Comparison of topographic corrections for land‐cover classification in mountainous terrain

To overcome the food and water shortages and optimize the land use, remote sensing techniques and satellite image processing have utilized our demands. However, with limitations in image processes, the use of such techniques will need further development to overcome related constraints. Shadows, occurred on the opposite side of objects, result from topography and different angles of the emitting light source is one of these limitations. Several topographic correction methods are proposed based on the properties of ground coverage. To suggest and compare methods for imagery topography, this study uses Cosine Correction, C-Correction, Statistical Empirical Correction, and finally the Minnaert Correction. The study area used to compare the introduced methods is located in North West of Isfahan (Ardestan), Iran. The current report has used OLI sensors (LANDSAT 8) combined with ASTER global digital elevation data. After implementing topographic corrections, by optimal index OIF, images are processed. Based on the unsupervised method and the study region, results based on optimal arrangement bands are introduced as a suitable classification. In conclusion, based on imagery and statistical data from the topography corrections, Minnaret shows the most exceptional topographical correction classification for the chosen studied region.

 

Keywords: aster, c-correction, cosine correction, Isfahan, Landsat-8, land management, Minnaert, oli, topographic correction, unsupervised classification.