1Undergraduate Student, School of Civil Engineering, Vellore Institute of Technology, Chennai, India
2Research Scholar, School of Civil Engineering, Vellore Institute of Technology, Chennai, India
3Professor, School of Civil Engineering, Vellore Institute of Technology, Chennai, India
4Associate Professor, Department of Civil Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India
5Associate Professor, School of Civil Engineering, Vellore Institute of Technology, Chennai, India
Online Published on 7 February, 2024.
The LULC changes play a pivotal role in explaining the spatial structure and dynamics of the Earth's landscape. The present study analyses LULC changes in the western Tamil Nadu districts of Coimbatore, Erode, the Nilgiris, and Tiruppur from 2000 to 2020, utilizing multispectral satellite imagery. In this study, Landsat imagery has been categorized into six LULC classes under the guidelines provided by the NRSC Level 1. These classes include built-up land, agricultural land, forest, grass/grazing land, wastelands, and water bodies. Landsat imagery is categorized into six LULC classes using supervised image classification, by employing Support Vector Machine techniques. The accuracy of the delineated LULC map is evaluated by Kappa statistics using the sample of 200 stratified randomly selected points obtained from Google Earth. Analysis of LULC shows significant changes in the study area, primarily attributable to the rapid increase in population, accompanied by industrialization and urbanization. Industrialization and urbanisation increase the built-up land by about 711 km2. Further, to meet the growing food demands of the increasing population, an additional 315 km2 of agricultural land has been generated. The analysis of LULC changes is of particular significance in the context of sustainable land and water resources management.
LULC change, Support Vector Machine, Tamil Nadu, Change detection
