Mangrove ecosystems face growing threats from human activity and erosion. This study aims to map mangrove distribution and canopy density and to evaluate the relationship between Normalized Difference Vegetation Index (NDVI) and field-measured canopy cover in East Belitung, Indonesia, by integrating high-resolution Pleiades imagery, NDVI, and hemispherical photography. A total of 50 field plots were used to assess canopy cover through hemispherical photography, while Object-Based Image Analysis (OBIA) with Support Vector Machine (SVM) classification was applied to map mangrove distribution and density. Results show that very dense canopies were largely associated with stands dominated by Rhizophora spp. along riverbanks and estuaries, especially in the northern and southern parts of the study area, with favorable hydrological conditions. Classification accuracy reached 83.3% (Kappa = 0.71), and canopy cover was strongly correlated with NDVI (r = 0.855), validating the method. The regression analysis further showed that canopy cover explained a substantial proportion of NDVI variation (R 2 = 0.731). Combining satellite data with field validation offers a scalable framework for mangrove monitoring and supports coastal resilience and sustainable management.
Agus et al. (Wed,) studied this question.