Radiometric Correction of Landsat 8 Imagery Using Open-Source Software and its Impact on Spectral Index Derivation: A Case Study in the Southern Expanded Metropolitan Microregion of Espírito Santo State, Brazil

Abstract. Orbital imagery acquired in the optical spectrum is inherently subject to geometric and radiometric errors. These inaccuracies stem from instrumental imperfections, imaging limitations, and various effects that influence the signal from the information source (targets) to the sensor. Most of these errors can be mitigated through radiometric calibration followed by atmospheric correction. Rigorous atmospheric correction requires data that allow for the estimation of scattering and absorption by atmospheric constituents at different wavelengths. Considering this context and aiming to enable the effective use of Landsat 8 satellite imagery (Level 1 processing) for spectral index-based change assessment, this study proposes a method based on radiometric data calibration followed by atmospheric correction using the 6S radiative transfer model, as implemented in the i.atcorr tool of the Geographic Resources Analysis Support System (GRASS GIS). Results, evaluated qualitatively and quantitatively, indicate that atmospheric correction using i.atcorr provides reliable outcomes only for the visible-red, near infrared, and shortwave infrared bands when assessing changes between two distinct epochs. For applications requiring the use of bands at the shortest wavelengths (blue and visible-green), which are more susceptible to atmospheric scattering effects, it is recommended to use Level 2 corrected images, processed by the LaSRC algorithm and provided by the U.S. Geological Survey (USGS).