Evaluation of Remote-Sensing Reflectance Products from Multiple Ocean Color Missions in Highly Turbid Water (Hangzhou Bay)

Validation of remote-sensing reflectance (Rrs) products is necessary for the quantitative application of ocean color satellite data. While validation of Rrs products has been performed in low to moderate turbidity waters, their performance in highly turbid water remains poorly known. Here, we used i...

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Autores principales:	Yuzhuang Xu, Xianqiang He, Yan Bai, Difeng Wang, Qiankun Zhu, Xiaosong Ding
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	ocean color product validation ultra-highly turbid water GOCI COCTS OLCI Science Q
Acceso en línea:	https://doaj.org/article/ce57499ec6ed441c9663fe27c4061dd3
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spelling	oai:doaj.org-article:ce57499ec6ed441c9663fe27c4061dd32021-11-11T18:52:12ZEvaluation of Remote-Sensing Reflectance Products from Multiple Ocean Color Missions in Highly Turbid Water (Hangzhou Bay)10.3390/rs132142672072-4292https://doaj.org/article/ce57499ec6ed441c9663fe27c4061dd32021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4267https://doaj.org/toc/2072-4292Validation of remote-sensing reflectance (Rrs) products is necessary for the quantitative application of ocean color satellite data. While validation of Rrs products has been performed in low to moderate turbidity waters, their performance in highly turbid water remains poorly known. Here, we used in situ Rrs data from Hangzhou Bay (HZB), one of the world’s most turbid estuaries, to evaluate agency-distributed Rrs products for multiple ocean color sensors, including the Geostationary Ocean Color Imager (GOCI), Chinese Ocean Color and Temperature Scanner aboard HaiYang-1C (COCTS/HY1C), Ocean and Land Color Instrument aboard Sentinel-3A and Sentinel-3B, respectively (OLCI/S3A and OLCI/S3B), Second-Generation Global Imager aboard Global Change Observation Mission-Climate (SGLI/GCOM-C), and Visible Infrared Imaging Radiometer Suite aboard the Suomi National Polar-orbiting Partnership satellite (VIIRS/SNPP). Results showed that GOCI and SGLI/GCOM-C had almost no effective Rrs products in the HZB. Among the others four sensors (COCTS/HY1C, OLCI/S3A, OLCI/S3B, and VIIRS/SNPP), VIIRS/SNPP obtained the largest correlation coefficient (R) with a value of 0.7, while OLCI/S3A obtained the best mean percentage differences (PD) with a value of −13.30%. The average absolute percentage difference (APD) values of the four remote sensors are close, all around 45%. In situ Rrs data from the AERONET-OC ARIAKE site were also used to evaluate the satellite-derived Rrs products in moderately turbid coastal water for comparison. Compared with the validation results at HZB, the performances of Rrs from GOCI, OLCI/S3A, OLCI/S3B, and VIIRS/SNPP were much better at the ARIAKE site with the smallest R (0.77) and largest APD (35.38%) for GOCI, and the worst PD for these four sensors was only −13.15%, indicating that the satellite-retrieved Rrs exhibited better performance. In contrast, Rrs from COCTS/HY1C and SGLI/GCOM-C at ARIAKE site was still significantly underestimated, and the R values of the two satellites were not greater than 0.7, and the APD values were greater than 50%. Therefore, the performance of satellite Rrs products degrades significantly in highly turbid waters and needs to be improved for further retrieval of ocean color components.Yuzhuang XuXianqiang HeYan BaiDifeng WangQiankun ZhuXiaosong DingMDPI AGarticleocean color productvalidationultra-highly turbid waterGOCICOCTSOLCIScienceQENRemote Sensing, Vol 13, Iss 4267, p 4267 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	ocean color product validation ultra-highly turbid water GOCI COCTS OLCI Science Q
spellingShingle	ocean color product validation ultra-highly turbid water GOCI COCTS OLCI Science Q Yuzhuang Xu Xianqiang He Yan Bai Difeng Wang Qiankun Zhu Xiaosong Ding Evaluation of Remote-Sensing Reflectance Products from Multiple Ocean Color Missions in Highly Turbid Water (Hangzhou Bay)
