Land Use and Land Cover Change Detection using Google Earth Engine

Land use and Land Cover (LULC) usually denotes to the classification of human activities and natural elements on the earth surface within a specific time edge. With the development of remote sensing technology and availability of multispectral data, LULC has become crucial in various applications like urbanization and agriculture. This research study focuses on demarcating cloud enabled remote sensing platform, Google Earth Engine (GEE) along with the use of machine learning algorithms and evaluates the platform’s utility to perform LULC. The multispectral datasets like Landsat-7 and sentinel-2 are used to test the performance. The visualization and analysis on change map between the years 2002-2015 shows the various correctly classified land cover regions.