Work

Development of a new mangrove integrity index (MII) using multi-sensor remote sensing approaches

Year: 2025

Type: article

Abstract: • XGBoost yields the most accurate predictions. • Climate factors show weak influence. • MII enables efficient large-scale assessment. Mangrove forests are essential for biodiversity, coastal protection, and carbon sequestration, yet anthropogenic pressures and climate change increasingly threaten them. This study introduces a novel approach to assessing mangrove conditions, including their health, structure, and vitality through the development of the Mangrove Integrity Index (MII), integrating structural attributes—above-ground biomass, tree volume, basal area, and stand density—derived from multi-satellite sensors. Conducted in the mangrove forests of Sungai Merbok, Sungai Pulai, and Sungai Johor, Malaysia, the study further examines the relationship between these structural attributes and climatic factors, utilising the ERA5-Land reanalysis dataset. Sentinel-1 and Sentinel-2 data were employed to derive SAR polarisation indices, vegetation indices, biophysical parameters, and GLCM texture features, modelled using XGBoost, Random Forest, Boosted Tree, and Support Vector Machines. XGBoost showed the highest accuracy: AGB (R 2 = 0.94, RMSE = 38.40 Mg ha −1 , MAE = 15.03 Mg ha −1 ), tree volume (R 2 = 0.97, RMSE = 11.41 m 3 ha −1 , MAE = 4.37 m 3 ha −1 ), basal area (R 2 = 0.97, RMSE = 1.84 m 2 ha −1 , MAE = 0.74 m 2 ha −1 ), and stand density (R 2 = 0.99, RMSE = 37 trees ha −1 , MAE = 18 trees ha −1 ). Climatic factors showed weak correlations with mangrove attributes. The entropy-weighted MII objectively classified mangroves into five integrity levels by assigning data-driven weights to multiple structural indicators, reducing subjective bias. Results revealed distinct spatial patterns, with Sungai Johor showing significantly higher degradation compared to Sungai Merbok and Sungai Pulai. These findings highlight the urgency for targeted restoration in vulnerable areas and offer a scalable, data-driven tool to support national and global conservation initiatives, including the 13th Malaysia Plan Strategy D6 and the Sustainable Development Goals.

Source: Ecological Indicators

DOI: 10.1016/j.ecolind.2025.114421