Land use land cover change detection in the lower Bhavani basin, Tamil Nadu, using geospatial techniques

Abstract

Land use land cover (LULC) change detection is essential for sustainable development, planning and management. This study was an attempt to evaluate the LULC change in the lower bhavani basin from 2014 to 2019, using Landsat 8 data integrating Google Earth Engine (GEE) as a web-based platform and Geographic Information System. The CART and Random Forest classifiers in GEE were used for performing supervised classification. The classified map accuracy was assessed using high resolution imagery and evaluated using a confusion matrix implemented in GEE. Five major LULC classes, viz., agriculture, built up, current fallow, forest and waterbody, were identified, and the dominant land use in the study area was agriculture and current fallow, followed by dominant land use of forest. During the study period (2014–2019) the change in built-up area 7.37% in 2019 and 5.45% in 2014, was noted due to urban sprawl. GEE showed significant versatility and proved to be an effective platform for LULC detection.