“EVALUATION OF HUNSUR CITY URBAN EXPANSION USING PYTHON BASED GIS MODELING”

Abstract

 

Urban expansion in rapidly developing tier two cities poses a critical challenge to sustainable land management and ecological stability. This study evaluates the spatio temporal dynamics of urban growth and its environmental impacts in Hunsur City, Mysuru District, Karnataka, over a 30 year period from 1990 to 2020. Utilizing an integrated approach combining Remote Sensing (RS), Geographic Information System (GIS) tools and Python based computational modeling the research analyzes multi decadal changes in Land Use and Land Cover (LULC). Landsat satellite imagery (Landsat 8-9 OLI/TIRS Collection 2 Level 2) for the years 1990, 2000, 2010 and 2020 was processed using supervised classification techniques in ArcGIS to map built-up area transitions. To capture the spatial pattern and directional intensity of outward urban sprawl, a multi-ring buffer analysis was executed at 0.5 km concentric intervals extending up to 3.5 km from the city centre. Python programming libraries, including rasterio, pandas and matplotlib were used to quantify pixel-level urban expansion metrics map decade wise annual growth rates and generate logical raster change detection maps saved as spatial GeoTIFFs.