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A Modified Aerosol Free Vegetation Index Algorithm for Aerosol Optical Depth Retrieval Using GOSAT TANSO-CAI Data

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/67057

Title: A Modified Aerosol Free Vegetation Index Algorithm for Aerosol Optical Depth Retrieval Using GOSAT TANSO-CAI Data
Authors: Zhong, Guosheng Browse this author
Wang, Xiufeng Browse this author →KAKEN DB
Tani, Hiroshi Browse this author →KAKEN DB
Guo, Meng Browse this author
Chittenden, Anthony R. Browse this author
Yin, Shuai Browse this author
Sun, Zhongyi Browse this author
Matsumura, Shinji Browse this author
Keywords: AOD retrieval
GOSAT CAI
Modified AFRI₁․₆ algorithm
surface reflectance
Issue Date: 7-Dec-2016
Publisher: MDPI
Journal Title: Remote Sensing
Volume: 8
Issue: 12
Start Page: 998
Publisher DOI: 10.3390/rs8120998
Abstract: In this paper, we introduced a new algorithm for retrieving aerosol optical depth (AOD) over land, from the Cloud and Aerosol Imager (CAI), which is one of the instruments on the Greenhouse Gases Observing Satellite (GOSAT) for detecting and correcting cloud and aerosol interference. We used the GOSAT and AErosol RObotic NETwork (AERONET) collocated data from different regions over the globe to analyze the relationship between the top-of-atmosphere (TOA) reflectance in the shortwave infrared (1.6 m) band and the surface reflectance in the red (0.67 m) band. Our results confirmed that the relationships between the surface reflectance at 0.67 m and TOA reflectance at 1.6 m are not constant for different surface conditions. Under low AOD conditions (AOD at 0.55 m < 0.1), a Normalized Difference Vegetation Index (NDVI) based regression function for estimating the surface reflectance of 0.67 m band from the 1.6 m band was summarized, and it achieved good performance, proving that the reflectance relations of the 0.67 m and 1.6 m bands are typically vegetation dependent. Since the NDVI itself is easily affected by aerosols, we combined the advantages of the Aerosol Free Vegetation Index (AFRI), which is aerosol resistant and highly correlated with regular NDVI, with our regression function, which can preserve the various correlations of 0.67 m and 1.6 m bands for different surface types, and developed a new surface reflectance and aerosol-free NDVI estimation algorithm, which we named the Modified AFRI(1.6) algorithm. This algorithm was applied to AOD retrieval, and the validation results for our algorithm show that the retrieved AOD has a consistent relationship with AERONET measurements, with a correlation coefficient of 0.912, and approximately 67.7% of the AOD retrieved data were within the expected error range (+/- 0.1 +/- 0.15AOD((AERONET))).
Rights: © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).
http://creativecommons.org/licenses/by/4.0/
Type: article
URI: http://hdl.handle.net/2115/67057
Appears in Collections:農学院・農学研究院 (Graduate School of Agriculture / Faculty of Agriculture) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 王 秀峰

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