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Remote Sens. 2017, 9(1), 89;

High Resolution Aerosol Optical Depth Retrieval Using Gaofen-1 WFV Camera Data

State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
The Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China
College of Information Science and Engineering, Wuchang Shouyi University, Wuhan 430064, China
Authors to whom correspondence should be addressed.
Academic Editors: Yang Liu, Jun Wang, Omar Torres, Richard Müller and Prasad S. Thenkabail
Received: 5 December 2016 / Revised: 10 January 2017 / Accepted: 15 January 2017 / Published: 19 January 2017
(This article belongs to the Special Issue Remote Sensing of Atmospheric Pollution)
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Aerosol Optical Depth (AOD) is crucial for urban air quality assessment. However, the frequently used moderate-resolution imaging spectroradiometer (MODIS) AOD product at 10 km resolution is too coarse to be applied in a regional-scale study. Gaofen-1 (GF-1) wide-field-of-view (WFV) camera data, with high spatial and temporal resolution, has great potential in estimation of AOD. Due to the lack of shortwave infrared (SWIR) band and complex surface reflectivity brought from high spatial resolution, it is difficult to retrieve AOD from GF-1 WFV data with traditional methods. In this paper, we propose an improved AOD retrieval algorithm for GF-1 WFV data. The retrieved AOD has a spatial resolution of 160 m and covers all land surface types. Significant improvements in the algorithm include: (1) adopting an improved clear sky composite method by using the MODIS AOD product to identify the clearest days and correct the background atmospheric effect; and (2) obtaining local aerosol models from long-term CIMEL sun-photometer measurements. Validation against MODIS AOD and ground measurements showed that the GF-1 WFV AOD has a good relationship with MODIS AOD (R2 = 0.66; RMSE = 0.27) and ground measurements (R2 = 0.80; RMSE = 0.25). Nevertheless, the proposed algorithm was found to overestimate AOD in some cases, which will need to be improved upon in future research. View Full-Text
Keywords: Gaofen-1; aerosol optical depth; deep blue; Wuhan; urban aerosol Gaofen-1; aerosol optical depth; deep blue; Wuhan; urban aerosol

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Sun, K.; Chen, X.; Zhu, Z.; Zhang, T. High Resolution Aerosol Optical Depth Retrieval Using Gaofen-1 WFV Camera Data. Remote Sens. 2017, 9, 89.

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