Can ICESat-2 estimate stand-level plant structural traits? Validation of an ICESat-2 simulator

Science of Remote Sensing(2023)

引用 1|浏览18
暂无评分
摘要
Global measurement of plant structural traits like canopy height, canopy cover and Plant Area Volume Density (PAVD) profiles form a key input for many emerging fields in ecology and meteorology. Here, we test the ability of an ICESat-2 simulator, based on the GEDI simulator presented by Hancock et al. (2019) and pre-launch ICESat-2 simulations by Neuenschwander and Magruder (2016), to replicate measurements of plant structural traits retrieved from ICESat-2 observations and, through this, explore the sensitivity of ICESat-2 to plant structural traits not currently in the ATL08 product. The simulator takes Airborne Laser Scanning (ALS) data, produces a pseudo-waveform and then samples individual photons to replicate real ICESat-2 measurements. Because the simulator assumes that the ICESat-2 photon-cloud distribution is proportional to the ALS vertical profile, which has been shown to be sensitive to canopy cover and structure, an accurate ICESat-2 simulator would indicate that ICESat-2 is sensitive to plant structural traits. ALS data are used to re-classify real ICESat-2, removing any classification error from the ATL08 product in order to allow a direct comparison of the returned photon profiles, from which the key simulation parameters -pure vegetation and pure ground photon rates -are calculated. ICESat-2 tracks that intersect ALS measurements from a range of sites and forest types are identified and simulated, allowing for one-to-one comparison of simulated and observed ICESat-2 photon-profiles and plant structural trait measurements. The canopy height, canopy cover, Relative Height metrics and PAVD profiles calculated from simulated and observed ICESat-2 photons are similar, with the simulator having an average canopy height bias of less than 50 cm and canopy cover bias less than 1.5% relative to the observed ICESat-2 data for sites where canopy:ground reflectance ratio is well constrained, indicating that ICESat-2 is sensitive to stand-level plant structural traits. Noise and differences between ground and canopy reflectances are found to be two key influences on the accuracy of ICESat-2 simulations and so plant structural trait measurement. This research suggests that, with global mapping of ground and canopy reflectances and correctly classified photons in the ATL08 product, it is possible to derive stand-level plant structural trait measurements from ICESat-2.
更多
查看译文
关键词
structural traits,plant,stand-level
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要