Mangroves play a pivotal role in providing ecological benefits and services to reduce and adapt to climate change impact on coastal ecosystem. They are capable of absorbing carbon, which is crucial in controlling CO₂ levels in the atmosphere. This research aims to assess the accuracy of selected vegetation indices for estimating above-ground carbon (AGC) stocks of mangroves using PlanetScope images in Bedul, Banyuwangi, East Java Province, Indonesia. A semi-empirical approach was used to assess and map mangrove AGC, starting with applying the allometric equation to calculate field-measured species-specific AGC stocks. Regression analyses were applied to develop a relationship between field AGC and vegetation indices derived from PlanetScope Image, including Normalized Difference Vegetation Index (NDVI), Difference Vegetation Index (DVI), and Enhanced Vegetation Index (EVI). The Standard Errors of Estimates (SE) were 31.41, 32.93, and 31.63 tons/ha for DVI, EVI, and NDVI, respectively. Thus, carbon stocks estimation, including DVI as an independent variable, is considered more accurate than other vegetation indices tested in this research

红树林在提供生态效益和服务以减少和适应气候变化对沿海生态系统的影响方面起着关键作用。它们具有吸收碳的能力，这对于控制CO ₂至关重要大气中的水平。这项研究的目的是使用印度尼西亚东爪哇省Banyuwangi的Bedul的PlanetScope图像，评估用于估算红树林的地上碳（AGC）储量的选定植被指数的准确性。首先采用半经验方法对红树林AGC进行评估和绘制地图，首先应用异速方程来计算实地测量的特定物种AGC种群。应用回归分析来建立田间AGC与从PlanetScope影像获得的植被指数之间的关系，包括归一化差异植被指数（NDVI），差异植被指数（DVI）和增强植被指数（EVI）。DVI，EVI和NDVI的标准估计误差（SE）分别为31.41、32.93和31.63吨/公顷。因此，碳储量估算（包括DVI作为自变量）