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机载Lidar数据的农作物覆盖度及LAI反演
引用本文:崔要奎,赵开广,范闻捷,徐希孺.机载Lidar数据的农作物覆盖度及LAI反演[J].遥感学报,2011,15(6):1282-1294.
作者姓名:崔要奎  赵开广  范闻捷  徐希孺
作者单位:北京大学 遥感与地理信息系统研究所,北京 100871;达勒姆市杜克大学 全球变化中心,北卡罗来纳州, 27708;北京大学 遥感与地理信息系统研究所,北京 100871;北京大学 遥感与地理信息系统研究所,北京 100871
基金项目:国家自然科学基金(编号: 40734025, 40871186);国家高技术研究发展计划(863计划) (编号: 2009AA12Z143);国家重点基础研究发展计划(973计划) (编号: 2007CB714402);中国科学院西部行动计划(二期)项目“黑河流域遥感—地面观测同步试验与综合模拟平台建设”(编号:KZCX2-XB2-09)
摘    要:虽然Lidar点云数据已被广泛应用于获取森林各项结构参数,但这些方法并不适合于低矮的灌丛、林地和农作物。本文以玉米为研究对象,提出利用机载Lidar点云数据的强度信息和全波形数据中的距离与扫描天顶角信息,反演农作物覆盖度和LAI的方法。在黑河进行的飞行实验和地面验证表明,该方法具有较高精度,也表明Lidar在低矮自然植被监测和农业应用上有较大潜力。

关 键 词:Lidar  点云  全波形  农作物  覆盖度  LAI
收稿时间:2010/11/17 0:00:00
修稿时间:2011/2/18 0:00:00

Retrieving crop fractional cover and LAI based on airborne Lidar data
CUI Yaokui,ZHAO Kaiguang,FAN Wenjie and XU Xiru.Retrieving crop fractional cover and LAI based on airborne Lidar data[J].Journal of Remote Sensing,2011,15(6):1282-1294.
Authors:CUI Yaokui  ZHAO Kaiguang  FAN Wenjie and XU Xiru
Institution:Institute of RS and GIS, Peking university, Beijing 100871, China;Center on Global Change, Duke University, Durham, NC 27708, USA;Institute of RS and GIS, Peking university, Beijing 100871, China;Institute of RS and GIS, Peking university, Beijing 100871, China
Abstract:Light detection and ranging (Lidar) point cloud data contains the information of the 3D coordinate and intensity, which can be applied to acquire the height of crown, fractional cover etc. in high-statue vegetation, such as the forest. Meanwhile, with the improvement of data storage capacity and processing speed, small footprint airborne Lidar is able to store the entire refl ected waveform through digitally sampling, which expands the application of Lidar. However, the methods used in forest are not suitable for shrubs, crops and other low canopies. In this paper, we choose the cron as the study object, and propose a crop fractional cover and leaf area index (LAI) retrieval method using airborne Lidar intensity of ground hits and the distance and zenith angle information contained in waveforms data. Relevant fi ght experiment and ground measurements in Heihe indicate that the method is reliable, and the experiment also validates the great potential for Lidar to be applied to monitor low natural vegetation in agriculture.
Keywords:Lidar  point cloud  full waveform  crop  fractional cover  LAI
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