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Spatial Information Research
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  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2366-3286 - ISSN (Online) 2366-3294
Published by Springer-Verlag Homepage  [2351 journals]
  • Tree cover percent investigation with respect to geographical area,
           vegetation types, agro ecological regions and in agriculture landscape of
           India: a geospatial approach
    • Abstract: This study has utilized the remote sensing and GIS datasets such as tree cover, harmonized land cover, agriculture mask and ancillary source of India for better comprehension of tree cover percent distribution in geographical territory/vegetation classes/agro-ecological zones/agriculture landscapes. The study revealed in the year 2000 the forest area in India was 15.4% of the total geographical area. Furthermore, the total agriculture area in India (including single/double/continuous/rainfed area) for the year 2000 was found 63% of the total geographical area and approximately 10% of the agriculture land retains at least 10% of tree cover which is roughly one-fourth of the total global average. The mean tree cover distribution in various vegetation types was found highest (76.4%) in the category of “Tropical and sub-tropical mountain forests, broadleaved, evergreen > 1000 m”. The vegetation category “Tropical mixed deciduous and dry deciduous forests” occupied high area percent (14.4%) and showed significantly low mean tree cover percent (15.1%). The tree cover percent analysis in various agro-ecological zones of India showed high mean tree cover in those zones where the rainfall is significantly high and soil fertility is adequate such as the categories “North Eastern Hills” (62.5%), “Eastern Himalayas” (60.0%) and “Western Ghats and Coastal Plain” (30.70%).
      PubDate: 2019-03-20
       
  • Examining the impact of regional land use and land cover changes on
           temperature: the case of Eastern India
    • Abstract: This study investigates the temperature trend (warming or cooling) over Eastern India during the period 1981–2006 and its response to the changes in land use and land cover (LULC). The ‘Observation minus Reanalysis’ (OMR) method is used to investigate the LULC impact on the temperatures over the region. We find that the Eastern India got warmer at a rate of 0.077 °C per decade during 1981–2006 and the changes in LULC contributed towards warming during 1991–2006 at a rate of ~ 0.2 °C per decade. We investigated the LULC changes during the period 1981–2006 over Eastern India by using satellite datasets for four different time periods viz. 1981, 1991, 2001, and 2006. Results indicate that shrubs/small vegetations, agricultural/fallow land and open forest are increased by 0.15%, 0.1% and 0.07% respectively over Eastern India during the period 1981–2006. On the other hand, bare land/snow cover and dense forest are decreased by 0.23% and 0.09% respectively over the region. Overall results indicate that the cooling is due to the conversion of open forest/shrubs/small vegetation into dense forest/agricultural/fallow land and the warming is due to the conversions of shrubs/agricultural/fallow land into bare land.
      PubDate: 2019-03-19
       
  • Change detection in urban landscapes: a tensor factorization approach
    • Abstract: Analysis of urban landscape has been an interesting research challenge for decades. The advent of machine learning and data mining techniques have geared the problem from simple analysis of data to knowledge discovery from data. This work attempts to mine urban landscapes to find the change pattern which has happened over the region for a period of interest. The work proposes a spatiotemporal-metric miner, which uses the spatial, temporal and landscape metric data to discover the change that has occurred in a region. The model works on a hierarchical basis, wherein, the regions of interest are chosen in a landscape and are aggregated to find the change that has happened over the entire region. The entire model is built by taking advantage of the tensorized representation of data, and thus resulting in the effective mining of tensors. The growth of a landscape is evaluated regarding two parameters, namely, Inter-class Growth Index and Intra-class Growth Index. Experiments are performed on the landscape regions of Indian cities, and a ranking of cities is presented based on the growth indices, which are validated against standards. In the experiments, Jaipur city showed the highest Inter-class Growth Index value of 2.68 and Surat city had an Intra-class Growth Index of 0.78.
      PubDate: 2019-03-16
       
