Large-scale forest height remote sensing inversion method considering ecological partition

The invention relates to a large-scale forest height remote sensing inversion method considering ecological partition. The method comprises the following steps: firstly, combining forest ecological partition data with a spaceborne photon counting laser radar, an optical image, topographic data, meteorological data and latitude and longitude data, then creating a multi-source remote sensing data nonparametric tree height model considering different ecological partitions and different forest types, and estimating the continuous forest height of the whole research area space by using the model. Ecological factors related to forest growth are comprehensively considered, the remote sensing-ecological coupling forest height estimation model is obtained by incorporating ecological partition factors into forest height modeling, and help can be provided for generating forest height space information from global and regional scales to more local scales. 本发明涉及一种顾及生态分区的大尺度森林高度遥感反演方法。首先将森林生态分区数据与星载光子计数激光雷达、光学影像、地形数据、气象数据和