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All Journal Geoplanning : Journal of Geomatics and Planning
Chetan R. Patel
Singhania University
Earth & Planetary Sciences

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An Application of Cellular Automata (CA) and Markov Chain (MC) Model in Urban Growth Prediction: A case of Surat City, Gujarat, India Sheladiya, Kaushikkumar Prafulbhai; Patel, Chetan R.
Geoplanning: Journal of Geomatics and Planning Vol 10, No 1 (2023)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.10.1.23-36

Abstract

The main purpose of this study is to detect land use land cover change for 1990-2000, 2000-2010, and 2010-2020 using multispectral Landsat images as well as to simulate and predict urban growth of Surat city using Cellular Automata-based Markov Chain Model. Maximum likelihood supervise classification was used to generate LULC maps of the years 1990,2000,2010, and 2020 and the overall accuracy of these maps were 90%, 95%, 91.25%, and 96.25%, respectively. Two transition rules were commuted to predict the LULC of 2010 and 2020. For validation of these LULC maps, the Area Under Characteristics curve was used, and these maps' accuracy was 95.30% and 86.90%. This validation predicted LULC maps for the years 2035 and 2050. Transition rules of 2010-2035 showed that there will be a probability that 36.33% of vegetation area and 40.27% of the vacant land area will be transited into built-up by the year 2035, and it will be 49.20 % of the total area. Also, 57.77% of the vegetation area and 60.24% of the built-up area will be transformed into urban areas by the year 2050, almost 62.60 %. Analysis of LULC maps 2035 and 2050 exhibits that there will be abundant growth in all directions except the South Zone and Southwest Zone. Therefore, this study helps urban planners and decision-makers decide what to retain, where to plan for new development and type of development, what to connect, and what to protect in coming years.
Application of Remote Sensing and Geographic Information System in Identification of Urban Growth nodes: A Case of Surat City, India Sheladiya, Kaushikkumar Prafulbhai; Patel, Chetan R.
Geoplanning: Journal of Geomatics and Planning Vol 10, No 2 (2023)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.10.2.97-110

Abstract

With the passage of time, the city's growth behavior will not change unless and until the government intervenes, and thus its identity will shift from monocentric to polycentric to meet the needs of citizens. As a result, this study is being conducted to identify emerging growth nodes within a selected area of Surat City, as well as their growth drivers over a 30-year period. Quantified built-up area within a patch size of 1km x 1km was used to compute patch density at five-year intervals from 1991 to 2021. In addition, the spatial changes that occurred within patches over the same time period were examined. Both analyses aid in determining the emerging growth nodes over a 30-year period. From 1991 to 2021, the city was driven by socioeconomic criteria such as land price, availability of good health and educational facilities, water and sewerage networks, fire stations, proximity factors such as proximity to major roads, bridges, bus stations, metro, railway stations, airport, environmental factors such as the development of riverfront and linear park, bio-diversity park, and government interventions in terms of Town Planning Schemes. This study thus aids urban planners and decision-makers in selecting which growth nodes to plan for new development and type of development, what to connect, and what to protect in the years to come.
Co-Authors Sheladiya, Kaushikkumar Prafulbhai