities, which are primarily comprised of medium-sized and small-sized cities. In such cities, other than social-related factors, population changes correlated with the financial strength index as an economic-related factor in medium-sized cities and the designation of underpopulated areas as an urban-planning-related factor in small-sized cities. Among the multidimensional factors, cities of different sizes were characterized by factors other than social-related indicators. These multifaceted factors could provide preliminary insights for urban policymakers to explore various policy measures on which they need to focus, depending on the city’s size.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-19T08:05:50Z
      DOI: 10.1177/23998083241274381
       
  • Mapping pedestrian network level outdoor heat hazard distributions in
           Philadelphia

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      Authors: Xiaojiang Li
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      With the rise of global temperature, many cities are suffering from more and more frequent extreme heat in hot summers. Quantitative information on the spatial distributions of urban heat has become more and more important for extreme heat mitigation and adaptation in cities. This study first investigated the fine-level heat hazard distributions at the sidewalk and building block level from the pedestrian perspective in Philadelphia, Pennsylvania. The urban microclimate modeling based on a high-resolution urban geometrical model was used to generate the 1m resolution outdoor heat hazard map in the study area. The sidewalk map was overlaid on the generated high-resolution heat hazard map to estimate the sidewalk level heat hazard. Based on the sidewalk level heat hazard map, this study further calculated the heat hazard level in the 400m walkshed along sidewalks for each building block. The building level hazard data were then aggregated at the census tract level to compare with the socioeconomic and racial/ethnic variables. The result shows that neighborhoods with higher proportion of African Americans have a higher heat hazard level in Philadelphia. This study would provide new insights for developing more thermally comfortable and pedestrian-friendly neighborhoods in the context of climate change.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-19T07:56:41Z
      DOI: 10.1177/23998083241274391
       
  • The rhythm of risk: Exploring spatio-temporal patterns of urban
           vulnerability with ambulance calls data

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      Authors: Mikhail Sirenko, Tina Comes, Alexander Verbraeck
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban vulnerability is affected by changing patterns of hazards due to climate change, increasing inequalities, rapid urban growth and inadequate infrastructure. While we have a relatively good understanding of how urban vulnerability changes in space, we know relatively little about the temporal dynamics of urban vulnerability. This paper presents a framework to assess urban vulnerability over time and space to address this gap. We apply the framework to Amsterdam, Rotterdam, and The Hague, the Netherlands. Using high-resolution, anonymised ambulance calls and socio-economic, built environment, and proximity data, we identify three temporal patterns: ’Midday Peaks’, ’Early Birds’, and ’All-Day All-Night’. Each pattern represents a unique rhythm of risk arising from the interaction of people with diverse demographic and socio-economic backgrounds and the temporal flow of their daily activities within various urban environments. Our findings also highlight the polycentric nature of modern Dutch cities, where similar rhythms emerge in areas with varying population densities. Through these case studies, we demonstrate that our framework uncovers the spatio-temporal dynamics of urban vulnerability. These insights suggest that a more nuanced approach is necessary for assessing urban vulnerability and enhancing preparedness efforts.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-14T12:19:42Z
      DOI: 10.1177/23998083241272095
       
  • Decoding Namboothiri illams of Kerala: A shape grammar approach

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      Authors: Linas Fathima A, Chithra K
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The mana/illam is a courtyard house typology found in the southern Indian state of Kerala, specific to the elite Namboothiri Brahmin community, who are members of the highest caste in the Hindu hierarchy, noted for their scholarship and wealth. These are highly decorated palatial houses built using timber or exposed laterite with sloped gable roofing designed to survive the heavy monsoons, expressive of Kerala’s rich vernacular and traditional architecture. This paper describes the language of mana/illam using shape grammar. To formulate the shape grammar, 36 samples of mana/illams across Kerala were architecturally documented, analysed, and their characteristics and differences in typology were determined. Three typologies of mana/illams are identified; spatial configurations, proportions, and hierarchy are examined, from which the vocabulary and rulesets for the shape grammar are formulated. Sixty-eight shape rules are defined across 20 stages. Sixty plan typologies of mana/illam are generated to illustrate the grammar.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-13T10:45:56Z
      DOI: 10.1177/23998083241271457
       
  • Intentional travel group and social network: Identification and dynamics
           during a pandemic

