Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 11, issue 10
Articles | Volume 11, issue 10
https://doi.org/10.5194/amt-11-5741-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-5741-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 10
Research article
 | 
18 Oct 2018
Research article |  | 18 Oct 2018

MODIS Collection 6 MAIAC algorithm

Alexei Lyapustin, Yujie Wang, Sergey Korkin, and Dong Huang

Viewed

Total article views: 11,170 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
7,642 3,403 125 11,170 224 305
  • HTML: 7,642
  • PDF: 3,403
  • XML: 125
  • Total: 11,170
  • BibTeX: 224
  • EndNote: 305
Views and downloads (calculated since 17 May 2018)
Cumulative views and downloads (calculated since 17 May 2018)

Viewed (geographical distribution)

Total article views: 11,170 (including HTML, PDF, and XML) Thereof 10,817 with geography defined and 353 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 27 Nov 2025
Download
Short summary
MAIAC algorithm used for the MODIS C6 processing is described. MAIAC combines time series analysis and pixel/image-based processing to improve the accuracy of cloud detection, aerosol retrievals and atmospheric correction. MAIAC offers an interdisciplinary suite of atmospheric, land surface and snow products. Due to generally high quality, high resolution and high coverage, MAIAC AOD and surface reflectance/BRDF have been widely used for air quality and land research and applications.
Read more
Share