description	Validation of remote-sensing reflectance (Rrs) products is necessary for the quantitative application of ocean color satellite data. While validation of Rrs products has been performed in low to moderate turbidity waters, their performance in highly turbid water remains poorly known. Here, we used in situ Rrs data from Hangzhou Bay (HZB), one of the world’s most turbid estuaries, to evaluate agency-distributed Rrs products for multiple ocean color sensors, including the Geostationary Ocean Color Imager (GOCI), Chinese Ocean Color and Temperature Scanner aboard HaiYang-1C (COCTS/HY1C), Ocean and Land Color Instrument aboard Sentinel-3A and Sentinel-3B, respectively (OLCI/S3A and OLCI/S3B), Second-Generation Global Imager aboard Global Change Observation Mission-Climate (SGLI/GCOM-C), and Visible Infrared Imaging Radiometer Suite aboard the Suomi National Polar-orbiting Partnership satellite (VIIRS/SNPP). Results showed that GOCI and SGLI/GCOM-C had almost no effective Rrs products in the HZB. Among the others four sensors (COCTS/HY1C, OLCI/S3A, OLCI/S3B, and VIIRS/SNPP), VIIRS/SNPP obtained the largest correlation coefficient (R) with a value of 0.7, while OLCI/S3A obtained the best mean percentage differences (PD) with a value of −13.30%. The average absolute percentage difference (APD) values of the four remote sensors are close, all around 45%. In situ Rrs data from the AERONET-OC ARIAKE site were also used to evaluate the satellite-derived Rrs products in moderately turbid coastal water for comparison. Compared with the validation results at HZB, the performances of Rrs from GOCI, OLCI/S3A, OLCI/S3B, and VIIRS/SNPP were much better at the ARIAKE site with the smallest R (0.77) and largest APD (35.38%) for GOCI, and the worst PD for these four sensors was only −13.15%, indicating that the satellite-retrieved Rrs exhibited better performance. In contrast, Rrs from COCTS/HY1C and SGLI/GCOM-C at ARIAKE site was still significantly underestimated, and the R values of the two satellites were not greater than 0.7, and the APD values were greater than 50%. Therefore, the performance of satellite Rrs products degrades significantly in highly turbid waters and needs to be improved for further retrieval of ocean color components.
format	article
author	Yuzhuang Xu Xianqiang He Yan Bai Difeng Wang Qiankun Zhu Xiaosong Ding
author_facet	Yuzhuang Xu Xianqiang He Yan Bai Difeng Wang Qiankun Zhu Xiaosong Ding
author_sort	Yuzhuang Xu
title	Evaluation of Remote-Sensing Reflectance Products from Multiple Ocean Color Missions in Highly Turbid Water (Hangzhou Bay)
title_short	Evaluation of Remote-Sensing Reflectance Products from Multiple Ocean Color Missions in Highly Turbid Water (Hangzhou Bay)
title_full	Evaluation of Remote-Sensing Reflectance Products from Multiple Ocean Color Missions in Highly Turbid Water (Hangzhou Bay)
title_fullStr	Evaluation of Remote-Sensing Reflectance Products from Multiple Ocean Color Missions in Highly Turbid Water (Hangzhou Bay)
title_full_unstemmed	Evaluation of Remote-Sensing Reflectance Products from Multiple Ocean Color Missions in Highly Turbid Water (Hangzhou Bay)
title_sort	evaluation of remote-sensing reflectance products from multiple ocean color missions in highly turbid water (hangzhou bay)
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/ce57499ec6ed441c9663fe27c4061dd3
work_keys_str_mv	AT yuzhuangxu evaluationofremotesensingreflectanceproductsfrommultipleoceancolormissionsinhighlyturbidwaterhangzhoubay AT xianqianghe evaluationofremotesensingreflectanceproductsfrommultipleoceancolormissionsinhighlyturbidwaterhangzhoubay AT yanbai evaluationofremotesensingreflectanceproductsfrommultipleoceancolormissionsinhighlyturbidwaterhangzhoubay AT difengwang evaluationofremotesensingreflectanceproductsfrommultipleoceancolormissionsinhighlyturbidwaterhangzhoubay AT qiankunzhu evaluationofremotesensingreflectanceproductsfrommultipleoceancolormissionsinhighlyturbidwaterhangzhoubay AT xiaosongding evaluationofremotesensingreflectanceproductsfrommultipleoceancolormissionsinhighlyturbidwaterhangzhoubay
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Evaluation of Remote-Sensing Reflectance Products from Multiple Ocean Color Missions in Highly Turbid Water (Hangzhou Bay)

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