Evaluating the Efficacy of Sentinel-2B and Landsat 8 OLI Satellite Imagery for Accurate Mangrove Mapping in Bengkulu City, Indonesia

Remote sensing has been extensively used to map mangrove forests. This study evaluates the accuracy of mangrove classification using Sentinel-2B and Landsat 8 OLI imagery in Bengkulu City, Indonesia. Using vegetation indices and maximum likelihood algorithms, the range of Normalized Difference Vegetation Index (NDVI) values are from 0.1181 to 0.6716 for Sentinel-2B and 0.0003 to 0.5142 for Landsat 8 OLI. Sentinel-2B yielded more precise classification result on mangrove, with an overall accuracy of 84.76%, in contrast to Landsat 8 OLI's accuracy of 65.71%. These results demonstrate the superior performance of Sentinel-2B in mangrove mapping due to its higher spatial resolution.