RapidFEM4D

Damage assessment through AGBD calculates the extent of environmental impact based on the percentage loss of pixel values. Losses less than 5% indicate No damage, while 5-25% is Light damage. Moderate damage is seen with 25-33% loss, Severe damage with 33-50%, and anything over 50% is considered Catastrophic.

Welcome to RapidFEM4D

Welcome to RapidFEM4D, a web-based mapping platform for assessing the impacts and recovery of Hurricane Ian on forest ecosystems in Florida.

Developed by the Forest Biometrics, Remote Sensing, and Artificial Intelligence (SilvaLab) at the University of Florida, this innovative mapping tool offers a perspective on the aftermath of Hurricane Ian. Explore data, visualizations, and insights on above-ground biomass density in Florida's forest ecosystems.

Let's explore, discover, and learn together!

Damage classification

No damage

Light

Moderate

Severe

Catastrophic

Mg/ha

Opacity:

Your feedback matters!

We value your input in enhancing RapidFEM4D.

Please share your feedback, suggestions, or any concerns to help us improve the platform and better meet your needs.

You can also reach us directly at silvalab.ufl@gmail.com

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How to cite RapidFEM4D

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

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 . [In preparation]