Remote Sensing of Mangrove Health and Vulnerability in Tolongano
DOI:
https://doi.org/10.55173/agriscience.v10i1.206Keywords:
mangrove forests, vegetation health, vulnerability, remote sensing, SAVI, weighted overlay.Abstract
Mangrove ecosystems play an important role in protecting coastal areas from erosion, waves, and other environmental disturbances. However, increasing anthropogenic pressures, including aquaculture expansion, settlement development, and land-use conversion, threaten their sustainability. Previous studies have commonly assessed mangrove health or vulnerability separately, providing limited insight into the relationship between ecosystem condition and potential threats. This study addresses this gap by integrating the Soil Adjusted Vegetation Index (SAVI) and Multi-Criteria Decision Analysis (MCDA) to evaluate mangrove health, spatial vulnerability, and their relationship in Tolongano Village, South Banawa Sub-district, Central Sulawesi. The integration of SAVI and MCDA offers a novel framework for identifying healthy mangrove areas that remain exposed to significant anthropogenic pressures.Using Landsat 8/9 imagery, land-use data, and field validation at 45 sampling points, mangrove health was classified into healthy (72.78 ha; 52.47%), moderate (32.82 ha; 23.66%), and unhealthy/degraded (33.11 ha; 23.87%) categories. Classification accuracy was high, with an Overall Accuracy of 97.78% and a Kappa coefficient of 0.98. Vulnerability analysis showed that 87.40% of the mangrove area was categorized as very highly vulnerable, mainly due to the proximity of aquaculture ponds. Correlation analysis produced a weak negative relationship (r = −0.2390) between mangrove health and vulnerability. The results indicate that healthy mangrove stands may still face substantial future threats. The SAVI–MCDA approach provides a practical tool for conservation prioritization, coastal spatial planning, and long-term mangrove management.
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