像元分解模型的植被覆盖度遥感估算

Remote sensing estimation of vegetation coverage based on sub-pixel analysis model

为了提高植被覆盖度遥感估算方法的精度,该文针对置信度方法和空间克里金插值方法各自存在的问题,基于线性像元二分模型,分别采用置信度方法和空间克里金插值方法计算推导,确定像元二分模型中两个重要参数NDVIveg和NDVIsoil,实现估算植被覆盖度,并对两种方法进行对比分析,同时提出方法中存在的问题以及模型的优化改进方向。

In order to improve the RS estimation accuracy of vegetation coverage,the paper used conventional confidence algorithm and spatial Kriging interpolation algorithm respectively to determine two important parameters of NDVIvegand NDVIsoilof the linear dimidiate pixel model for estimating the vegetation coverage,based on the inadequacy analysis of the above mentioned algorithms.Finally,the two algorithms were comparatively analyzed and the direction of the future research and development trends were discussed.