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      Authors: Mingzhi Zhou, Shuyu Lei, Jiangyue Wu, Hanxi Ma, David M Levinson, Jiangping Zhou
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Using multiday continuous smartcard data in 2020, we investigate group-based travel in Hong Kong metro system by identifying metro riders intentionally traveling in groups (ITGs). ITGs serve as our proxies for citywide physical social interactions. Considering ITG members are interrelated through group-based trips, we construct a social network (an ITG network) formed by ITGs to explore the network properties and structures of ITG activities. Examining ITGs both before and during the COVID-19 pandemic, we measure the spatial patterns of ITGs and their dynamics across locales and over time. We find that the degree of the ITG network follows a heavy-tailed distribution. The network size and interconnections vary across time. Some ITG members are more influential vertices than others in maintaining the networks’ topological properties. We illustrate how new data and methods can be used to explore in-person interactions and social activity patterns in transit-reliant cities.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-12T11:58:20Z
      DOI: 10.1177/23998083241271453
       
  • Accessibility derivative: Measuring the accessibility contribution of
           public transit routes

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      Authors: Luyu Liu, Harvey J Miller
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Accessibility is one of the most essential objectives of public transit systems as the transit service’s useability and service quality. The accessibility of transit systems as a whole is well understood; however, it is still unclear how each route contributes to the system-wide accessibility. Meanwhile, with a higher risk of disruptions and more uncertainties from climate change and other disruptions, there is an urgent need to systematically study the impacts of service change with the contribution of each route to general accessibility. To address this gap, we introduce the accessibility derivative, a model-agnostic measure of the contribution of each route in a transit system. We define the derivative of a route as the systemwide change in accessibility after removing the route from the system. We demonstrate how to calculate the derivative numerically from widely available public transit schedule and automated passenger count data. The measure reflects the inherent structure of a transit system and reveals the impacts of potential route-level service changes. The results provide firsthand evidence on public transit assessment and planning, including performance assessment, schedule redesign, and planning transfers.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-12T06:33:38Z
      DOI: 10.1177/23998083241272098
       
  • ‘Local Hubs and Global Gateways’: Understanding the impact of
           Singapore’s master plan on urban polycentricity

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      Authors: Cai Wu, Mingshu Wang, Jiong Wang, Duncan Smith, Menno-Jan Kraak
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Master plans are pivotal in strategising urban development, dictating land use, building height, and development intensity. These plans influence the spatial arrangement of urban infrastructure and activities, shaping the morphological and dynamic urban spatial structure. This study evaluates Singapore’s master plan’s effect on urban spatial structure, utilising data extracted from the master plan to project future land use and spatial interaction scenarios. By simulating the changing commercial floor space in different urban centres and its impact on commuting patterns, we evaluate the master plan’s impact on urban spatial structure and promoting polycentric urban development. Singapore’s master plan, with a clear vision towards polycentricity through the ‘Local hubs and global gateways’ strategy, is examined for its impact on urban spatial structure. The study uses urban mobility data and spatial network analysis to reveal how the master plan aims to decentralise development from the Central Business District (CBD) and distribute economic activities across various regions. Our findings indicate that regional centres and local hubs are becoming more autonomous while the CBD remains dominant. The results also highlight the importance of integrating morphological and functional polycentricity measurements and socioeconomic indicators to comprehensively evaluate urban development strategies. This study contributes to understanding urban spatial structure and offers practical insights for future urban planning.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-09T12:59:32Z
      DOI: 10.1177/23998083241267070
       
  • Modelling sprawl in a medium-sized urban area considering the future
           arrival of autonomous vehicles

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      Authors: Rubén Cordera, Soledad Nogués, Esther González-González, José Luis Moura
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Cities may undergo important changes in the coming years driven by various economic, social, and technological innovations, such as those related to autonomous mobility. Among other effects, autonomous vehicles may affect morpho-functional patterns of urban development and, especially, may reinforce or reduce dispersed development patterns, which have been relevant in many cities, particularly in the last decades. In order to offer an assessment of these possible effects, we propose a new urban sprawl index to measure the degree of dispersion/concentration of settlements in the medium-sized urban area of a Spanish city (Santander, Cantabria). Further, we explain the distribution of this index by means of a regression model, showing that variables such as average household income, trip time to the main urban centre, or the percentage of people using cars to commute to work are relevant factors that correlate positively with urban sprawl. Finally, we apply the proposed model to different scenarios to examine how the development of autonomous mobility could affect the characteristics of the analysed settlements. The results obtained suggest that, in scenarios with higher car usage and longer trip times to the urban centre because of the larger number of circulating vehicles, the form of urban settlements, especially those at an intermediate distance from the urban core, could experience an increase in sprawl. Therefore, Autonomous Vehicles could promote, under certain conditions, an urban form with more sustainability problems.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-09T12:17:27Z
      DOI: 10.1177/23998083241272664
       
