Generating a 10 m resolution canopy height model of new york state using gedi and sentinel-2 data

Investigating the quantity of forest above-ground biomass (AGB) is vital for understanding the role of forests in the global carbon cycle. Canopy height model (CHM) plays an important role in estimating AGB. Accurate large-scale forest CHM estimation using traditional methods requires a lot of labor, time, and cost. Remote sensing is a cost-effective approach, which provides valuable information over large areas in a timely manner. Recent advances in spaceborne light detection and ranging (LiDAR) data paved the road for measuring elevation. The global ecosystem dynamics investigation (GEDI) onboard the International Space Station is particularly designed to collect information on vertical vegetation structure. Thus, the main objective of this paper is to use the GEDI level 2A elevation and height metrics product to create a high resolution, state-wide CHM. To create a continuous CHM, GEDI point-based height measurements were extrapolated using Sentinel-2 imagery to produce a 10 m CHM of the New York State for the year 2019. The generated 10 m CHM was evaluated using GEDI height measurements (RMSE=4.85 m, R-2=0.65). A comparison of 10 m CHM and a 30 m global CHM (RMSE=6.6 m, R-2=0.62) demonstrated the potential of finer spatial resolution and red-edge bands in creating a more accurate CHM which is important to support forest monitoring at large-scale.