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An Improved Method for Retrieving Aerosol Optical Depth Using Gaofen-1 WFV Camera Data.
- Source :
- Remote Sensing; 1/15/2021, Vol. 13 Issue 2, p280, 1p
- Publication Year :
- 2021
-
Abstract
- The four wide-field-of-view (WFV) cameras aboard the GaoFen-1 (GF-1) satellite launched by China in April 2013 have been applied to the studies of the atmospheric environment. To highlight the advantages of GF-1 data in the atmospheric environment monitoring, an improved deep blue (DB) algorithm using only four bands (visible–near infrared) of GF-1/WFV was adopted to retrieve the aerosol optical depth (AOD) at ~500 m resolution in this paper. An optimal reflectivity technique (ORT) method was proposed to construct monthly land surface reflectance (LSR) dataset through converting from MODIS LSR product according to the WFV and MODIS spectral response functions to make the relationship more suitable for GF-1/WFV. There is a good spatial coincidence between our retrieved GF-1/WFV AOD results and MODIS/Terra or Himawari-8/AHI AOD products at 550 nm, but GF-1/WFV AOD with higher resolution can better characterized the details of regional pollution. Additionally, our retrieved GF-1/WFV AOD (2016–2019) results showed a good agreement with AERONET ground-based AOD measurements, especially, at low levels of AOD. Based on the same LSR dataset transmitted from 2016–2018 MODIS LSR products, R<subscript>ORT</subscript> of 2016–2018 and 2019 GF-1/WFV AOD retrievals can reach up to 0.88 and 0.94, respectively, while both of RMSE<subscript>ORT</subscript> are smaller than 0.13. It is indicated that using the ORT method to deal with LSR information can make GF-1/WFV AOD retrieval algorithm more suitable and flexible. [ABSTRACT FROM AUTHOR]
- Subjects :
- AEROSOLS
CAMERAS
ARTIFICIAL satellite launching
COINCIDENCE
POLLUTION
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 13
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 148251972
- Full Text :
- https://doi.org/10.3390/rs13020280