  • Cool colors promote a restorative sidewalk experience: A study on effects
           of color and pattern design of ground murals on mood states and perceived
           restorativeness using 2D street view images

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      Authors: Lanqing Gu, Annika Dimitrov-Discher, Martin Knöll, Jenny Roe
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Ground murals have been increasingly applied as a tactical urban design strategy to improve place quality. However, limited research has explored how ground mural design may impact mental health. This study applied a 3 × 2 × 2 mixed design to explore how design features of sidewalk ground murals, specifically color (warm, cool, or achromatic) and pattern (rectilinear or curvilinear), influence mood states and perceived restorativeness of stressed or non-stressed individuals. Students (n = 112) were assigned into two groups, one with stress induction and the other without. They were asked to view images showing six design conditions and the uncolored condition. For each condition, mood states, including pleasure level, energetic arousal, and relaxation, were assessed using statements, along with perceived restorativeness as measured by the Perceived Restorativeness Scale—short version. The results reveal that presence of sidewalk murals improved mood states, including hedonic tone and energetic arousal, and perceived restorativeness compared to the uncolored sidewalk. Cool colors had the strongest effects in promoting a restorative experience, particularly for stressed subgroup. Warm colors significantly reduced relaxation across all participants and were perceived as less restorative for stressed individuals. Achromatic colors reduced energetic arousal and were perceived as the least restorative across all participants. Pattern features did not contribute to mood enhancement, but curvilinear patterns were perceived as more restorative than rectilinear patterns. This study provides empirical evidence to support urban public space design aiming to benefit mental health through ground murals with a more systematic color and pattern use.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-09T05:04:16Z
      DOI: 10.1177/23998083241272100
       
  • Land-use efficiency and local government revenue: Evidence from 272
           Chinese cities using a novel structural equation modelling approach

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      Authors: Tianyuan Wang, Li Wan, Helen XH Bao
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The unprecedented urbanisation observed in leading developing countries has placed immense pressure on effective and efficient land management. The significance of land-use efficiency in the Chinese context has been addressed in the literature, particularly on the measurements of land-use efficiency and key influencing factors. However, quantifying the interdependence between land-use efficiency, local government revenue, employment and infrastructure development whilst controlling for significant cross-city differences remains a gap in the literature. Based on data for 272 prefecture-level Chinese cities between 2012 and 2017, this study employs a novel modelling approach, combining latent class analysis (LCA) in a generalised structural equation model. The incorporation of LCA helps to control for the significant, non-linear heterogeneity across city samples. The empirical model identifies both the direct (one-off land conveyance fee and transaction-related tax revenue from land transactions) and indirect (corporate and personal taxes generated from employment and business growth) channels, through which land development contributes to local government revenue. It also provides one of the first quantified evidence, confirming that employment growth provides higher long-term return than a one-off, land conveyance fee to government revenue in China, controlling for significant cross-city heterogeneity in land-use efficiency and wage.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-09T04:21:59Z
      DOI: 10.1177/23998083241272092
       
  • Beyond the backyard: Unraveling the geographies of citizens’ engagement
           in digital participatory planning

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      Authors: Anna Kajosaari, Martina Schorn, Kamyar Hasanzadeh, Tiina Rinne, Saana Rossi, Marketta Kyttä
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Despite the emergence of virtual spaces as arenas for public participation, the geographies of digital participation have gained relatively little attention. Besides considering who participates and why, there is an evident gap in research considering the spatial relationships between the participants of digital urban planning processes and the spaces that are the subject of their participation. This paper proposes a working concept of the spatiality of participation that distinguishes between the spaces in which participation occurs, the spatial realities of the participants, and the spaces as objects of participatory planning. Relationships between these dimensions are investigated empirically with a Public Participation GIS study set in Espoo, Finland, involving 1,731 citizens and over 6,800 future planning and development ideas mapped across the city. The results of the study support prior research observing that e-participation has the potential to spatially expand participation processes both in terms of the involved public and the spatial knowledge they produce. However, our results also show that online participation may capture spatial ties between people and places that differ from those of traditional participation modes, ranging from place-protective behaviors close to the residential location to more casual spatial attachments.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-08T10:07:02Z
      DOI: 10.1177/23998083241271460
       
