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  • 软件名称:基于机载激光雷达数据的森林结构参数反演
  • 软件大小: 0.00 B
  • 软件评级: ★★★
  • 开 发 商: 李文娟,赵传燕,别强,高婵婵,高云飞
  • 软件来源: 《遥感技术与应用》
  • 解压密码:www.gissky.net

资源简介

摘要: 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0.5 m×0.5 m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。 关键词: 机载激光雷达;  植被结构参数;  黑河上游;  遥感反演     Abstract: Forest structure parameters are very important inputs for ecological and hydrological models.The spatial distribution of these parameters is urgently needed by distributed eco-hydrological models.It is a great success in obtaining vegetation parameters using airborne LiDAR(Light Detection and Ranging),which has the powerful detection ability of forest spatial structure.This paper selected Tianlaochi catchment of the upper reaches of Heihe River as the study area and forests as study object in the study area.First,we derived a vegetation classification map by high resolution images data(Geoeye-1)in the study area.And then,forest structural parameters(i.e.,canopy height,crown width,diameter at breast height(DBH),leaf area index(LAI))were retrieved based on airborne LiDAR data.Finally,the retrieved results were validated by field investigation.The results show that it is a good way to estimate the forest structural parameters using LiDAR data.There were good correlations between the measured value and estimated value(i.e.,canopy height,crown width,and LAI).Correlation coefficients(R2)were 0.98,0.84,and 0.73,respectively.In addition,we analyzed the variation of average canopy height and LAI with the increase of elevation.This study could draw the conclusion that airborne LiDAR technology is better way to retrieve forest structural parameters than passive remote sensing,but it still needs to be improved.The retrieved parameters will provide inputs for the distributed eco\|hydrological model built in the subsequent research.

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