针对ICESat-2 ATL08产品含有较多噪声光子和树高粗差的问题，设计了利用光子数量、光束能量和地表覆盖等特性进行光子滤波和粗差剔除的方法；研究了从高分辨率多光谱数据各波段反射参数和提取的NDVI、RVI、SAVI、MSAVI、PVI植被指数与激光测高数据之间的相关关系，对比分析了多元回归和随机森林模型反演的有效性和精度。结果表明，随机森林模型可以获得较高的树高反演精度，以浙江省杭州市临安区输电走廊进行的反演实验获得了RMSE=2.84 m的结果，结合电力数据制作的树高隐患图可以为输电设施安全隐患排查提供辅助决策。
Aiming at the problem that ICESat-2 ATL08 product contains a lot of noise photons and gross errors of tree height, a method of photon filtering and gross errors elimination was designed by using a series of characteristics such as photon number, beam energy and ground coverage; The correlations of reflection parameters in each band with NDVI, RVI, SAVI, MSAVI, PVI vegetation indexes extracted from high-resolution multispectral data and with laser altimetry data were studied, and the effectiveness and accuracy of multiple regression and random forest model inversion were compared and analyzed. Study results showed that the random forest model can obtain higher inversion accuracy of tree height. The inversion experiment carried out in the transmission corridor of Lin' an District, Hangzhou City, Zhejiang Province obtained the result of RMSE=2.84 m. The tree height hidden danger map produced by combining the power data can provide auxiliary decision-making for the hidden danger investigation of transmission facilities.
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