  • Unraveling the mystery of urban expansion in the Guangdong-Hong Kong-Macao
           Greater Bay Area: Exploring the crucial role of regional cooperation

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      Authors: Xianchun Zhang, Yucheng Zou, Chang Xia, Ya’nan Lu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Existing scholarship extensively explores the dynamics, determinants, and consequences of urban expansion, yet there is scant literature examining the impact of regional cooperation upon the directions and spatial forms of urban expansion amidst the fast-urbanizing process. This study focuses on the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a developed megacity-region in southern China, to probe whether the notable urban expansion observed in contemporary China has been profoundly influenced by collaborative efforts among jurisdictions. Through the spatial metrics and panel data regression spanning the period from 2010 to 2018, this study unveils that regional cooperation has extended from coastal cities towards hinterland cities within the GBA. Consequently, urban land in most cities has undergone expansion in diverse directions. Furthermore, in contrast to economic and social cooperation, regional institutional cooperation emerges as the most influential factor driving external urban expansion. Additionally, heterogeneous results reveal that regional cooperation drives the external expansion of ordinary cities towards core cities. In contrast, the inertia within the urban system demonstrates strong path dependence on the pattern of adjacent expansion, contrasting with the external expansion facilitated by regional cooperation. In summary, this study illuminates the genesis and dynamics of urban expansion amid the city-regionalization process, going beyond interpretations confined to the municipal scale.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-07T09:25:01Z
      DOI: 10.1177/23998083241272705
       
  • Dynamic changes of food environment: In and out of COVID-19 pandemic

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      Authors: Zhiying Lu, Yang Yang, Danlin Ou, Dazhi Gu
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The outbreak of the COVID-19 pandemic has precipitated food crises worldwide, prompting a re-examination of the resilience of the urban food environment. While previous research on the urban food environment has predominantly focused on Western contexts, scant attention has been given to China. This study takes Shenzhen, China as an example to establish a food environment evaluation framework centered on accessibility, diversity, and healthiness factors, aiming to analyze the dynamic changes of the food environment during normal and pandemic periods. By using the GA optimization algorithm, some convenience stores are transformed into self-pickup points (SPPs), which is expected to eliminate the deserts risk areas (DRAs) with low cost and high efficiency. The findings reveal a distinctive “center-periphery” spatial structure characterizing the food environment in Shenzhen, and the improvement of healthiness plays a crucial role in sustaining food oases and ameliorating food swamps. This research provides methods for improving the resilience of the food environment during the pandemic across diverse nations, bolstering the security of urban lifeline systems.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-06T07:06:11Z
      DOI: 10.1177/23998083241272101
       
  • Quantifying the effects of Singapore’s street configurations on
           people’s activity spaces

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      Authors: Anirudh Govind, Ate Poorthuis, Ben Derudder
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Although it is generally accepted that street configurations may influence people’s intra-urban travel, capturing the exact nature of that influence remains challenging. We frame this challenge as one of operationalization and measurement and attempt to quantify and analyze the impact of street configurations more precisely. We draw on geographic data science tools to suggest that street configurations may be captured using catchment area polygons. To illustrate our approach, we derive these polygons for every building in Singapore and show that catchment area sizes spatially cluster, thus acting as proxies for street configurations. Using a spatial error model, we demonstrate that these catchment area sizes partially explain people’s intra-urban travel, conceptualized as their activity spaces. That is, as street configurations lead to larger catchment areas, people’s activity spaces tend to shrink. We show that the explanatory power of catchment area sizes is distinct from, albeit correlated with, other built environment variables (such as amenity density and land use diversity) typically used to explain people’s travel. We conclude by considering the potential of our approach in broader urban geographical research agendas drawing on street configurations and other morphological influences in the study of socio-spatial processes.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-05T04:08:04Z
      DOI: 10.1177/23998083241272093
       
  • NorDark-DT: A digital twin for urban lighting infrastructure planning and
           analysis

