Quantifying Mangrove Health Using the Biophysical Mangrove Vegetation Structure Index (BMVSI) for Sustainable Coastal Management in the Bintan Islands, Indonesia

Indonesia has the most extensive mangrove coverage globally, yet a single, integrated metric for defining mangrove health status remains limited. Bintan Island, significant for its bauxite mining history and as a major foreign tourist destination, could experience impacts on its mangrove health. The objective of the article is to assess the health status of Bintan’s mangroves using the Biophysical Mangrove Vegetation Structure Index (BMVSI), which was derived strictly from eleven field measurement indicators. Additionally, the study compares the BMVSI results with five vegetation-based indices from satellite remote sensing datasets. The BMVSI was developed using the Principal Component Analysis (PCA) with ten significant variables representing 87.3% of the total variance. They are Above Ground Biomass (AGB), tree diameter, stand diameter, total basal area, tree height, canopy coverage, the number of trees, total stands, number of seedlings, and biodiversity. The health status using BMVSI was ranked from worst, bad, moderate, good, and excellent. The results stated that Bintan’s BMVSI status was mainly categorized as moderate, followed by good, bad, and worst, with none of them classified as excellent. Good status was observed at two stations in Berakit and one in Kawal, while the worst was found only in Kawal Village. Moreover, among the vegetation indices used, Normalized Difference Chlorophyll Index (NDCI) and Normalized Difference Vegetation Index (NDVI) revealed the highest correlation (r = 0.71) with the BMVSI, and these indices were able to detect the worst and bad status of BMVSI. In conclusion, the BMVSI framework is designed to capture the diversity of ecological conditions by incorporating ten key parameters that reflect essential components of a healthy ecosystem. This approach has the potential to integrate field measurements with remote sensing data, facilitating a more comprehensive and flexible assessment of mangrove health. Moreover, given the region’s rapid economic development, particularly in Kawal Village, there is an urgent need for mangrove forest rehabilitation.