Effect of image radiometric correction levels of Landsat images to the land cover maps resulted from maximum likelihood classification

Abstract

Radiometric correction of remote sensing images is required to improve the quality of image pixel values and provide a measurable physical unit of each pixel. Selection of the appropriate image radiometric and atmospheric correction level defines the success of any remote sensing-based mapping applications. This study aims to assess the effects of radiometric correction levels applied to Landsat 8 (Operational Land Imager, OLI) image acquired in 2018 to the results of the land cover classification using the Maximum Likelihood Classifier (MLC). The image was corrected into four levels of radiometric and atmospheric correction; no correction (digital number), at-sensor radiance, at-sensor reflectance (top of atmosphere, ToA), and at-surface reflectance (bottom of atmosphere, BoA). A set of classification training sample covering five land cover classes (mangroves, inland vegetation, exposed soil, built-up area, and water body) was selected from the image. To ensure fair class comparison, the number of training sample were set to be proportional to the area of targeted classes. The results of this study show that there is no difference in the classification results of each level of correction, both in the area and distribution of the classes. This finding indicates that MLC result is invariable of image correction level.