Aboveground biomass density maps for post-hurricane Ian forest monitoring in Florida
Abstract 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 passi...
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Nature Portfolio
2025-07-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05464-0 |
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| author | Inacio T. Bueno Carlos A. Silva Caio Hamamura Victoria M. Donovan Ajay Sharma Jiangxiao Qiu Jinyi Xia Kody M. Brock Monique B. Schlickmann Jeff W. Atkins Denis R. Valle Jason Vogel Andres Susaeta Mauro A. Karasinski Carine Klauberg |
| author_facet | Inacio T. Bueno Carlos A. Silva Caio Hamamura Victoria M. Donovan Ajay Sharma Jiangxiao Qiu Jinyi Xia Kody M. Brock Monique B. Schlickmann Jeff W. Atkins Denis R. Valle Jason Vogel Andres Susaeta Mauro A. Karasinski Carine Klauberg |
| author_sort | Inacio T. Bueno |
| collection | DOAJ |
| description | Abstract 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 R2 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. |
| format | Article |
| id | doaj-art-0604b2c46eb042dc80ca970d77b09aca |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-0604b2c46eb042dc80ca970d77b09aca2025-08-20T04:01:46ZengNature PortfolioScientific Data2052-44632025-07-0112111410.1038/s41597-025-05464-0Aboveground biomass density maps for post-hurricane Ian forest monitoring in FloridaInacio T. Bueno0Carlos A. Silva1Caio Hamamura2Victoria M. Donovan3Ajay Sharma4Jiangxiao Qiu5Jinyi Xia6Kody M. Brock7Monique B. Schlickmann8Jeff W. Atkins9Denis R. Valle10Jason Vogel11Andres Susaeta12Mauro A. Karasinski13Carine Klauberg14School of Forest, Fisheries, and Geomatics Sciences, University of FloridaSchool of Forest, Fisheries, and Geomatics Sciences, University of FloridaFederal Institute of Education, Science and Technology of São PauloSchool of Forest, Fisheries, and Geomatics Sciences, University of FloridaCollege of Forestry, Wildlife and Environment, Auburn UniversitySchool of Forest, Fisheries, and Geomatics Sciences, University of FloridaSchool of Forest, Fisheries, and Geomatics Sciences, University of FloridaSchool of Forest, Fisheries, and Geomatics Sciences, University of FloridaSchool of Forest, Fisheries, and Geomatics Sciences, University of FloridaUSDA Forest Service, Southern Research StationSchool of Forest, Fisheries, and Geomatics Sciences, University of FloridaSchool of Forest, Fisheries, and Geomatics Sciences, University of FloridaDepartment of Forest Engineering, Resources and Management, Oregon State UniversityBIOFIX Research Center, Federal University of ParanáSchool of Forest, Fisheries, and Geomatics Sciences, University of FloridaAbstract 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 R2 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.https://doi.org/10.1038/s41597-025-05464-0 |
| spellingShingle | Inacio T. Bueno Carlos A. Silva Caio Hamamura Victoria M. Donovan Ajay Sharma Jiangxiao Qiu Jinyi Xia Kody M. Brock Monique B. Schlickmann Jeff W. Atkins Denis R. Valle Jason Vogel Andres Susaeta Mauro A. Karasinski Carine Klauberg Aboveground biomass density maps for post-hurricane Ian forest monitoring in Florida Scientific Data |
| title | Aboveground biomass density maps for post-hurricane Ian forest monitoring in Florida |
| title_full | Aboveground biomass density maps for post-hurricane Ian forest monitoring in Florida |
| title_fullStr | Aboveground biomass density maps for post-hurricane Ian forest monitoring in Florida |
| title_full_unstemmed | Aboveground biomass density maps for post-hurricane Ian forest monitoring in Florida |
| title_short | Aboveground biomass density maps for post-hurricane Ian forest monitoring in Florida |
| title_sort | aboveground biomass density maps for post hurricane ian forest monitoring in florida |
| url | https://doi.org/10.1038/s41597-025-05464-0 |
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