Aerosol effect on the performance of a change detection technique

The performance of a change detection technique depends on the radiometric quality of Earth Observation (EO) data. The Cross-Correlation Analysis (CCA) as change detection technique requires the use of only one multi-spectral image at time T2 and a Land Cover/Land Use (LC/LU) map at time T1. The radiometric accuracy of the time T2 image can be improved applying an atmospheric correction to obtain a surface reflectance suitable for the appropriate analysis. In the atmospheric correction processing many atmospheric variables are involved. The comprehensive representation of the local aerosol during the sensor acquisition are provided by the aerosol optical thickness at 550 nm and the micro-physical properties of the aerosol. In this work, the CCA technique was applied to a recent Landsat 8 image for change detection. The CCA overall accuracy values obtained by selecting different aerosol types during the atmospheric correction performed by the OLI@CRI (OLI Atmospherically-Corrected Reflectance Imagery) algorithm (Bassani et al., 2016), are presented. The OLI@CRI algorithm was applied to the Landsat 8 image acquired August 10, 2014 on a protected Natura 2000 site in southern Italy. The microphysical properties of the aerosol provided by the AERONET station close to the site were used. The local aerosol was present in fine-dominated mode with absorption property similar to the water-soluble and dust-like. The results highlighted the effectiveness of the atmospheric correction providing an Overall Accuracy (OA) of 95.47±0.31% using AERONET data vs. an OA of 91.10±0.43% with no atmospheric correction. When basic components were considered in the OLI@CRI algorithm, the OA decreased in the case of absorbing and fine-mode aerosol (soot) and with coarse aerosol (dust-like and oceanic); while in case of water-soluble component (similar properties to the local aerosol) the quality of the results was preserved as attested by the overall accuracy (95.52±0.31).