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      Authors: Léo Leplat, Claudia López-Alfaro, Arne Styve, Ricardo da Silva Torres
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The implementation of sustainable urban lighting infrastructure is of paramount importance to promote healthy habits, mitigate the impact of light pollution on humans and wildlife, and balance out energy consumption. However, the analysis of alternatives for implementing lighting interventions in urban spaces is a laborious and time-consuming task, often involving the use of multiple tools. Also, the design of lighting infrastructure often demands a balance of conflicting needs and variables (e.g., aesthetics, human perception, impact on wildlife, and energy consumption). In this paper, we introduce NorDark-DT, an urban digital twin to support urban lighting infrastructure planning and analysis. We present the main requirements addressed in its design and development, its architecture and components, and illustrate its use in compelling usage scenarios related to the assessment of lighting intervention options in two study areas in Ålesund (Norway) and Uppsala (Sweden). We also discuss challenges and lessons learned during the development of NorDark-DT, providing valuable insights to developers, stakeholders, and practitioners interested in the creation of urban digital twins or similar tools.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-05T03:43:46Z
      DOI: 10.1177/23998083241272099
       
  • Text mining public feedback on urban densification plan change in
           Hamilton, New Zealand

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      Authors: Xinyu Fu, Catherine Brinkley, Thomas W Sanchez, Chaosu Li
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Cities worldwide are commonly aspiring to transition from inefficient urban sprawl patterns to more compact and sustainable urban forms. However, urban densification efforts often face significant public resistance or skepticism, hindering at-scale implementation. There is a scarcity of empirical studies identifying the rationale and mechanisms underpinning public opposition to urban density. This study aims to bridge this gap by leveraging novel natural language processing techniques (NLP), combined with mixed-methods analysis of a unique, highly detailed public dataset on urban intensification in Hamilton. This research stands out by proposing a transferable model for rapidly generating insights from large public feedback datasets, and also unveils the polarized and complex, self-interest-driven mechanisms, including NIMBYism (Not In My Back Yard), behind public support or opposition to urban densification. NLP techniques, such as sentiment analysis, topic modeling, and ChatGPT, can be used to offer rapid insights into a large, unstructured public feedback dataset. When combined with submitters’ individual interest representation and identifies, these AI-generated summaries can offer important insights into the hidden rationales behind public opinions, and, more importantly, be used to design tailored public engagement activities to obtain community buy-in.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-08-02T09:56:14Z
      DOI: 10.1177/23998083241272097
       
  • Identifying Urban functional regions: A multi-dimensional framework
           approach integrating metro smart card data and car-hailing data

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      Authors: Yuling Xie, Xiao Fu, Yi Long, Mingyang Pei
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Urban functions often diverge from initial planning due to changes driven by residents’ behaviors. Effective urban planning and renewal require accurately identifying urban functional regions based on residents’ behavior data (including activity and travel data). However, previous methods have primarily relied on either point of interest (POI) data or a single source of traffic data, and often ignore the combined influence of residents’ activities and travel behaviors. In this study, we introduce a novel framework that integrates multiple sources of traffic data (such as metro smart card data and car-hailing data) with POI data to identify urban functional regions. This approach is unique because it simultaneously considers two critical dimensions of residents’ behavior: travel and activity behaviors. By combining these dimensions, we extract a comprehensive set of characteristics, including travel time, travel flow, origin-destination patterns, activity types, and activity time, which are then aggregated at the regional level (i.e., traffic analysis zone). To process these characteristics, we use latent Dirichlet allocation (LDA) to extract high-level semantic features from each data type. Additionally, to handle the sparse data from metro smart cards, we employ a specialized clustering technique. The integration of diverse and complementary information from multiple data sources enables more accurate and nuanced identification of urban functional regions than single data source and k-means clustering algorithm, providing valuable insights for urban planners.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-07-30T09:45:19Z
      DOI: 10.1177/23998083241267370
       
  • Accessibility Score – Data analytics for the holistic assessment of
           urban mobility networks and the case of Braunschweig

