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Diurnal Dynamics and Seasonal Variations of Total Suspended Particulate Matter in Highly Turbid Hangzhou Bay Waters Based on the Geostationary Ocean Color Imager
Liu, Jia2; Liu, Jiahang1; He, Xianqiang2,3; Pan, Delu2,4,5; Bai, Yan2,5; Zhu, Feng1; Chen, Tieqiao1; Wang, Yihao1
作者部门遥感与智能信息系统研究中心
2018-07
发表期刊IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
ISSN1939-1404
卷号11期号:7页码:2170-2180
产权排序1
摘要

Characterized by high concentrations and significant diurnal dynamics, total suspended particulate matter (TSM) in Hangzhou Bay (HZB) can influence the water quality. Both cruise sampling and polar-orbiting satellite remote sensing make it difficult to synoptically delineate such matter in coastal regions due to insufficient spatiotemporal resolution. However, near-real-time monitoring from the Geostationary Ocean Color Imager (GOCI), the world's first geostationary satellite ocean color sensor, now allows hourly observations of target areas. Here, we developed an empirical TSM retrieval algorithm for the GOCI, based on the spectral absorption index (SAI). Additionally, validations of the atmospheric correction algorithm and SAI TSM algorithm were conducted, with the GOCI-retrieved normalized water-leaving radiance (Lwn) and TSM well-matched with in situ values. Moreover, the diurnal dynamics corresponded to tidal phases, with a maximum-of 5000 mg/L in central HZB. The seasonal variations in TSM were also determined by freshwater inputs and sediment loads, with correlation coefficients of -0.77 and 0.84, respectively. The increased wind speed in winter enhanced vertical mixing and favored the resuspension of sediment to the upper layer, and therefore TSM was higher in winter than in summer. These results highlight the feasibility of using geostationary ocean color remote sensing to monitor short-term and regional oceanic phenomena in coastal waters. Furthermore, this study contributes to our understanding of related sediment dynamics and physical biogeochemical processes.

关键词Diurnal Dynamics Geostationary Ocean Color Imager (Goci) Seasonal Variation Spectral Absorption Index (Sai) Total Suspended Particulate Matter (Tsm) Validation
学科领域Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
DOI10.1109/JSTARS.2018.2830335
收录类别SCI ; EI
语种英语
WOS研究方向Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号WOS:000440035600003
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
EI入藏号20182205264023
引用统计
被引频次:22[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/30537
专题遥感与智能信息系统研究中心
通讯作者Liu, Jiahang
作者单位1.Chinese Acad Sci, Lab Remote Sensing & Intelligent Informat Syst, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China
2.State Ocean Adm, Inst Oceanog 2, State Key Lab Satellite Ocean Environm Dynam, Hangzhou 310012, Zhejiang, Peoples R China
3.Zhejiang Univ, Ocean Coll, Hangzhou 310058, Zhejiang, Peoples R China
4.Chinese Acad Engn, Beijing 100088, Peoples R China
5.Hangzhou Normal Univ, Inst Remote Sensing & Earth Sci, Hangzhou 311121, Zhejiang, Peoples R China
推荐引用方式
GB/T 7714
Liu, Jia,Liu, Jiahang,He, Xianqiang,et al. Diurnal Dynamics and Seasonal Variations of Total Suspended Particulate Matter in Highly Turbid Hangzhou Bay Waters Based on the Geostationary Ocean Color Imager[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2018,11(7):2170-2180.
APA Liu, Jia.,Liu, Jiahang.,He, Xianqiang.,Pan, Delu.,Bai, Yan.,...&Wang, Yihao.(2018).Diurnal Dynamics and Seasonal Variations of Total Suspended Particulate Matter in Highly Turbid Hangzhou Bay Waters Based on the Geostationary Ocean Color Imager.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,11(7),2170-2180.
MLA Liu, Jia,et al."Diurnal Dynamics and Seasonal Variations of Total Suspended Particulate Matter in Highly Turbid Hangzhou Bay Waters Based on the Geostationary Ocean Color Imager".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 11.7(2018):2170-2180.
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