Analysis of the ASTER Image Topographic Correction Method in Complex Mountain Areas

Abstract

The phenomenon of “anisotropic reflection” caused by gradient and aspect changes in complex mountain areas has large disturbance on the spectral information of ground feature in remote sensing images, which will further affect the inversion of surface information based on the spectral characteristics of ground feature. Topographic correction is an effective means to weaken the topographical effect and improve the inversion accuracy of spectral reflectance of remote sensing images. Ten topographic correction methods, such as Teillet regression, VECA, Cosine, Cosine-B, Cosine-C, Cosine-T, C, SCS, SCS+C and Minnaert, were used to conduct topographic correction of ASTER remote sensing images in the complex mountain areas of Qulong, and visual effects, statistical results and spectral changes of ground features were used to quantitatively evaluate the correction results. The results show that the topographic effect in the study area is weakened to different degrees. Teillet-regression correction model has the best correction effect and the topographic effect is weakened to the maximum extent. VECA, cosine-c, and Minnaert calibration models followed. Teillet-regression model can be used as topographic correction model in complex mountain areas.