Analysis of Land Use Land Cover Detection Using Remote Sensing and GIS of Coimbatore Region, Tamil Nadu

Abstract: The study's main aim is to analyze the land use changes of the Coimbatore Corporation for the period of 2017 and 2023. The temporal analysis was conducted using two satellite images and multiple vector data. ArcGIS Pro image classification and machine learning packages are used to capture building footprints and road networks. The satellite images are classified into four major classes: water, crops, trees, built-up, flooded vegetation, range land and bare land. Further, study shows that there was a major decreased in crops (-6.42%), bare land (-1.13%) and range land (-0.2%) and a major built up (4.81%), flooded vegetation (0.302%), water (1.14%) and trees (1.09%) has increased in land use from 2017-2023. The population growth increases the built area and this is the reason for the change of LULC classes. ArcGIS Pro ML-based segmentation and supervised classification method are used to classify images and capture vector data. The change detection of LULC analysis shows an increase in residential, commercial, and Industrial areas due to raid urbanization.