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      Authors: Olaf Mumm, Majd Murad, Vanessa Miriam Carlow
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The accessibility and quality of urban mobility networks (UMN) depend on a multitude of static and dynamic conditions for each individual. Promoting sustainable mobility, such as walking, requires a very specific assessment of UMN’s qualities given the specific needs of pedestrians. The objective of this research is to provide a new approach for the comprehensive, mode-specific understanding of a UMN as a base for good planning and decision making. With the Accessibility Score (AccessS), we propose an integrated, indicator-based, holistic geospatial framework for the quantified assessment of qualitative UMN attributes identified in an extensive literature review.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-07-24T12:35:45Z
      DOI: 10.1177/23998083241261100
       
  • Does a compact city really reduce consumption-based carbon emissions'
           The case of South Korea

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      Authors: Hansol Mun, Jaeweon Yeom, Jiwoon Oh, Juchul Jung
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Evidence to prove that compact cities, the core of smart growth strategies, are the vision for carbon-neutral cities has been insufficiently explored because analyses have not distinguished between production- and consumption-based carbon emissions. Empirically analyzing the relationship with compact cities by estimating the final demand and investigating carbon emissions generated from the consumption of goods is essential. This study estimated consumption-based carbon emissions in South Korea using nighttime satellite imagery. Subsequently, using spatial analysis, K-means clustering analysis, and a regression model, we comprehensively confirmed whether a compact city to reduce consumption-based carbon emissions should be pursued. The results showed that (1) based on the clustering analysis, consumption-based carbon emissions were the lowest in clusters with the most desirable development form from a compact city perspective; and (2) the OLS regression analysis showed that the higher the complex land use (diversity), population density (density), congestion frequency intensity (transit access), green area ratio (environment), and agricultural area ratio (environment), the lower the consumption-based carbon emissions. However, the results confirmed that the greater the Vehicle Kilometers Traveled (street accessibility) and the poorer the accessibility of high-speed rail, the higher the consumption-based carbon emissions. Therefore, we recommend pursuing a compact city to reduce consumption-based carbon emissions.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-07-24T09:58:11Z
      DOI: 10.1177/23998083241263898
       
  • Packaging code and data for reproducible research: A case study of journey
           time statistics

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      Authors: Federico Botta, Robin Lovelace, Laura Gilbert, Arthur Turrell
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The effective and ethical use of data to inform decision-making offers huge value to the public sector, especially when delivered by transparent, reproducible, and robust data processing workflows. One way that governments are unlocking this value is through making their data publicly available, allowing more people and organisations to derive insights. However, open data is not enough in many cases: publicly available datasets need to be accessible in an analysis-ready form from popular data science tools, such as R and Python, for them to realise their full potential. This paper explores ways to maximise the impact of open data with reference to a case study of packaging code to facilitate reproducible analysis. We present the jtstats project, which consists of a main Python package, and a smaller R version, for importing, processing, and visualising large and complex datasets representing journey times, for many transport modes and trip purposes at multiple geographic levels, released by the UK Department for Transport (DfT). jtstats shows how domain specific packages can enable reproducible research within the public sector and beyond, saving duplicated effort and reducing the risks of errors from repeated analyses. We hope that the jtstats project inspires others, particularly those in the public sector, to add value to their data sets by making them more accessible.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-07-24T09:11:51Z
      DOI: 10.1177/23998083241267331
       
  • About positive and negative synergies of social projects: Treating
           correlation in participatory value evaluation

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      Authors: Francisco J Bahamonde-Birke, Niek Mouter
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      Participatory value evaluation (PVE) is a novel method aiming at the evaluation of projects from a societal perspective. It aims at establishing which investment projects or investment portfolios (with a portfolio containing multiple investment projects) are likely to be favored by the population, given a limited budget. The approach emulates the decision-making problem faced by policy-makers. The ultimate end of PVE is to evaluate and establish how individuals value attributes of public projects in order to construct social trade-offs between different attributes and investments projects. However, it is important to consider that when investment portfolios consist of more than one investment project, significant synergies (positive and negative) may exist among the projects. This paper proposes a new evaluation framework that allows addressing synergies among projects in the context of PVE, while also offering a highly flexible structure. The approach is tested making use of one synthetic and two real datasets. Results show that neglecting synergies among the utilities of the projects included in the chosen portfolio majorly reduces the model fit and biases the estimators.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-07-21T10:17:39Z
      DOI: 10.1177/23998083241264321
       
  • Contiguity of underutilized lands: Dynamic simulation taking their
           temporary uses into account

