ANALYSIS OF NDVI, NDWI, AND SAVI TRANSFORMATIONS FOR IDENTIFICATION OF MANGROVE DENSITY IN BENGKULU - Al Ikhsan Rama Komura; Sumarmi Sumarmi; Syamsul Bachri (Universitas Sebelas Maret (UNS), 2025)
This study was conducted in the mangrove forest area of Bengkulu City, Indonesia, which is rich in ecosystem diversity and has a long coastline. By utilising remote sensing technology, this study aimed to provide accurate information on the condition of mangrove forests and their role in the local ecosystem. Sentinel image analysis using NDVI, SAVI, and NDWI vegetation indices showed that NDVI was dominated by high density with values between 0.35 and 1, covering an area of 674.19 hectares. In the SAVI analysis, an extremely high density class with values 1.22 to 1.38 covered an area of 457.82 hectares. Conversely, NDWI indicated a low-density class with values between 0.17 and 0.27, covering an area of 457.82 hectares. Accuracy tests conducted with 30 samples showed an accuracy level of 83.33%. It is hoped that this study's results can significantly contribute to the understanding and management of mangrove ecosystems in Bengkulu City.