  • Soil survey to support land use/land cover planning in BPS and BPM region
           in Gangajalghati block, West Bengal, India
    • Abstract: To secure food and other associated need for growing population, the only way is to increase agricultural production and to utilize the land with respect to its potentiality in a sustainable way. In the present study an attempt has been made to evaluate sustainable land use/land cover planning in Buried Pediment Shallow (BPS) and Buried Pediment Medium (BPM) region in Gangajalghati block, Bankura district, India using remote sensing and GIS techniques. BPS consists of weathered and unconsolidated materials with thin soil cover (0–5 m) mainly sand mixed with silt and clay. BPM consists of gently sloping dissected topography with shallow to deep soil profile (5–20 m) which are characterised by severely eroded, coarse textured, stoniness and acidic soils. Ruggedness of the topography, scarcity of water, soil acidity (pH 5–6) and soil erosion are the key problems in this area, which hampers the productivity of the land. Hence these soils have very low moisture holding capacity and very low nutrient status. To overcome these problems, different thematic maps are taken into consideration for recommendation of land use/land cover planning in this area. This study will facilitate enhancement of agricultural productivity in a sustainable manner and restoration of ecological balance between degraded and rain fed ecosystems.
      PubDate: 2019-03-11
       
  • Improving the performance of location based spatial textual query
           processing using distributed strip index
    • Abstract: Location Based Services are information retrieval services that offer accurate information required by the end user. These services are the query based services accessed mainly through mobile devices and have number of uses in social networking for providing entertainment, business and healthcare information. In health care system, if a person wants to get immediate medical help at any place, he needs to access a medical database with the help of location-based query. Sometimes, location-based query can associate with the text information, such as the user wants to find the nearest hospital with the facility of pharmacy or ambulance. This type of query has to resolve both location and textual information. This paper proposes a new distributed index structure to resolve location-based query, and introduces a new probabilistic mechanism to correct the typographical errors when retrieving the documents. The experimental results show that the distributed strip index structure produces better performance than the existing distributed R tree structure.
      PubDate: 2019-03-09
       
  • Analyzing the risk related to climate change attributes and their impact,
           a step towards climate-smart village (CSV): a geospatial approach to bring
           geoponics sustainability in India
    • Abstract: The paper deals with various thematic parameters such as agriculture crop scenario (2000, 2010), water stress, precipitation trend and deficit, climate-induced risk towards crops, drought-prone area, suicide attributes of farmers, agro-ecological regions, prediction of future (2050) precipitation and temperature variation during kharif and rabi seasons of India and their spatial pattern were analyzed in GIS for better understanding of climate change. The analysis revealed about the need of synergic approach/strategies to address the impact of climate change. Few of the Climate-smart villages (CSVs) projects of India were discussed here based on their approach, achievement, and limitation. The CSV conceptual strategies are fully based on climate smart agriculture potentiality to achieve sustainability in food security, enhancing the livelihood, eradication of poverty and magnifying the farm household resilience. The climate-induced high and very high risk to the crops areas were found dominated in the arid and semi-arid regions which will be challenged in future due to water stress, inadequate irrigation facility, increasing trend of temperature and variation in precipitation pattern. The hotspot districts of farmer’s suicide were very significant in climate-induced very high risk zone and majority of them falls in the drought-prone areas/extremely high to high water-stressed areas which leads to crop failure. There is a need to formulate a concrete policy, legal, and institutional actions addressing the farmers problem significantly at country, state, district and village levels which will support investment/technology/guideline in and adoption of Climate-smart village (CSV) practices after seeing the socio-economic background (poverty/tribes/backward class) of them.
      PubDate: 2019-03-09
       
  • Information value based landslide susceptibility zonation of Dharamshala
           region, northwestern Himalaya, India
    • Abstract: This study investigates the application of statistical information value method (In V) for landslide susceptibility zonation of Dharamshala region, Kangra valley of Himachal Pradesh, India. The study area witnesses a number of landslides due to the prevailing factors such as slope angle, aspect, lithology, soil type, land use pattern, drainage density, and fault density. A landslide inventory map was prepared for the study area to understand the spatial distribution of landslides and their correlation with the prevailing causal factors. The mapped landslides covered an area of approximately 1.1 km2 (landslide training data 0.66 km2 and testing data 0.44 km2) out of the total study area (39.3 km2). Degree of correlation of the causal factors with the mapped landslides was inferred using the bivariate statistical information value (In V) method. The results show that, VHS zone has 0.65 km2 landslide affected area whereas, the HS zone has 0.01 km2 landslide affected area which means that the complete landslide training data (0.66 km2) falls in the HS and VHS zones. The performance of the landslide susceptibility zonation map for predicting the future landslide events was inferred based on the prediction rate curve which gave 0.96 area under curve value.
      PubDate: 2019-03-06
       
