空间科学学报2023，Vol.43Issue(6)：1176-1193,18.DOI:10.11728/cjss2023.06.2023-0074
基于多源遥感数据的植被冠层高度估算
Forest Canopy Height Mapping Based on Multi-source Remote Sensing Data
摘要
Abstract
Accurate estimation of spatially continuous forest canopy height is crucial for quantifying forest carbon stocks,understanding forest ecosystems,and making forest management and restoration policies.Spaceborne Light Detection and Ranging(LiDAR)can measure forest canopy height over laser footprints at semi-global the coverage,which provides a promising data source for estimating forest canopy height at national to global scales.This study used the random forest regression method to map forest canopy height by fusing Ice,Cloud and land Elevation Satellite-2(ICESat-2)Advanced Topo-graphic Laser Altimeter System(ATLAS)measurements and Landsat-8 images,combined with terrain and climatic features,and other data to generate forest canopy height products of the maximum(Hmax)and mean height(Hmean)values at 30 meter resolution across Mississippi State of America in 2020.The results show that the mean and standard deviation of Hmax in forest area is 24.14 m and 4.24 m respec-tively.For the Hmean,the mean and standard deviation of Hmean in forest area were 12.04 m and 2.59 m respectively.The estimated Hmax and Hmean across Mississippi agree well with airborne measurements(Hmax:R2 = 0.486,HRMSE = 4.532 m;Hmean:R2 = 0.467,HRMSE = 2.848 m).In this study,the differ-ence and ratio of the maximum and average values of canopy height were used to reflect the vertical structure complexity of the forest canopy.The differences of different geographical divisions,forest types,planted forests and natural forests were compared,and it was found that the complexity of loess hilly ar-eas,deciduous forests,wetland forests and natural forests in the study area was higher.In addition,the canopy height mapping scheme proposed in this study for non-mountain plantations is of guiding signifi-cance for forest management,species diversity conservation and"carbon neutrality"assessment in the in the Yangtze River Delta and other areas dominated by non-mountain planted forest of China.关键词
激光雷达/ICESat-2/冠层高度制图/多源遥感/密西西比森林Key words
LiDAR/ICESat-2/Canopy height mapping/Multi-source remote sensing/Mississippi forest分类
信息技术与安全科学引用本文复制引用
田镇朋,马勤,周维,袁敬毅,刘小强,叶粟,POUDEL Krishna,HIMES Austin,RENNINGER Heidi,王家新..基于多源遥感数据的植被冠层高度估算[J].空间科学学报,2023,43(6):1176-1193,18.基金项目
国家自然科学基金青年科学基金项目(42201366)和南京师范大学启动基金项目(184080H202B349)共同资助 （42201366）
