A Perspective on Topographic Correction Methods on Satellite Images

Abstract

The presence of atmospheric and topographic effects in satellite images is inevitable, which may reduce image information content. A standard procedure for improving satellite images is topographic and atmospheric correction during preprocessing. The topographic effect on satellite images is not an error but a distortion caused by solar and surface geometries. Surfaces facing toward the Sun tend to be bright, whereas surfaces facing away from the Sun are usually dark. This effect is strongly related to the solar surface incident angle, and it is one of the main factors that increases the spectral variation in satellite images. The objective of this paper is to review the commonly available methods for topographic correction. The spectral variation may reduce the accuracy of processes, such as surface topographical classification, which can limit the capability of autonomous remote sensing applications. Many have tried to reduce the effect of topography and achieved great success; however, most methods are complicated and require many parameters. The topographic correction methods can be categorized into two groups: empirical and physical methods. In this paper, a total of six empirical methods were reviewed, including Cosine correction (CC), Statistical-Empirical (SE) correction, Minnaert (MIN) correction, Shepherd and Dymond’s (SD) Correction Method, Sun-canopy-sensor (SCS) Models and Path Length Correction (PLC) Method. The algorithms and models used in the physical topographical correction method were also discussed. Parameters related to the topographic correction algorithm were reviewed in detail. This paper reviewed a total of six common topographic correction methods and seven assessment methods for topographic correction.