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机载激光雷达(Light Detection And Ranging,LiDAR)技术对植被空间结构和地形的探测能力较强,在植被参数定量测量和反演方面具有显著优势。首先利用野外调查并结合高分辨率Geoeye-1影像数据,对黑河上游天涝池流域植被类型进行分类,提取研究区森林分布,然后结合0.5m×0.5m机载激光雷达(LiDAR)数据对森林结构参数(树高、冠幅、胸径和叶面积指数)进行反演,最后利用实际观测数据对反演结果进行验证。结果表明:机载激光雷达数据能够精确地反演森林结构参数,树高、冠幅、胸径和叶面积指数的实测值与估测值决定系数分别为0.98、0.84、0.57和0.73。本研究获得流域森林覆盖区域高精度树冠高度和叶面积指数空间分布图,同时分析了冠层高度和叶面积指数随高度的变化。本研究的结果为该流域分布式生态水文模型提供了重要的输入参数。
The technique of Light Detection And Ranging (LiDAR) has strong ability to detect the spatial structure and topography of vegetation, and has significant advantages in quantitative measurement and inversion of vegetation parameters. Firstly, field investigation and high-resolution Geoeye-1 image data were used to classify the vegetation types of the Tianlulogui basin in the upper reaches of the Heihe River. The forest distribution in the study area was extracted. Then, The structural parameters (tree height, crown width, diameter at breast height and leaf area index) were inverted. Finally, the actual observation data were used to verify the inversion results. The results show that airborne lidar data can accurately reflect forest structural parameters. The measured coefficient of forest height, crown width, DBH and leaf area index are 0.98, 0.84, 0.57 and 0.73 respectively. In this study, high-precision canopy height and leaf area index spatial distribution map of the forest coverage area was obtained. At the same time, the change of canopy height and leaf area index with height was analyzed. The results of this study provide important input parameters for the distributed eco-hydrological model.