<![CDATA[Abstract Mangrove forests in Timbulsloko and Bedono have very dynamic conditions, due to tidal flooding and land subsidence that occur in these areas. Meanwhile, mangrove forests in the Timbulsloko and Bedono Village play an important role in preventing abrasion which often occurs in these areas. The importance of the mangroves function in this area makes it crucial to monitor their condition. Monitoring the condition of mangroves can be done by looking at their density through the vegetation index. Therefore, this study aimed to determine the best vegetation index to be used in the Timbulsloko and Bedono villages to monitor mangroves in 2016-2018, 2020, and 2022. The method in this research consisted of two stages, namely sentinel 2 image processing and the field survey. Image processing was used to determine the condition of mangroves based on several vegetation indices. Meanwhile, data collection in the field was utilized to validate several vegetation indices used in this study and conducted with the hemispherical photography method. Linear regression analysis was used to determine the most suitable vegetation index to be applied in the study area. The study found that NDVI vegetation index had the highest accuracy value, followed by SAVI, EVI, and MVI. The use of NDVI to see the changes in mangrove conditions showed an increase in the total area in each category. So, it can be concluded that the area and density of mangrove forests in the Bedono and Timbulsloko villages increased every year. Highlight Research Mangroves in each region have different canopy density values. The use of the mangrove vegetation index will produce different accuracy values in different areas. LAI has a very strong relationship with the NDVI. The addition of area in the sparse mangrove category can be an indication of mangrove planting at the most recent time. In general, the research outcome will be valuable recommendation for mangrove rehabilitation in current target area.]]>
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