🌿 RapidFEM4D: Aboveground Biomass Density Maps for Post-Hurricane Ian Forest Monitoring in Florida

📌 Overview

RapidFEM4D is a project focused on generating Aboveground Biomass Density maps to monitor the impact and recovery of Florida’s forests following Hurricane Ian. Using Google Earth Engine (GEE) and machine learning models, the project integrates GEDI, Harmonized Landsat Sentinel, Sentinel-1 data to produce high-resolution biomass estimates.

📍 Study Area

• Region: Florida, USA
• Event Monitored: Hurricane Ian (2022)
• Key Data Sources:
  • GEDI L4A (Global Ecosystem Dynamics Investigation)
  • Harmonized Landsat Sentinel
  • Sentinel-1

🛠️ Project Components

🔹 AGBD Model Development

• Uses Random Forest Regression to train biomass models.
• Feature selection from optical, radar, and LiDAR data.
• Stored in Google Earth Engine assets