Simulating the Urban Growth using SLEUTH Model for modelling Urban Heat Island in Varanasi, India

This abstract has open access
Abstract Summary
Accelerating urban growth and land use/cover change sets increasing pressure on the natural environment and have become a global concern as these are believed to be responsible for the ecological degradation (biodiversity loss). With the increasing share of population residing in cities and enhanced demand of land resource, particularly in developing countries, the most intensive and dynamic human development activity has become the leading forces behind these changes. Due to intensive urban growth, built mass primarily of having high concentrations of anthropogenic activities have led to the development of urban microclimates (UMCs). The development of UMCs is allied with the urban heat island (UHI) phenomenon. Therefore, developing methods for assessing urban growth planning scenarios, analyzing environmental degradation, simulating urban expansion, regarding the future consequences for land use and the progress of current spatial plans and policies is important for urban-regional planners and decision makers. Studies from past demonstrates different models for analyzing urban growth using various algorithms, like cellular automata (CA) coupling with fuzzy logic, artificial neural network, Markov chain and SLEUTH. The simulation of urban growth through cellular automata models brings improved understanding of the complex dynamic process of land use change, which conventional models fails to analyze. Hence, the aim of this study is to simulate future urban expansion of Varanasi city from 2018 to 2030, using cellular automata method in SLEUTH model. The input data required by the model including Slope, Land use, Exclusion, Urban extent, Transportation and Hillshade are obtained from satellite images after supervised classification. This research uses the Landsat 8 and Landsat 5 data. Also, analyzing the correlation between Land Surface temperature (LST) and Normalized Difference Vegetative Index (NDVI) gives the overall scenario of temporal effect due to temperature increase on vegetation cover. The results of this study may be useful for planners and policy makers to implement preventative and governing factors in advance and make more informed strategic decisions.
Abstract ID :
ISO465
Submission Type
Student
,
Indian Institute of Technology (IIT) Kharagpur, India
Student
,
Indian Institute of Technology Kharagpur
Student
,
Indian Institute of Technology Kharagpur
Assistant Professor
,
Indian Institute of Technology Kharagpur
Head of the Department of Architecture and Regional Planning
,
Indian Institute of Technology Kharagpur
Professor & Chair, School of City and Regional Planning
,
Georgia Tech, Atlanta

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