Performance evaluation of ICESat-2 laser altimeter data for retrieving plant area index

Abstract

Canopy spatial structure plays an essential role in ecosystem function and the carbon cycle. The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) provided continuous three-dimensional sampling observation that can be used to derive canopy structure parameters. Although ICESat-2 data is delivering global estimates of forest structure, analysis of the performance of ICESat-2 data across a range of forest conditions remains limited. Therefore, the overall goal of this study was to evaluate the structural estimates of plant area index (PAI) from ICESat-2 data over temperate deciduous forest structural types. The PAI was derived using the geolocated photon data (ATL03) and the segment-based path length distribution method based on 100-m ICESat-2 vegetation product data (ATL08) segments. The ground-measured data used to evaluate the accuracy of PAI inversion at 100-m ATL08 segments was collected in the Saihanba forest reservation, northern China, which was covered by temperate deciduous needle-leaved forest. The results showed that the ICESat-2 PAI was in good agreement with ground-measured data, which indicated that the method had a better performance in retrieving PAI with ICESat-2 data. Moreover, we compared the effects of the characteristic of signal photons in the segments on the accuracy of PAI inversion and found that the accuracy of PAI inversion was limited by the quality of signal photons. Findings from this study highlight the method for estimating PAI with ICESat-2 data that may be suitable for a range of cover types.