Document Type : Original Article
Department of Geomatics, Computer Science and Mathematics, Hochschule für Technik Stuttgart, Germany
Forest Stewardship Council International, Bonn, Germany
Satellite remote sensing aerosol monitoring products are readily available but limited to regional and global scales due to low spatial resolutions making them unsuitable for city-level monitoring. Freely available satellite images such as Sentinel -2 at relatively high spatial (10m) and temporal (5 days) resolutions offer the chance to map aerosol distribution at local scales. In this study, we retrieve Aerosol Optical Depth (AOD) from Sentinel -2 imagery for the Munich region and assess the accuracy against ground AOD measurements obtained from two Aerosol Robotic Network (AERONET) stations. Sentinel -2 images with less than 30% cloud cover acquired between January and October 2018 were used in the study and contemporaneous AERONET Level 1.5 AOD data used to validate the AOD retrievals. Since aerosol distribution and properties exhibit high temporal variations, only satellite data and AERONET measurements acquired within 15 minutes were considered for validation and statistical analysis. Sen2Cor, iCOR and MAJA algorithms which retrieve AOD using Look-up-Tables (LUT) pre-calculated using radiative transfer (RT) equations and SARA algorithm that applies RT equations directly to satellite images were used in the study. Sen2Cor, iCOR and MAJA retrieved AOD at 550nm show strong consistency with AERONET measurements with average correlation coefficients of 0.91, 0.89 and 0.73 respectively. However, MAJA algorithm gives better and detailed variations of AOD at 10m spatial resolution which is suitable for identifying varying aerosol conditions over urban environments at a local scale.