Abstract: Based on multitemporal remote sensing (Sentinel-1/2) image data, the digital elevation model (DEM), and the Google Earth Engine (GEE) platform, this study achieved the large-scale dynamic monitoring of the ranges and interspecific distributions of mangrove forests in Hainan Island in 2016, 2019, and 2022. The effects of Sentinel-1 polarization and DEM-derived topographic features were considered in distinguishing mangrove species. Compared to the species identification using only Sentinel-2 image data, the identification method incorporating polarization or topographic features improved the classification accuracy by 3.34 and 3.35 percentage points, respectively. Moreover, incorporating both polarization and topographic features into the identification process was more effective for the interspecific classification of mangrove forests, raising the classification accuracy by 4.07 percentage points and enabling more accurate extraction of different species information. The monitoring results indicate that the areas of mangrove forests in Hainan Island in 2016, 2019, and 2022 were 3628.738 hm², 3634.129 hm², and 3881.212 hm², respectively, showing an overall increase at an average annual rate of 1.127% over six years. Regarding population dynamics, the dominant species included Ceriops tagal and Rhizophora stylosa in the northern mangrove forest in Dongzhai port, and Bruguiera sexangula in the southern portion. The northern estuary of Bamen Bay was dominated by Bruguiera sexangula, while the Wenjiao River mouth exhibited richer species. In the Xinying, and Huachang bays, and Maniao Port, the dominant mangrove species shifted from Ceriops tagal and Rhizophora stylosa to Kandelia obovata and Lumnitzera racemosa over six years, with Sonneratia apetala spreading at the bay mouths. In Xinying Port, the dominant mangrove species shifted from Rhizophora stylosa and Rhizophora stylosa to Lumnitzera racemose. The distribution of Kandelia obovata in Dongfang City expanded gradually, while the species composition in Sanya City remained almost stable, with the growth area occupied primarily by Ceriops tagal. Overall, the method used in this study enhances the identification accuracy of mangrove species, allowing a fine-scale analysis of the evolutionary process of mangrove species, thereby supporting the formulation of the mangrove forest protection policy.