Remote sensing is a key technology for the monitoring of land cover and land use change and the retrieving of bio-physical parameters of vegetation in mountainous area.However,due to the obscuring by terrain relief,the mountainous shadows in the optical remote sensing images have brought great difficulties for the remote sensing applications in mountain area.In this paper,a new method for the restoration of information obscured by mountain shadows was proposed.This method took advantage of the characteristics of MODIS Aqua and Terra,whose time of passing territory are morning and afternoon separately,to compose the information sources for the shadow area on high resolution images.Then the homogenous pixels in both MODIS and TM were selected based on the angle filter,cloud filter and homogenous filter.Based on the hypothesis that the statistics relationship exists for the homogenous pixels between MODIS and TM, the proposed method further built up a regression tree model for the sun-light area,and then used the built model to predict information of the shadow area in Landsat TM images.According to the comparison of the restoration result between the proposed method and SCS+C model,the method in this paper can better reflect the detail information of the shadow area and simultaneously preserve the information of sun-light area well.With the development of new high spatial resolution sensors such as Sentinel-2A/B and Landsat 8 Operational Land Imager,using multi-sources data to restore information of mountainous shadow area is a new development tendency,and the proposed method in this paper can be used as a reference for those similar satellite datasets.