机载林业探测大光斑激光雷达系统的设计与应用
收稿日期: 2018-06-01
修回日期: 2018-06-29
网络出版日期: 2020-09-25
基金资助
陆地生态系统碳监测卫星地面应用及反演关键技术攻关(2016k-10);植被与环境变化国家重点实验室开放课题(LVEC-2017kf02)
Design and Application of Forest Detecting Based on Airborne Large-Footprint LiDAR System
Received date: 2018-06-01
Revised date: 2018-06-29
Online published: 2020-09-25
激光雷达以其独特的穿透能力在大面积的林业探测中越来越受到重视。以国家林业局调查规划设计院和北京遥测技术研究所共同设计研发的大光斑激光雷达系统为基础,详细介绍了该系统的工作原理、模块组成、设备安装、参数设计、数据处理等,并对该系统的飞行试验数据进行了分析,结果显示,该系统下得到的波形数据可对建筑、农田、森林等地物进行精确地刻画。进一步利用Matlab 2014b软件对大光斑激光雷达回波波形估测森林样地最大冠层高度,并利用与之对应的小光斑激光雷达数据提取的森林最大冠层高度对比,总体平均精度达到89.24%。利用SPSS软件做配对样本T检验,结果表明,该系统下获得的大光斑波形数据估测的森林最大冠层高度与小光斑估测的森林冠层高度的差异显著性为0.366,大于0.05,无明显差异,直接证明了大光斑激光雷达估测森林最大冠层高度的独特性能。因此,在未来的林业探测中,可用该系统对大面积的森林资源进行探测,为大面积估测林分最大高、平均高、郁闭度、生物量、蓄积量、叶面积指数等一系列森林参数创造了条件。
吴发云 , 高显连 , 潘超 , 孙忠秋 , 王丽东 , 刘迎春 . 机载林业探测大光斑激光雷达系统的设计与应用[J]. 林草资源研究, 2018 , 0(4) : 125 -132 . DOI: 10.13466/j.cnki.lyzygl.2018.04.020
LiDAR(Light Laser Detection and Ranging)are drawing more attention with its unique penetration for the detection of large areas of forest.Based on the large-footprint LiDAR system designed by Academy of Forest Inventory and Planning of State Forestry Administration and Beijing Telemetry Technology Research Institute,this paper introduced the working principle of the system,module composition,equipment installation,parameter design,data processing,etc.,and one flight test data of the system was analyzed.The results show that the waveform data obtained through this system can describe buildings,farmland and forest accurately.In addition,compared with the data collected by the small-footprint LiDAR,the overall average accuracy is 89.24%,which proves this system has a high precision in the description of maximum crown height.The result of paired sample T test with no significance of difference also proves the data obtained through the system has a unique performance of estimation in maximum canopy height of the forest.Therefore,the large-footprint LiDAR system can be used to estimate large areas of forest for maximum height,average height,crown density,biomass,volume,leaf area index and a series of forest parameters in the detection of forest in the future.
Key words: forestry; airborne; large-footprint LiDAR; design; application; maximum height
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