Volume XLII-3/W9
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W9, 181–185, 2019
https://doi.org/10.5194/isprs-archives-XLII-3-W9-181-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W9, 181–185, 2019
https://doi.org/10.5194/isprs-archives-XLII-3-W9-181-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  25 Oct 2019

25 Oct 2019

VALIDATION OF AEROSOL PRODUCTS FROM ESA/AATSR OVER CHINA AND AOD FUSION BASED ON UNCERTAINTIES

Y. N. Wen1,2, Y. H. Che1,2, J. Guang1, Y. Q. Xie1,2, Z. Shi1,2, Y. Zhang1, and Z. Q. Li1 Y. N. Wen et al.
  • 1State Environmental Protection Key Laboratory of Satellite Remote Sensing, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China

Keywords: Aerosol, Validation, Fusion, ADV, ORAC, SU, Uncertainty

Abstract. Aerosols play an important role in climate changes and environmental changes as well as on human health. ADV v3.11, ORAC v4.10, and SU v4.32 was three new versions of Advanced Along-Track Scanning Radiometer (AATSR) aerosol datasets which are published on Climate Change Initiative (CCI). In order to evaluate the accuracy of three AATSR aerosol optical depth (AOD) datasets, and to improve the spatial coverage and accuracy of AATSR AOD dataset, this study completed two works: the first part is validated the accuracy of three AOD datasets; the second part is fused three AATSR AOD datasets based on uncertainty of each dataset. After comparing with AERONET and CARSNET ground-based data over China, results show that the root-mean-square error (RMSE) for ADV v3.11, ORAC v4.10, SU v4.32 and fused AOD are 0.22, 0.17, 0.18, 0.17 respectively.