AI RESEARCH
Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation
arXiv CS.AI
•
ArXi:2501.19328v3 Announce Type: replace-cross With the rise in global greenhouse gas emissions, accurate large-scale tree canopy height maps are essential for understanding forest structure, estimating above-ground biomass, and monitoring ecological disruptions. To this end, we present a novel approach to generate large-scale, high-resolution canopy height maps over time. Our model accurately predicts canopy height over multiple years given Sentinel-1 composite and Sentinel~2 time series satellite data. Using GEDI LiDAR data as the ground truth for.