Atmospheric and Radiometric Normalization of Satellite Images for Landscape-Level Environmental Monitoring: The Case of The Mediterranean Region

Abstract

Ensuring atmospheric and radiometric consistency among the frameworks of satellite data used in regional studies is a critical requirement for change detection studies employed in regional planning monitoring. The purpose of this article is to provide a guide for the necessary atmospheric correction and radiometric normalization processes required in generating environmental data at the landscape level for physical planning. In this context, adjustments were made to remove atmospheric effects before merging multiple ASTER satellite image frames used in a project supported by TÜBİTAK, covering landscape-level environmental inventory and monitoring. The Dark Object Subtraction method with the Cos(t) model was utilized in the atmospheric correction process. Subsequently, separate regression relationships were computed for each band by considering overlapping areas on adjacent tracks of ASTER data, and radiometric normalization was performed based on these regression equations. Thus, differences between satellite images used in monitoring land changes and affecting multiple frames were minimized.