NASA’s Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) provides rich insights over the earth’s surface through elevation data collected by its photon-counting lidar instrument, since its launch in September 2018. While this mission is primarily aimed to capture ice measurements, ICESat-2 also provides data over vegetated areas, offering the capability to gain insights into ecosystem structure with a space lidar. With ICESat-2 directly capturing the three-dimensional features of forests, a key surrogate measure of forest carbon, forest aboveground biomass (AGB), can potentially be estimated. This study involved an examination of the utility of ICESat-2 for estimating forest aboveground biomass (AGB). Methods previously developed with simulated ICESat-2 data over Sam Houston National Forest (SHNF) in southeast Texas, were implemented using actual data from an adjacent ICESat-2 transect over similar vegetation conditions. Custom noise filtering and photon classification algorithms were applied to ICESat-2’s geolocated photon data (ATL03) and canopy height estimates were retrieved. Reference AGB within 100 m x 17 m boxes in the along-track direction, were extracted for developing relationships between canopy height parameters from processed ATL03 data and AGB, using linear regression. ICESat-2-derived AGB estimates were then extrapolated to generate a 30-m AGB map for the study area, using vegetation indices from Landsat 8 OLI, landcover and canopy cover, with random forests (RF).
Results/Conclusions
Using a separate test set for model evaluation, the final regression model achieved a R2 and RMSE value of 0.62 and 24.63 Mg/ha for estimating AGB with ICESat-2 data from a strong beam. For comparison purposes, the model using data from a weak beam achieved a R2 of 0.37. Predicted AGB from 100-m segments were assigned to 30-m pixels and RF was used to model AGB with vegetation indices derived from Landsat 8 OLI and canopy cover and landcover maps from the National Land Cover Database (NLCD) as independent variables. Model evaluation with a separate test set yielded a R2 of 0.58 and RMSE of 23.89 Mg/ha. With increasing availability of observations from ICESat-2, insights about ecosystem structure and AGB could be investigated at multiple spatial scales, to contribute to an improved understanding of terrestrial carbon stocks and the sustainable management of forest resources. Methods implemented in this study are conducive to achieving spatially explicit estimates of AGB over a larger spatial extent. These findings provide an initial look at the ability of ICESat-2 to estimate AGB and will serve as a basis for further upscaling efforts.