Landsat-Scale Regional Forest Canopy Height Mapping Using ICESat-2 Along-Track Heights: Case Study of Eastern Texas

Spaceborne profiling lidar missions such as the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) are collecting direct elevation measurements, supporting the retrieval of vegetation attributes such as canopy height that are crucial in forest carbon and ecological studies. However, such profiling lidar systems collect observations along predefined ground tracks which limit the spatially complete mapping of forest canopy height. We demonstrate that the fusion of ICESat-2 along-track canopy height estimates and ancillary Landsat and LANDFIRE (Landscape Fire and Resource Management Planning Tools Project) data can enable the generation of spatially complete canopy height data at a regional level in the United States. We developed gradient-boosted regression models relating canopy heights with ancillary data values and used them to predict canopy height in unobserved locations at a 30 m spatial resolution. Model performance varied (R2 = 0.44 − 0.50, MAE = 2.61–2.80 m) when individual (per month) Landsat data and LANDFIRE data were used. Improved performance was observed when combined Landsat and LANDFIRE data were used (R2 = 0.69, MAE = 2.09 m). We produced a gridded canopy height product over our study area in eastern Texas, which agreed moderately (R2 = 0.46, MAE = 4.38 m) with independent airborne lidar-derived canopy heights. Further, we conducted a comparative assessment with the Global Forest Canopy Height product, an existing 30 m spatial resolution canopy height product generated using GEDI (Global Ecosystem Dynamics Investigation) canopy height and multitemporal Landsat data. In general, our product showed better agreement with airborne lidar heights than the global dataset (R2 = 0.19 MAE = 5.83 m). Major differences in canopy height values between the two products are attributed to land cover changes, height metrics used (98th in this study vs 95th percentile), and the inherent differences in lidar sampling and their geolocation uncertainties between ICESat-2 and GEDI. On the whole, our integration of ICESat-2 data with ancillary datasets was effective for spatially complete canopy height mapping. For better modeling performance, we recommend the careful selection of ICESat-2 datasets to remove erroneous data and applying a series of Landsat data to account for phenological changes. The canopy height product provides a valuable spatially detailed and synoptic view of canopy heights over the study area, which would support various forestry and ecological assessments at an enhanced 30 Landsat spatial resolution