Dataset
Bueno, I.T.; Silva, C.A.; Hamamura, C.; Schlickmann, M.B.; Donovan, V.M.;
Atkins, J.W.; Brock, K.; Xia, J.; Valle, D.R.; Qiu, J.; Vogel, J.;
Susaeta, A.; Sharma, A.; Karasinski, M.; Klauberg, C.
RapidFEM4D: aboveground biomass density maps for post-Hurricane Ian forest monitoring in Florida.
Ag Data Commons. Dataset.
https://doi.org/10.15482/USDA.ADC/28304213.v1
Data paper
Bueno, I.T.; Silva, C.A.; Hamamura, C.; Schlickmann, M.B.; Donovan, V.M.;
Atkins, J.W.; Brock, K.; Xia, J.; Valle, D.R.; Qiu, J.; Vogel, J.;
Susaeta, A.; Sharma, A.; Karasinski, M.; Klauberg, C.
Aboveground biomass density maps for post-hurricane Ian forest monitoring in Florida.
Sci Data 12, 1189 (2025).
https://doi.org/10.1038/s41597-025-05464-0
Methodology
Bueno, I.T.; Silva, C.A.; Schlickmann, M.B.; Donovan, V.M.; Atkins, J.W.;
Brock, K.; Xia, J.; Valle, D.R.; Qiu, J.; Vogel, J.; Susaeta, A.;
Sharma, A.; Klauberg, C.; Mohan, M.; Dalla Corte, A.P.
Upscaling Frameworks Drive Prediction Accuracy and Uncertainty When Mapping Aboveground Biomass
Density
from the Synergism of Spaceborne LiDAR, SAR, and Passive Optical Data.
Remote Sens. 2025, 17, 2340.
https://doi.org/10.3390/rs17142340
