Assessment of Slope-Adaptive Metrics of GEDI Waveforms for Estimations of Forest Aboveground Biomass over Mountainous Areas

作     者：Wenjian Ni Zhiyu Zhang Guoqing Sun 

作者机构：State Key Laboratory of Remote Sensing ScienceAerospace Information Research InstituteChinese Academy of SciencesBeijing 100101China University of Chinese Academy of SciencesBeijing 100049China Department of Geographical SciencesUniversity of MarylandCollege ParkMD 20742USA 

出 版 物：《Journal of Remote Sensing》 (国际遥感学报（英文）)

年 卷 期：2021年第2021卷第1期

页      面：180-196页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：sponsored by the National Key R&D Pro-gram of China(2020YFE0200800 and 2017YFA0603002) National Natural Science Foundation of China(Grant No.42022009) 

主　　题：terrain estimation ground 

摘      要：Waveform broadening effects of large-footprint lidar caused by terrain slopes are still a great challenge limiting the estimation accuracy of forest aboveground biomass(AGB)over mountainous ***-adaptive metrics of waveforms were proposed in our previous ***,its validation was limited by the unavailability of enough reference *** study made full validation of slope-adaptive metrics using data acquired by the Global Ecosystem Dynamics Investigation(GEDI)mission,meanwhile exploring GEDI waveforms on estimations of forest *** types of waveform metrics were employed,including slope-adaptive metrics(RHT),typical height metrics relative to ground peaks(RH),and waveform parameters(WP).In addition to terrain slopes,two other factors were also explored including the geolocation issue and signal start and ending points of *** showed that footprint geolocations in the first version GEDI data products were shifted to the left forward of nominal geolocations with a distance of about 24 m~30 m and were substantially corrected in the second version;the fourth and fifth groups of signal start and ending points of waveforms had worse performance than the rest of the four groups because they used the maximum and minimum signal thresholds,*** airborne laser scanner(ALS)data as reference,the root mean square error(RMSE)of terrain slopes extracted from the digital elevation model of the shuttle radar topography mission(SRTM DEM)was about 3°.The coefficients of determination(R^(2))of estimation models of forest AGB based on RH metrics were improved from 0.48 to 0.68 with RMSE decreased from 19.7 Mg/ha to 15.4 Mg/ha by the second version *** RHT and WP metrics gave the best and the worst estimation accuracy,*** further improved R^(2) to 0.77 and decreased RMSE to 13.0 Mg/ha using terrain slopes extracted from SRTM DEM with a resolution of 1 arc second.R^(2) of estimation models based on RHT was finally