  • Give-And-Take heuristic model to political redistricting problems
    • Abstract: Political redistricting is a process used to redraw political boundaries based on a number of criteria that include demographic criteria (e.g. population equality and minority representation) and geographic criteria (e.g. contiguity and compactness). Redistricting can be highly controversial because it is possible that the drafters can be involved in the decision making where to draw political boundaries. The use of computers in political redistricting can remove several factors such as intentions of the decision makers or the majority in political views or race from the redistricting process. The main purpose of this paper is to develop a heuristic approach called Give-And-Take Greedy model in order to solve large scale political redistricting problem with respect to a strict population equality and contiguity. The heuristic follows the basic greedy concept to accept a best solution every iteration. The distinctive concept of the heuristic is to exchange or swapping population units within specified districts as well as to use the more efficient contiguity checking method. The computational results from Give-And-Take greedy heuristic can successfully be applied to real redistricting plans, especially for a congressional redistricting in the United States in satisfying with a strict equal population.
      PubDate: 2019-03-02
       
  • Relationship between groundwater quality and distance to fault using
           adaptive neuro fuzzy inference system (ANFIS) and geostatistical methods
           (case study: North of Fars Province)
    • Abstract: The aim of this paper is to use Kriging (spherical, exponential, and Guassian models) and Inverse distance weighted (IDW) methods to prepare the water quality map. In addition, the relationship between water quality and distance to fault is determined in northeast of Fars province, Iran. Adaptive neuro fuzzy inference system method is also used to predict groundwater quality. The measured Sodium adsorption ratio and electrical conductivity parameters that are obtained from 384 wells in 2005 to 2014 are utilized to determine groundwater quality. The results show that the Kriging method (spherical model) has a higher accuracy with lower RMSE value than IDW method. Thereafter, this model is used to prepare the interpolation maps. Moreover, the results indicate the hybrid model in terms of maximum R2 and the minimum error is suitable enough to predict water quality parameters. In addition, the results depict by increasing the number of fault, the groundwater quality is decreased and vice versa.
      PubDate: 2019-02-26
       
  • Calculation of area, mapping and vulnerability assessment of a
           geomorphosite from GPS survey and high resolution Google Earth satellite
           image: a study in Mama Bhagne Pahar, Dubrajpur C. D. block, Birbhum
           district, West Bengal
    • Abstract: Geomorphosites are the geomorphological landforms that have scientific, cultural, aesthetic and socio-economic values due to human perception. Mama Bhagne Pahar is one of the ancient geomorphosites in West Bengal which has specific and unique geomorphic characteristics than its surrounding area. Now a days, Global Positioning System (GPS) has become a standard surveying technique due to its accuracy and effectiveness. In the present study, perimeter and area of Mama Bhagne Pahar has been calculated from the data collected from GPS survey. Here, principle of Pythagorean theorem has been applied to calculate the perimeter of Mama Bhagne Pahar and calculation of area has been done by applying Coordinate method. Finally, vulnerability of the study area has been assessed using both qualitative and quantitative approaches. In this respect, a map showing encroachment of Mama Bhagne Pahar by human settlements has been prepared by using data collected from GPS survey coupled with high resolution Google Earth satellite image with the help of Arc GIS software.
      PubDate: 2019-02-25
       
