周梦维, 柳钦火, 刘 强, 肖 青. 基于机载小光斑全波形LIDAR的作物高度反演[J]. 农业工程学报, 2010, 26(8): 183-188.
    引用本文: 周梦维, 柳钦火, 刘 强, 肖 青. 基于机载小光斑全波形LIDAR的作物高度反演[J]. 农业工程学报, 2010, 26(8): 183-188.
    Inversion for crop height by small-footprint-waveform Airborne LIDAR[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(8): 183-188.
    Citation: Inversion for crop height by small-footprint-waveform Airborne LIDAR[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(8): 183-188.

    基于机载小光斑全波形LIDAR的作物高度反演

    Inversion for crop height by small-footprint-waveform Airborne LIDAR

    • 摘要: 为了填补利用激光雷达反演作物冠层高度的空白,本文以全波形激光雷达发射与回波波形的高斯性为理论基础,首先通过对波形的拟合,实现作物与土壤波形的剥离,然后确定回波波形上各关键点,最后结合作物冠层结构的特征获得作物冠层高度。验证结果表明:反演作物冠层高度的绝对误差在0.06 m以内,相对误差小于5.2%。该方法对于反演其他植被结构参数也具有重要的借鉴意义。

       

      Abstract: Due to limited vertical resolution, the waveform of vegetation whose height is relatively low will superpose on soil waveform. Therefore, LIDAR full-waveform data is mainly used in forestry, but no research in the crops. In this paper, in order to derive crop height, a gaussian decomposition algorithm based on transmitting waveform was adopted to distinguish the crop waveform from soil waveform, and to extract peak location and pulse width from raw waveform data. The method was proved a reliable and high accurate decomposition algorithm. Moreover, the decomposition algorithm lays the proper foundation for obtaining other crop biophysical parameters.

       

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