Mangroves are coastal ecosystems that play a vital role in maintaining coastal stability, providing habitat for diverse biota, and reducing the impacts of climate change. However, these ecosystems continue to face threats, including in Muara Jenggalu, Bengkulu City. This study aims to map the spatial distribution of mangroves using Sentinel-2A imagery with the Object-Based Image Analysis (OBIA) method, which employs SVM (Support Vector Machine) as a statistical technique for prediction and classification, while also examining the relationship between the vegetation index (NDVI) and mangrove canopy cover. The results indicate that the segmentation scale influences classification accuracy, with scale 3 achieving a high accuracy of 97.17% and a mangrove area of 41.01 ha. The classification segments the study area into four main classes: mangroves, non-mangrove vegetation, water bodies, and non-vegetation. NDVI values ranged from 0.12 to >0.35, with mangrove areas primarily in the medium to high vegetation category. Simple regression analysis revealed a significant positive relationship between canopy cover percentage and NDVI values. The information acquired from this research can be used as a basis for planning the conservation and sustainable management of coastal ecosystems.
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