Retrieval of forest canopy height in a mountainous region with ICESat-2 ATLAS

Forest canopy height is one of the important forest parameters for accurately assessing forest biomass or carbon sequestration. ICESat-2 ATLAS provides the potential for retrieval of forest canopy height at global or regional scale, but the current canopy height product (ATL08) has coarse resolution and high uncertainty compared to airborne LiDAR-derived canopy height (hereafter ALCH) in mountainous regions, and is not ready for such applications as biomass modeling at finer scale. The objective of this research was to explore the approach to accurately retrieve canopy height from ATLAS data by incorporating an airborne-derived digital terrain model (DTM) and a data-filtering strategy. By linking ATLAS ATL03 with ATL08 products, the geospatial locations, types, and (absolute) heights of photons were obtained, and canopy heights at different lengths (from 20 to 200 m at 20-m intervals) of segments along a track were computed with the aid of airborne LiDAR DTM. Based on the relationship between the numbers of canopy photons within the segments and accuracy of ATLAS mean canopy height compared to ALCH, a filtering method for excluding a certain portion of unreliable segments was proposed. This method was further applied to different ATLAS ground tracks for retrieval of canopy heights and the results were evaluated using corresponding ALCH. The results show that the incorporation of high-precision DTM and ATLAS products can considerably improve the retrieval accuracy of forest canopy height in mountainous regions. Using the proposed filtering approach, the correlation coefficients (r) between ATLAS canopy height and corresponding ALCH were 0.61???0.91, 0.65???0.92, 0.68???0.94 for segment lengths of 20, 60, and 100 m, respectively; RMSE were 1.90???4.35, 1.55???3.63, and 1.34???3.23 m for the same segment lengths. The results indicate the necessity of using high-precision DTM and using the proposed filtering method to retrieve accurate canopy height from ICESat-2 ATLAS in mountainous regions with dense forest cover and complex terrain conditions.

Automated summary

This research aims to explore the method of accurately retrieving forest canopy height from ATLAS data and improve retrieval accuracy by incorporating a high-precision digital terrain model (DTM) and a data-filtering strategy. The results show that using the proposed method, the retrieval accuracy of forest canopy height in mountainous regions with dense forest cover and complex terrain conditions can be considerably improved.