  • Morphometric analysis and the validity of Hortonian postulations in
           Anambra drainage basin, Nigeria
    • Abstract: Anambra drainage basin is decimated by a plethora of rivers emanating from heavy rainfall and fluvio-geomorphic surface processes. Apparently, hydrologic and sedimentologic processes influences basin form and processes which are governed by laws of drainage basin composition postulated by Horton. Metrical dimension provides linearity, topographic and area variables used to validate Horton’s postulates in the Anambra drainage basin. Topographic tools and ARC GIS 10.2 were utilized. The stream number, length and areal quantities showed that the three laws of drainage basin composition postulated by Horton are valid. It is a 6th order dendritic pattern with elongated shape and coarse texture. The drainage density, stream frequency and infiltration number were with low values: 0.10, 0.10 and 0.27 respectively while the overland processes recorded 0.51, implying heavy dissection. The constant of channel maintenance is 0.99 km2. The relief characteristics indicated a low relief. The significance of the morphometric attributes of the Anambra drainage basin has a lot of implications in agricultural practice and erosion processes.
      PubDate: 2019-02-23
       
  • Analysis of long-term seasonal and annual temperature trends in North
           Bengal, India
    • Abstract: In the recent past, scientific modeling of climatic elements, in particular, temperature data has attained considerable importance as it affects many aspects of the environment and also indicates a clear sign of climate change. The temperature warming is mainly associated with the increasing concentration of greenhouse gases triggered by the land use and land cover changes. In the last century, exploitation of forest resource, population influx, and expansion of agricultural land has changed the natural landscape of North Bengal to a great extent. Thus the present study intends to find out long-term changes in maximum and minimum temperature for six northern districts of the state of West Bengal, popularly known as North Bengal. The non-parametric Mann–Kendall test and Theil-Sen’s slope estimator reveals the presence of warming trends in both maximum and minimum temperature. Annual temperature is rising 0.006 °C per year and 0.007 °C per year at most of the districts for the maximum and minimum temperature respectively. However, the seasonal analysis of trend exposes that post-monsoon and winter temperature rise are predominantly contributing to the upward annual trend. The highest increasing trend in maximum and minimum temperature is observed at Malda (0.013 °C per year) in the post-monsoon and winter season respectively. Except the post-monsoon season, the minimum temperature is rising rapidly than maximum temperature across the region. Additionally, Sequential Mann–Kendall test exhibits the periodic fluctuation of trends, which are more prominent in pre-monsoon and monsoon season.
      PubDate: 2019-02-14
       
  • Geo-spatial perspective of vegetation health evaluation and climate change
           scenario in India
    • Abstract: Vegetation health of any ecosystem and changes in it are vital in global change in ecology and it is delicately linked to climate change. This study evaluated the spatial patterns of significant negative change trend using composite NOAA-AVHRR data time series (1982–2006), long term forest fire point data, invasive hotspot data and predicted climate anomalies data over the different harmonized landcover categories of India. Around 65% of Indian forest shows the trend of negative change. Significant negative change were found to be highest (203,026 km2) over ‘Tropical mixed deciduous and dry deciduous forests’ category, followed by ‘Tropical lowland forests, broadleaved, evergreen’ (81,555 km2) and ‘Evergreen shrubland & regrowth/Abandoned shifting cultivation/Extensive shifting cultivation’ (55,811 km2). Around 85% of Indian biodiversity hotspot showed the negative change. The analysis of forest fire revealed the ‘Tropical mixed deciduous and dry deciduous forests’ retained the highest forest fire percentage (40%). The prediction of temperature anomalies for the year 2030 using RCP 4.5 model showed the increase in the temperature in the range of 0.58–1.32 °C and was found highest in northern part of India. Similarly, the rainfall prediction for the year 2030 showed rainfall deficit in several states of India. The outcomes of the present study would help in prioritization of various vegetation types suffering from anthropogenic and natural disturbances and will guide the policymakers to safeguard, prioritized forest areas for effective conservation, scientific protection and climate change mitigation endeavors.
      PubDate: 2019-02-14
       
