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Forest Mean Height Extraction Based on the Low-densityAirborne LiDAR and CCD Data

  • The study generated forest canopy height model (CHM) using the low-density arborne Light Detection and Ranging (LiDAR) , it sketched the stand polygons combined with the high-resolution Charge Coupled Device (CCD) digital camera image, and extracted the stand mean height by the improved recognition algorithm.The results showed that the overall accuracy of the total valid data was 74.86%, The accuracy was 75.62% for Robinia pseudoacacia, and 74.74% for Pinus tabulaeformis. The precision of broad-leaved was slightly higher than that of the conifer species owing to the influence of the point cloud density. Therefore, low-density LiDAR with high resolution CCD data can quickly and accurately extract the stand mean height.
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  • [1] 庞 勇,李增元,陈尔学,等.激光雷达技术及其在林业上的应用[J]. 林业科学,2005,41(3):129-136

    [2] Popesc S C, Wynne R H, Nelson R F.et al.Estimating plot-level tree heights with lidar: local filtering with a canopy-height based variable window size[J]. Computers and Electronics in Agriculture, 2002, 37:71-95

    [3] Holmgren J,Nilsson M,Olsson H. et al.Estimation of tree height and stem volume on plots using airborne laser scanning[J]. Forest Science,2003,49(3):419-428

    [4] Maltamo M,Eerikainen K,Pitkanen J .et al.Estimation of timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions[J]. Remote Sensing of Environment,2004,90:319-330

    [5] Clark M L, Clark D B, Roberts D A. et al.Small-footprint lidar estimation of sub-canopy elevation and tree height in a tropical rain forest landscape[J]. Remote Sensing of Environment, 2004, 91:68-89

    [6] Thomas V,Treitz P. Mapping stand-level forest biophysical variables for a mixedwood boreal forest using lidar:an examanation of scanning desity[J]. Can J For Res, 2006 36:34-47

    [7] Stonge B, Jumelet J, Cobello M, et al.Measuring individual tree height using a combination of stereophotogrammetry and lidar[J]. Can J For Res, 2004, 34:2122-2130
    [8] 庞 勇,赵 峰,李增元,等.机载激光雷达平均树高提取研究[J]. 遥感学报, 2008,12(1):152-158

    [9] 赵 峰.机载激光雷达数据和数据相机影像林木参数提取研究 .北京:中国林科院资源信息研究所,2007

    [10] [10] 庞 勇,李增元,谭炳香,等.点云密度对机载激光雷达林分高度反演的影像[J].林业科学研究,2008,21(增刊):17-18

    [11] [11] 张彦林,冯仲科,杨伯钢,等.LIDAR技术在林业调查中的应用研究[J].林业资源管理,2007(6):73-77

    [12] [12] 冯仲科,杨伯钢,罗 旭,等.应用LIDAR技术预测林分蓄积量[J].北京林业大学学报,2007(增刊2):45-51

    [13] [13] 杨伯钢,冯仲科,罗 旭,等.LIDAR技术在树高测量上的应用与精度分析[J]. 北京林业大学学报,2007(增刊2):78-81

    [14] [14] 贾玉明,雷 鸣,侯红松.LIDAR机载激光雷达数据制作DEM原理分析[J].大众科技,2007(8):79-80

    [15] [15] 刘清旺,李增元,陈尔学,等.利用机载激光雷达数据提取单株木树高和树冠[J].北京林业大学学报,2008,30(6): 83-90

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Forest Mean Height Extraction Based on the Low-densityAirborne LiDAR and CCD Data

Abstract: The study generated forest canopy height model (CHM) using the low-density arborne Light Detection and Ranging (LiDAR) , it sketched the stand polygons combined with the high-resolution Charge Coupled Device (CCD) digital camera image, and extracted the stand mean height by the improved recognition algorithm.The results showed that the overall accuracy of the total valid data was 74.86%, The accuracy was 75.62% for Robinia pseudoacacia, and 74.74% for Pinus tabulaeformis. The precision of broad-leaved was slightly higher than that of the conifer species owing to the influence of the point cloud density. Therefore, low-density LiDAR with high resolution CCD data can quickly and accurately extract the stand mean height.

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