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Comparison and evaluation of MODIS Multi-angle Implementation of Atmospheric Correction (MAIAC) aerosol product over South Asia.

Authors :
Mhawish, Alaa
Banerjee, Tirthankar
Sorek-Hamer, Meytar
Lyapustin, Alexei
Broday, David M.
Chatfield, Robert
Source :
Remote Sensing of Environment. Apr2019, Vol. 224, p12-28. 17p.
Publication Year :
2019

Abstract

Abstract The Multiangle Implementation of Atmospheric Correction (MAIAC) is a new generic algorithm applied to collection 6 (C6) MODIS measurements to retrieve Aerosol Optical Depth (AOD) over land at high spatial resolution (1 km). This study is the first evaluation of the MAIAC AOD from MODIS Aqua (A) and Terra (T) satellites between 2006 and 2016 over South Asia. The retrieval accuracy of MAIAC was assessed by comparing it to ground-truth AErosol RObotic NETwork (AERONET) AOD, as well as to AOD retrieved by the two operational MODIS algorithms: Dark Target (DT) and Deep Blue (DB). MAIAC AOD showed higher spatial coverage and retrieval frequency than either the DT or the DB AOD retrievals. The high spatial resolution of the MAIAC retrievals enhances the capability to distinguish aerosol sources and to determine fine aerosol features, such as wildfire smoke plumes and haze over complex geographical regions, and provides more retrievals in conditions that are cloudy or when the surface is partially covered by snow. In comparison to AERONET AOD, MAIAC AOD shows a better accuracy than both DT and DB AOD. A higher number of MAIAC-AERONET AOD matchups demonstrate the capability of MAIAC to retrieve AOD over varied surfaces, different aerosol types and loadings. Our results demonstrate high retrieval accuracy in term of the Expected Error (EE) (A/T, EE: 72.22%, 73.50%), and low root mean square error (A/T, RMSE: 0.148, 0.164), root mean bias (RMB) (A/T, RMB: 0.978, 1.049) and mean absolute error (MAE) (A/T, MAE: 0.098, 0.096). Moreover, MAIAC has a lower bias as a function of the viewing geometry and the aerosol type among the three retrieval algorithms. MAIAC performed well over bright and vegetated land surfaces, showing the highest retrieval accuracy over dense vegetation and particularly well in retrieving smoke AOD, yet it underestimated dust AOD. In conclusion, MAIAC's ability to provide AOD at high spatial resolution appears promising over South Asia, thus having advantage over contemporary aerosol retrieval algorithms for epidemiological and climatological studies. Capsule In comparison with MODIS DT and DB AOD, and AERONET AOD, MAIAC shows improved accuracy and lower bias over South Asia, as well as with greater spatial coverage. Graphical abstract Distribution of Aqua and Terra MODIS MAIAC, DT and DB AOD bias with respect to AERONET over South Asia. Unlabelled Image Highlights • Comprehensive evaluation of MAIAC AOD vs AERONET AOD and DT/DB AOD over South Asia • High-resolution MAIAC is capable to distinguish aerosol sources and fine feature. • MAIAC retrieval accuracy is higher than DT/DB with more accuracy over dark surface. • MAIAC has less sensitivity to variation in aerosol types across the seasons. • MAIAC best retrieve AOD for smoke events while underestimate AOD for dust. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00344257
Volume :
224
Database :
Academic Search Index
Journal :
Remote Sensing of Environment
Publication Type :
Academic Journal
Accession number :
135012537
Full Text :
https://doi.org/10.1016/j.rse.2019.01.033