  • Hierarchical anomalies in drainage network: a case study from Western
           Ghats, South India
    • Abstract: The Chalakudy river, a seventh order tropical drainage system emerging from the Western Ghats is flowing through the Southern Granulite Terrain of Peninsular India. Anomalies in the hierarchical organization of drainage networks reflect the effects of anthropogenic interferences and structural controls in the development of a drainage basin. The anomalies in the drainage composition are determined from bifurcation index, hierarchical parameters and stream gradient index. Computation of drainage indices is carried out with the aid of vectorized data derived from Survey of India (SOI) open series topo maps and Shuttle Radar Topographic Mission (SRTM) data (3Arc resolution) using ArcGIS 10.4 software. Here we discuss the quantitative methodology to determine the hierarchical anomaly index, hierarchical anomaly density and hierarchical anomaly number of drainage basin from geospatial data with an attempt to infer the degree of geomorphic evolution of the sub-basins from the analysis. The sub-basins are in their mature to the late mature stages of geomorphic evolution. It is observed that the tectonically induced diffusive process and anthropogenic interferences in the drainage basin altered the hierarchical organization of drainage network of Chalakudy river basin.
      PubDate: 2019-02-13
       
  • Development of optimal routing service for emergency scenarios using
           pgRouting and FOSS4G
    • Abstract: This study aims to implement a system for Emergency Routing Decision Planning (ERDP) based on Service Oriented Architecture. A Web-based system is implemented to facilitate ubiquitous dynamic routing services on up-to-date road network data. Integration of Dijkstra’s shortest path and Analytic Hierarchy Process (AHP) algorithms has facilitated improved weighted travel-time computation. Route computations are done considering situation at source, transit and destinations. The AHP is used to prioritize amongst possible destinations considering impedance factors affecting travel time. The routing algorithm is deployed as Web Processing Service (WPS) using the ZOO-Project Platform. Two scenarios for application of the ERDP Web services are demonstrated. In the first scenario of medical emergency, the ERDP computes routes between patient’s location, emergency car to hospital in proximity of accident site considering dynamic factors such as conditions of road network, the patient’s state and availability of medical facilities and expertise in the target hospital. In the second scenario of a disaster situation, the GRASS GIS r.sim.water simulation model for overland flow under excess rainfall conditions was integrated into the ERDP system as a WPS. The result of the simulation is used to automatically update the road network database and new routes are computed based on existing conditions. The system is developed using Free and Open Source Software for Geoinformatics (FOSS4G) stack and is amenable to customization to support other emergencies such as fire, debris flow and tsunami. Integration with Sensor Observation Services for automatic data updates from CCTV camera and weather stations could further improve utility as a real-time ERDP system.
      PubDate: 2019-02-13
       
  • Predicting the land use and land cover change using Markov model: A
           catchment level analysis of the Bhagirathi-Hugli River
    • Abstract: Land use and land cover are important biophysical factors which have a major role in different terrestrial processes on the earth. Land use and land cover change are a vital element of global environmental change. It is very essential for regional development and land use management towards sustainable development. The different time’s period satellite images in the study area have been studied to understand temporal as well as the spatial variability of land use and land cover (LULC) change. In this, an attempt was made to adopt the Markov model for obtaining and investigating the dynamics of land use change. Markov model was used as a stochastic model to make quantitative comparisons of the land-use changes between time periods extending from 2001 to 2010. Model performance was evaluated between the empirical LULC map obtained extracted from Landsat 8 (2017) image and the simulated LULC map obtained from the Markov model. The future land use distribution in the year 2019 and 2028 was acquired using a Markov model. This result shows that the Markov model and geospatial technology together are able to effectively capture the spatiotemporal trend in the landscape pattern in this study area.
      PubDate: 2019-02-11
       
  • Multi-scale object-based fuzzy classification for LULC mapping from
           optical satellite images
    • Abstract: In this paper, a multi-scale object-based fuzzy approach is demonstrated for land use/land cover (LULC) classification using high-resolution multi-spectral optical RapidEye and IKONOS images of Lao Cai and Can Tho areas in Vietnam respectively. Optimal threshold for segmentation procedure is selected from rate of change-local variance graph. Object-based fuzzy approach is implemented to identify LULC classes and LULC initial sets, and then the initial sets are classified to final LULC classes. In case of Lao Cai area, normalized difference vegetation index (NDVI), normalized difference water index (NDWI), water index (WI) in object-based are used to generated water, terrace field classes, and built-up and vegetation sets. NDVI, soil index (SI) and red band are used to distinguish built-up set to building, bare land and road classes. NDVI and RedEgde band are inputs to classify rice field and forest classes from vegetation set. In case of Can Tho area, NDWI and WI are generated to water, vegetation, paddy field classes and built-up set, and then built-up set is classified to building, bare land, road, and paddy field classes. The technique is able to create LULC maps of Lao Cai and Can Tho areas with (90.8%, 0.84), and (92.3%, 0.90) classification accuracy and kappa coefficient, correspondingly.
      PubDate: 2019-02-06
       
