The objective for this study is to address existing knowledge gaps by developing a reliable land cover identification approach using Sentinel-1 imagery to support sustainable environmental management in the Lake Maninjau area. This area is significant due to its ecological, economic, and social functions for the community. The research method employed entails the interpretation of objects on the earth's surface in satellite images. This process necessitates the identification of these objects through visual recognition, based on the characteristics or attributes inherent to each object. The visual interpretation of Sentinel 1 SAR (synthetic aperture radar) data utilized Google Earth as a geographical reference platform. The results of this study demonstrate the capability of Sentinel-1 data in distinguishing major land-cover classes, including water bodies, settlements, rice fields, aquaculture ponds, and vegetation. Sentinel-1 is an effective and efficient data source for land cover monitoring, especially in areas frequently covered by clouds.