A comparative study of radiometric correction methods for optical remote sensing imagery: the IRC<i>vs.</i>other image‐based C‐correction methods

Abstract

Remotely sensed data have inherent radiometric errors caused by atmospheric and topographic effects. In this paper, the performance of image‐based radiometric correction methods for optical satellite imagery is assessed by comparing variants of the traditional semiempirical C‐correction method with the physically‐based Integrated Radiometric Correction (IRC) method. High‐resolution digital elevation model (DEM) data were used for calculating the topographic parameters needed in both methods. The corrected reflectance obtained by using statistical parameters calculated for the whole of the study area (the general‐c approach) was investigated. In general, high correction accuracy (i.e. low correlation between surface reflectance and topography) was obtained. The IRC method yielded the highest accuracy for any band, indicating that application of this method could improve land‐use/land‐cover (LU/LC) classification. However, the general‐c approach showed a remarkable decrease in accuracy for all methods when applied to specific land‐cover types, particularly in visible bands. Subsequently, higher accuracy was obtained with correction parameters computed by using pixels within each land‐cover type (the specific‐c approach). The difference between these approaches demonstrates the dominant impact of surface features on the correction schemes. In the specific‐c approach, C‐correction gives a higher accuracy in the visible bands (C‐correction parameters tend to be overestimated because of strong haze) whereas IRC provides the best results in infrared bands (less haze).