  • Assessment of geostatistical methods for spatiotemporal analysis of
           drought patterns in East Texas, USA
    • Abstract: Drought is one of the most complex and least understood climate-related natural hazards. Active drought mitigation and contingency plan formulation often require a reliable drought distribution map. This study analyzed different spatial interpolation techniques to produce drought distribution map in East Texas, USA. Deterministic [inverse distance weighting (IDW) and spline], and geostatistical [ordinary kriging (Gaussian (KG) and spherical (KS))] interpolation techniques were employed as candidate methods for evaluation. Thirty-four years (1980–2013) of weather station data (N = 47) were used to calculate a 12-month Standardized Precipitation Evaporation Index (SPEI). The dataset was randomly divided into test data (70%, N = 33) and validation data (30%, N = 14). The resulting SPEI maps were cross-checked and validated through a validation dataset by calculating error matrices. The results indicate that KG tends to perform well in relatively drier conditions while IDW shows mixed results, performing well both in dry and wet conditions. The overall power of the four techniques to map 12-month drought conditions resulted in the order of IDW > KG > KS > spline.
      PubDate: 2019-02-01
       
  • Geo-spatial approach with frequency ratio method in landslide
           susceptibility mapping in the Busu River catchment, Papua New Guinea
    • Abstract: With the exacerbated kinetic energy of high volume of flowing water, the middle and lower catchment zones of a rugged terrain often become more prone to landslide. Almost half of Lae city, the second largest city in Papua New Guinea falling in the lower end of the catchment remains variably vulnerable to landslides. The study deliberates on the mapping of landslide sustainability, utilizing the geographical data sets such as terrain aspect and slope, land use land cover, site soil-geology, distance from river and distance from existing fault lines as input data for frequency ratio analysis culminating in delineation of susceptible landslide potential zones within the catchment area. The location of previous and recent landslide occurrence zones within the study region were identified and demarcated by dint of high resolution Google earth imagery complimented with the data gathered through field visit. All the thematic layers were prepared and organised for assignment of weights. The calculated frequency ratio values were assigned as weightage to each factor class. By using the weightage sum and raster calculator spatial analyst tool in ArcGIS 10.2.2 the results was generated. The result was then verified with known landslide occurrence and the cumulative % graph was constructed through calculated values. Furthermore the area under curve was calculated and validated with the ground truth information.
      PubDate: 2019-02-01
       
  • The impact of urban green areas on the surface thermal environment of a
           tropical city: a case study of Ibadan, Nigeria
    • Abstract: This study assesses the relative impact of green areas on the surface thermal characteristics of an urban area. From this study, the existence of the Park Cool Island (PCI) around the green areas and surrounding zones of the green area was noted, as surface temperatures were lower at the green areas and higher at the outer boundaries. Agodi gardens had the highest vegetation cover of 62.1% and was the area with the lowest mean surface temperature (26.79 °C), while Agugu green area had the lowest vegetation cover of 20.7% and had the highest mean surface temperature (27.75 °C). Green areas with higher vegetation cover percentages had higher rate of change of PCI with buffer distance compared to the other two green areas that had lower percentages of vegetation cover. The green areas were identified for their cooling roles on surface temperature within the urban centres of Ibadan as the surface temperature intensities were of the order of 1–2 °C lower within the 500-m buffer zone. The findings, therefore, brings to light the need for increased greenery within the urban areas of the city, and also provide information for urban planners and designers on the need for green spaces in mitigating heat island phenomenon in the city.
      PubDate: 2019-02-01
       
 
 
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