Rapid mapping of land cover changes in tropical watershed in Indonesia using Google Earth Engine

Abstract Besitang watershed is one of the tropical watersheds in Indonesia. In the upstream area, Besitang watershed is part of the Gunung Leuser National Park, a conservation forest abundant with diverse wildlife, including primates and terrestrial mammals. Studying land cover changes in Besitang watershed is crucial. A challenge in studying land cover changes in tropical watersheds is cloud cover, thus necessitating land cover mapping studies in Besitang watershed using Google Earth Engine (GEE). GEE is a platform for processing geo-big data, providing extensive and cloud-free satellite image data. Therefore, this study aims to map land cover in Besitang watershed using machine learning-based classification on GEE. The land cover mapping process in Besitang watershed utilizes Landsat 8 satellite imagery. The input data includes bands 1 to 7 of Landsat 8 imagery and image transformations such as NDVI, NDWI, NDBI, BSI, EVI, NDTI, SATVI. The years selected for analysis are 2001 and 2021, with machine learning techniques tested including CART and Random Forest (RF). The results of this study indicate that RF is the best machine learning method for mapping land cover in Besitang watershed, using an image combination consisting of Band 2, Band 3, Band 4, Band 5, Band 6, Band, NDVI, NDWI, NDBI, BSI. The mapping results show a forest area change of approximately 352326.29 hectares, with the majority of changes to plantation.