Mangrove AGB (Pesawaran District 2020-2022)

This study develops a multisource ensemble-learning framework for mangrove AGB estimation in Pesawaran District, Indonesia, by integrating optical imagery from Sentinel-2, SAR backscatter from Sentinel-1, GEDI LiDAR–derived structural metrics, and environmental variables within a monthly, time-aligned dataset from 2020 to 2022.本研究针对印度尼西亚佩萨瓦兰县的红树林地上生物量（Aboveground Biomass，AGB）估算任务，构建了一种多源集成学习框架。该框架将哨兵二号（Sentinel-2）光学影像、哨兵一号（Sentinel-1）合成孔径雷达（Synthetic Aperture Radar，SAR）后向散射数据、GEDI激光雷达（GEDI LiDAR）衍生的结构参数与环境变量整合至2020至2022年的逐月时间对齐数据集中，以此开展该区域的红树林地上生物量估算研究。