Bueno Inacio T, Silva Carlos A, Hamamura Caio, Donovan Victoria M, Sharma Ajay, Qiu Jiangxiao, Xia Jinyi, Brock Kody M, Schlickmann Monique B, Atkins Jeff W, Valle Denis R, Vogel Jason, Susaeta Andres, Karasinski Mauro A, Klauberg Carine
School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL, 32611, USA.
Federal Institute of Education, Science and Technology of São Paulo, Capivari, SP, Brazil.
Sci Data. 2025 Jul 10;12(1):1189. doi: 10.1038/s41597-025-05464-0.
Hurricane Ian caused aboveground biomass density (AGBD) losses across Florida's forests in the United States, highlighting the need for accurate, large-scale monitoring tools. We combined Global Ecosystem Dynamics Investigation (GEDI) LiDAR data with synthetic aperture radar (SAR) and passive optical satellite imagery to model GEDI AGBD as a function of image-derived data, enabling predictions across the study area and producing continuous AGBD maps. Validation using in situ field data demonstrated high model performance, with an R of 0.93 and a root mean square difference (RMSD) of 39.3%. Spatial uncertainty reflecting bootstrap-derived variance remained consistent, with relative standard errors around 90% across the years analyzed. The data are accessible through a web application, RapidFEM4D, enabling researchers and stakeholders to assess AGBD maps for areas of interest. These datasets support monitoring forest recovery, assessing carbon dynamics, and guiding post-hurricane management and restoration. The RapidFEM4D platform facilitates access and analysis of Hurricane Ian's impact on Florida's forests, empowering stakeholders with actionable insights and offering a model for similar efforts in other hurricane-prone regions.
飓风伊恩给美国佛罗里达州的森林造成了地上生物量密度（AGBD）损失，凸显了对精确的大规模监测工具的需求。我们将全球生态系统动力学调查（GEDI）激光雷达数据与合成孔径雷达（SAR）及被动光学卫星图像相结合，以将GEDI AGBD建模为图像衍生数据的函数，从而能够对整个研究区域进行预测并生成连续的AGBD地图。使用实地现场数据进行的验证显示模型性能良好，R值为0.93，均方根差（RMSD）为39.3%。反映自举法衍生方差的空间不确定性保持一致，在所分析的年份中相对标准误差约为90%。这些数据可通过一个网络应用程序RapidFEM4D获取，使研究人员和利益相关者能够评估感兴趣区域的AGBD地图。这些数据集有助于监测森林恢复情况、评估碳动态，并指导飓风后的管理和恢复工作。RapidFEM4D平台便于获取和分析飓风伊恩对佛罗里达州森林的影响，为利益相关者提供可采取行动的见解，并为其他飓风多发地区的类似工作提供了一个范例。
