STATISTICAL STUDY OF MODIS ALGORITHMS IN ESTIMATING AEROSOL OPTICAL DEPTH OVER THE CZECH REPUBLIC

• Main Authors: Ibrahim, Saleem, Halounová, Lena
• Format: Article in Journal/Newspaper
• Language: English
• Published: Czech Technical University in Prague, Faculty of Civil Engineering 2019
• Subjects: AERONET; AOD; DB; DT; DTB; MODIS; Remote sensing; Aerosol Robotic Network
• Online Access: https://ojs.cvut.cz/ojs/index.php/cej/article/view/8787

As a result of the rapid development of remote sensing techniques and accurate satellite observations, it has become customary to use these technologies in ecological and aerosols studies on a regional and global level. In this paper, we analyse the performance of three Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms in estimating Aerosol Optical Depth (AOD) in the Czech Republic to gain knowledge about their accuracy and uncertainty. The Dark Target (DT), the Deep Blue (DB), and the merged algorithm (DTB) of the MODIS latest collection 6.1 Level 2 aerosol products (MOD04_L2) were tested by comparing its results with the measurements of Aerosol Robotic Network (AERONET) Level 3 Version 2.0 ground station at Brno airport. The DT algorithm is compatible the best with AERONET observations with a correlation coefficient (R = 0.823), retrievals falling within the EE envelope (EE% = 82.67%), root mean square error (RMSE = 0.059), and mean absolute error (MAE = 0.044). The DTB algorithm provided close results of the DT algorithm but with less accuracy, on the other hand the DB algorithm has the lowest accuracy between all, but this algorithm was able to provide a bigger sample size than the other two algorithms.