<![CDATA[Mangrove forest is one of the essential components of natural ecosystems. Mangrove forests have various essential functions, such as holding land sediments, tsunamis, and ocean waves, storing large amounts of carbon, and providing various other benefits for coastal and land areas. However, the conversion of mangrove forests has reduced and degraded mangrove land. Therefore, monitoring and conserving land changes in mangrove forests must be carried out to determine the effects on land ecosystems and coastal areas. Remote sensing has the spatial ability to analyze changes in mangrove ecosystems in coastal regions temporally because it has the advantage of using satellite imagery data. This study compares the classification method using multiple image sensors to analyze land cover changes in mangrove forests in North Luwu Regency, South Sulawesi, in 2015-2020. The technique used in this research is the classification of Object-Based Image Analysis (OBIA) and the variety of Maximum Likelihood. The results of Sentinel-1 image analysis using Maximum Likelihood provide information on changes in mangrove land cover during 2015-2020 with an area of 449.17 (Ha), while the results of Landsat 8 analysis using (OBIA) provide information on changes in mangrove land cover 596 (Ha).Keywords: Optics, Radar, OBIA, Maximum Likelihood, Mangrove]]>
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