{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:12:16Z","timestamp":1760242336293,"version":"build-2065373602"},"reference-count":75,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2017,5,25]],"date-time":"2017-05-25T00:00:00Z","timestamp":1495670400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Cloud and Aerosol Imager (CAI) onboard the Greenhouse Gases Observing Satellite (GOSAT) is a multi-band sensor designed to observe and acquire information on clouds and aerosols. In order to retrieve aerosol optical depth (AOD) over land from the CAI sensor, a Dark Target (DT) algorithm for GOSAT CAI was developed based on the strategy of the Moderate Resolution Imaging Spectroradiometer (MODIS) DT algorithm. When retrieving AOD from satellite platforms, determining surface contributions is a major challenge. In the MODIS DT algorithm, surface signals in the visible wavelengths are estimated based on the relationships between visible channels and shortwave infrared (SWIR) near the 2.1 \u00b5m channel. However, the CAI only has a 1.6 \u00b5m band to cover the SWIR wavelengths. To resolve the difficulties in determining surface reflectance caused by the lack of 2.1 \u03bcm band data, we attempted to analyze the relationship between reflectance at 1.6 \u00b5m and at 2.1 \u00b5m. We did this using the MODIS surface reflectance product and then connecting the reflectances at 1.6 \u00b5m and the visible bands based on the empirical relationship between reflectances at 2.1 \u00b5m and the visible bands. We found that the reflectance relationship between 1.6 \u00b5m and 2.1 \u00b5m is typically dependent on the vegetation conditions, and that reflectances at 2.1 \u00b5m can be parameterized as a function of 1.6 \u00b5m reflectance and the Vegetation Index (VI). Based on our experimental results, an Aerosol Free Vegetation Index (AFRI2.1)-based regression function connecting the 1.6 \u00b5m and 2.1 \u00b5m bands was summarized. Under light aerosol loading (AOD at 0.55 \u00b5m &lt; 0.1), the 2.1 \u00b5m reflectance derived by our method has an extremely high correlation with the true 2.1 \u00b5m reflectance (r-value = 0.928). Similar to the MODIS DT algorithms (Collection 5 and Collection 6), a CAI-applicable approach that uses AFRI2.1 and the scattering angle to account for the visible surface signals was proposed. It was then applied to the CAI sensor for AOD retrieval; the retrievals were validated by comparisons with ground-level measurements from Aerosol Robotic Network (AERONET) sites. Validations show that retrievals from the CAI have high agreement with the AERONET measurements, with an r-value of 0.922, and 69.2% of the AOD retrieved data falling within the expected error envelope of \u00b1 (0.1 + 15% AODAERONET).<\/jats:p>","DOI":"10.3390\/rs9060524","type":"journal-article","created":{"date-parts":[[2017,5,30]],"date-time":"2017-05-30T04:35:42Z","timestamp":1496118942000},"page":"524","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Dark Target Algorithm for the GOSAT TANSO-CAI Sensor in Aerosol Optical Depth Retrieval over Land"],"prefix":"10.3390","volume":"9","author":[{"given":"Guosheng","family":"Zhong","sequence":"first","affiliation":[{"name":"Graduate School of Agriculture, Hokkaido University, Sapporo 0608589, Japan"}]},{"given":"Xiufeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Research Faculty of Agriculture, Hokkaido University, Sapporo 0608589, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5856-4018","authenticated-orcid":false,"given":"Meng","family":"Guo","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Northeast Normal University, Changchun 130024, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3025-7611","authenticated-orcid":false,"given":"Hiroshi","family":"Tani","sequence":"additional","affiliation":[{"name":"Research Faculty of Agriculture, Hokkaido University, Sapporo 0608589, Japan"}]},{"given":"Anthony","family":"Chittenden","sequence":"additional","affiliation":[{"name":"Faculty of Fisheries Sciences, Hokkaido University, Hakodate 0418611, Japan"}]},{"given":"Shuai","family":"Yin","sequence":"additional","affiliation":[{"name":"Graduate School of Agriculture, Hokkaido University, Sapporo 0608589, Japan"}]},{"given":"Zhongyi","family":"Sun","sequence":"additional","affiliation":[{"name":"Graduate School of Agriculture, Hokkaido University, Sapporo 0608589, Japan"}]},{"given":"Shinji","family":"Matsumura","sequence":"additional","affiliation":[{"name":"Faculty of Agriculture, Kagawa University, Sapporo 0608589, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2017,5,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"23","DOI":"10.3390\/rs8010023","article-title":"Aerosol Optical Depth Retrieval over Bright Areas Using Landsat 8 OLI Images","volume":"8","author":"Sun","year":"2015","journal-title":"Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1479","DOI":"10.5194\/angeo-30-1479-2012","article-title":"Study of MODIS derived AOD at three different locations in the Indo Gangetic Plain: Kanpur, Gandhi College and Nainital","volume":"30","author":"Choudhry","year":"2012","journal-title":"Ann. 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