A simple empirical topographic correction method for ETM plus imagery

A simple topographic correction approach, the Variable Empirical Coefficient Algorithm (VECA), was developed using theoretical and statistic analyses of the radiance values of remotely sensed data acquired for rugged terrain and the cosine of the solar illumination angle (cos i). Visual comparison and statistical analysis were used for evaluation of the proposed algorithm and the performance of the VECA approach was compared with 10 commonly used methods. The test site selected for this study is located on the south hill of the Qinling Mountain in Shanxi province, China, and the remotely sensed data used were from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) images. The results indicate that the Cosine-T, Cosine-C, sun-canopy-senor (SCS) and Cosine-b correction have the problem of overcorrection, and the other corrections can be classed into three ranks: the VECA, b correction and C models performed the best, followed by the Teillet-regression correction model, and the SCS+C, Minnaert and Minnaert-SCS corrections performed the worst. The proposed VECA correction and the b correction are the most capable of removing the topographic effects of the ETM+ image. The VECA is not only simple in theory but also easy to operate, indicating that the VECA is an effective topographic correction tool in remote sensing techniques.