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      Authors: Kanta Sayuda, Hiroyuki Usui, Yasushi Asami, Kimihiro Hino
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      In Japan, shrinking densely built-up cities face the dual issue of lacking open spaces and increasing underutilized lands, such as vacant lots, lots with vacant houses, and parking lots. These unused land patches can be temporarily repurposed as open spaces for evacuation and recreation. However, identifying such clump is methodologically challenging. To address this issue, lot geometry is utilized. The study thus aims to investigate the frequency and size of contiguous underutilized lands, called the contiguity of underutilized lands, at a specific time point and under their temporary uses. A densely built-up area in Kobe city, Japan, was selected for the empirical case study. A comparison with simulation results shows that the observed static contiguity of underutilized lands tends to be more substantial than a uniformly random distribution. It shows a certain feasibility of a temporary use policy conducted in the case site. Specifically, when considering the temporary uses of underutilized lands, the maximum area of contiguous temporary open spaces is 583 m2, meeting the area requirement for a redevelopment project in Kobe. Utilizing parking lots can further extend the maximum area up to 945 m2. Nevertheless, policy makers need to promote the joint development of privately owned lots facing a wide roadway, as these are unlikely to become temporary open spaces. This study contributes not only to providing new methods for land use change simulation using lot geometry to analyse the contiguity of underutilized lands under their temporariness but also to demonstrating the feasibility and limitations of a temporary use policy.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-07-21T05:54:22Z
      DOI: 10.1177/23998083241265735
       
  • A 3D agent-based model for simulating urban densification in Toronto,
           Canada

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      Authors: Richard Burke, Raja Sengupta, Alistair Ford
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      The use of land parcel data, 3D visualisation and urban theories offers a significant opportunity for advancing simulations of urban densification. This paper presents a 3D agent-based model (ABM) to explore future urban densification dynamics in Toronto based on stakeholder behaviour and interactions, the impact of zoning regulations, and profit expectations. The ABM establishes residents, developers, landowners, and the local zoning authority as primary actors involved in urban densification. This model replicates the Toronto urban development process through a structured framework of submodels which represent different stages of this process, based on the literature and gentrification theories. Three different scenarios are developed which show the city is projected to experience between 46 and 98 new developments by the year 2040. Average building height could increase by 17% to 56%, and the city could have 10,238 to 25,070 new units to meet future population demand. These simulations characterise Toronto’s future capacity for urban densification, realise the levels of densification required to meet Toronto’s growing population, and ultimately provide a more comprehensive understanding of the city’s future transformation.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-06-21T08:54:11Z
      DOI: 10.1177/23998083241261762
       
  • “MAPPING PUBLIC SPACE MICRO-OCCUPATIONS: Drone-Driven Predictions of
           Spatial Behaviors in Carapungo, Quito”

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      Authors: Víctor Cano-Ciborro, Ana Medina, Alejandro Burgueño, Mario González-Rodríguez, Daniel Díaz, María Rosa Zambrano
      Abstract: Environment and Planning B: Urban Analytics and City Science, Ahead of Print.
      This study evaluates the spatial behavior of an intermodal transportation hub in Carapungo, one of the densest neighborhoods in Quito, Ecuador. This public infrastructure is deficient and lacks adequate equipment for the people who use, occupy, and transit within and around it, as well as for the numerous activities that occur, particularly at Carapungo’s Entry Park. Traditional methods for analyzing urban dynamics and land use are typically rigid and fail to grasp the complex and nonlinear nature of public spaces, especially in informal Global South cities. However, recent advancements in Artificial Intelligence and Machine Learning, combined with aerial drone videos, have enabled the modeling and prediction of urban dynamics beyond state regulations and formal planning. In this context, we developed a model using Computer Vision Technology and the YOLOv5 algorithm, incorporating Deep Learning training. The objective is twofold: firstly, to detect people, their movement and speed; and secondly, to produce “Occupancy” and “Count & Speed” cartographies that highlight commuters’ spatial patterns. These situated cartographies provide valuable insights into urban design, mobility, and interaction within a conflicted public space’s-built environment. The generated data offer planners and policymakers quantitative spatial information to consider local practices and dynamics in urban planning, particularly in situations of informality and insufficient urban infrastructure.
      Citation: Environment and Planning B: Urban Analytics and City Science
      PubDate: 2024-06-20T11:19:06Z
      DOI: 10.1177/23998083241262548
       
 
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School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
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