Algorithm for image fusion based on DEM and remote sensing image

Terrain roughness and vegetation growth are important influence factors of environment. But it is very difficult to describe the terrain roughness in remote sensing image. Although with the launch of TERRA, Moderate resolution Imaging Spectroradiometer (MODIS), with abundant information, quickly acquiring data and wide range of coverage, is a new data for classication of land area. Considering terrain is still very important problem. This study considered the characteristics of Zhejiang land planting. The digital slope image derived from the DEM map and multitemporal MODIS were used for the purpose of improving the classification accuracy of MODIS in large hilly region. Two methods have been employed till now. One is visual interpretation using digital images. and the other is the automated extraction of landform characteristics from DEM. Thus, the results obtained from the first method are difficult for future use. As to the second method, it is difficult to get detailed classifications for example. to distinguish a valley plain from an open plain by using DEM alone due to the complex nature in landform characteristics. In fact. DEM and digital image contain different. yet complementary. information related to landform features. Therefore. a new method to integrate landform information of both DEM and MODIS and NOAA-AVHRR image by digitizing signing lines in MODIS and NOAA-AVHRR image is presented in this paper. With this approach. different results of basic landforms were successfully classified and mapped automatically in Zhejiang Province. In addition. the spatial variability of accuracy in classification was also evaluated by sampling points based on an application of Globe positioning system (GPS).