基于多源数据并顾及森林类型的森林冠层高度反演
Forest canopy height inversion considering forest types based on multi-source data
[目的]基于随机森林方法,通过ICESat-2的LiDAR数据与Sentinel-1的SAR数据、Sentinel-2的光学影像以及地形数据的协同构建针、阔、混三种不同森林类型对应的森林冠层高度估计模型,并对不同森林类型对应模型的精度进行验证和比较;同时,利用随机森林方法获取不同模型对应建模最优变量集及集合中各变量重要性得分,并对各变量在模型建立过程中发挥的作用进行定量地比较和分析。[方法]首先,在不同空间分辨率下,通过机载lidar反演得到的冠…查看全部>>
[Objective]Based on the Random Forest method,forest canopy height estimation models corresponding to coniferous forest,broadleaf forest and mixed forest were established by synergizing ICESat-2 lidar data,Sentinel-1 SAR data,Sentinel-2 optical images and topographic data,and then the accuracy of the established models for different forest types were validated and compared.Meanwhile,the optimal variable set corresponding to each forest type and importance sco…查看全部>>
席志龙;邢艳秋;陈贵珍;徐华东;
ICESat-2 Sentinel-1 Sentinel-2 地形信息 森林类型 冠层高度 随机森林 最优变量
ICESat-2 Sentinel-1 Sentinel-2 topographic information forest type canopy height Random Forest optimal variable
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