@Article{MartinsLyaCarBarNov:2017:VaHiMA,
               author = "Martins, Vitor Souza and Lyapustin, A. and Carvalho, Lino Augusto 
                         Sander de and Barbosa, Cl{\'a}udio Clemente Faria and Novo, Evlyn 
                         M{\'a}rcia Le{\~a}o de Moraes",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {NASA 
                         Goddard Space Flight Center} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Validation of high-resolution MAIAC aerosol product over South 
                         America",
              journal = "Journal of Geophysical Research: Atmospheres",
                 year = "2017",
               volume = "122",
               number = "14",
                pages = "7537--7559",
             abstract = "Multiangle Implementation of Atmospheric Correction (MAIAC) is a 
                         new Moderate Resolution Imaging Spectroradiometer (MODIS) 
                         algorithm that combines time series approach and image processing 
                         to derive surface reflectance and atmosphere products, such as 
                         aerosol optical depth (AOD) and columnar water vapor (CWV). The 
                         quality assessment of MAIAC AOD at 1 km resolution is still 
                         lacking across South America. In the present study, critical 
                         assessment of MAIAC AOD550 was performed using ground-truth data 
                         from 19 Aerosol Robotic Network (AERONET) sites over South 
                         America. Additionally, we validated the MAIAC CWV retrievals using 
                         the same AERONET sites. In general, MAIAC AOD Terra/Aqua 
                         retrievals show high agreement with ground-based measurements, 
                         with a correlation coefficient (R) close to unity (RTerra:0.956 
                         and RAqua: 0.949). MAIAC accuracy depends on the surface 
                         properties and comparisons revealed high confidence retrievals 
                         over cropland, forest, savanna, and grassland covers, where more 
                         than 2/3 (~66%) of retrievals are within the expected error (EE = 
                         ±(0.05 + 0.05 × AOD)) and R exceeding 0.86. However, AOD 
                         retrievals over bright surfaces show lower correlation than those 
                         over vegetated areas. Both MAIAC Terra and Aqua retrievals are 
                         similarly comparable to AERONET AOD over the MODIS lifetime (small 
                         bias offset ~0.006). Additionally, MAIAC CWV presents quantitative 
                         information with R ~ 0.97 and more than 70% of retrievals within 
                         error (±15%). Nonetheless, the time series validation shows an 
                         upward bias trend in CWV Terra retrievals and systematic negative 
                         bias for CWV Aqua. These results contribute to a comprehensive 
                         evaluation of MAIAC AOD retrievals as a new atmospheric product 
                         for future aerosol studies over South America.",
                  doi = "10.1002/2016JD026301",
                  url = "http://dx.doi.org/10.1002/2016JD026301",
                 issn = "2169-8996 and 2169-897X",
             language = "en",
           targetfile = "
                         
                         Martins_et_al-2017-Journal_of_Geophysical_Research-_Atmospheres.pdf",
        urlaccessdate = "27 abr. 2024"
}