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Remote sensing estimation of carbon fractions in the Chinese Yellow River estuary

文献类型：期刊论文

作者Yu, Xiang1,2,3; Wang, Yebao1,2,3; Liu, Xiangyang4; Liu, Xin1,2; Liu, Xin(Chinese Acad Sci, Yantai Inst Coastal Zone Res, Key Lab Coastal Environm Proc & Ecol Remediat, Yantai, Shandong, Peoples R China)
刊名MARINE GEORESOURCES & GEOTECHNOLOGY
出版日期2018
卷号36期号:2页码:202-210
关键词Carbon Fractions Chinese Yellow River Estuary Modis Remote Sensing
ISSN号1064-119X
DOI10.1080/1064119X.2017.1297876
产权排序第1完成单位 ; 第2完成单位
文献子类Article
英文摘要Reliable and consistent carbon fraction estimates are crucial in studying the role of coasts in the global carbon cycle. Remote sensing offers the potential to estimate carbon fractions with its advantages of large spatial coverage and real-time surveys. Colored dissolved organic matter (CDOM) absorption was generally used as a proxy to estimate dissolved organic carbon (DOC). However, the CDOM-DOC relationship varies by region and remains inconstant. Thus, the correlation between the reflectivity of visible band and DOC concentration was directly adopted in DOC estimation and performed well in former studies. Atomic groups of the various components of carbon fractions produce electronic transition by absorbing photons, and this process occurs both in the visible bands and in the near-infrared bands. Thus, the wide range of absorption band provides an approach to estimate carbon fractions using the correlation between the reflectivity of the whole visible/near-infrared bands of optical satellite sensors and carbon fractions. A new ratio band combination was developed and performed well in carbon fraction concentration retrievals, and the yielded estimation accuracies (R-2>0.77, RPD >2.02) were sufficient to map the spatial distributions of carbon fractions with the moderate resolution imaging spectroradiometer image.
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WOS关键词DISSOLVED ORGANIC-CARBON ; WATER-QUALITY ; CHLOROPHYLL-A ; SPECTRAL REFLECTANCE ; SURFACE-TEMPERATURE ; SPATIAL VARIATIONS ; MATTER ABSORPTION ; INORGANIC CARBON ; SATELLITE DATA ; TROPHIC STATE
WOS研究方向Engineering ; Oceanography ; Mining & Mineral Processing
语种英语
WOS记录号WOS:000424062100006
资助机构Chinese Academy of Sciences(NSFC41371483, KZZD-EW-14)
源URL[http://ir.yic.ac.cn/handle/133337/23570]  
专题烟台海岸带研究所_海岸带信息集成与综合管理实验室
通讯作者Liu, Xin; Liu, Xin(Chinese Acad Sci, Yantai Inst Coastal Zone Res, Key Lab Coastal Environm Proc & Ecol Remediat, Yantai, Shandong, Peoples R China)
作者单位1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Key Lab Coastal Environm Proc & Ecol Remediat, Yantai, Shandong, Peoples R China
2.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Shandong Prov Key Lab Coastal Environm Proc, Yantai, Shandong, Peoples R China
3.Univ Chinese Acad Sci, Beijing, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Yu, Xiang,Wang, Yebao,Liu, Xiangyang,et al. Remote sensing estimation of carbon fractions in the Chinese Yellow River estuary[J]. MARINE GEORESOURCES & GEOTECHNOLOGY,2018,36(2):202-210.
APA Yu, Xiang,Wang, Yebao,Liu, Xiangyang,Liu, Xin,&Liu, Xin.(2018).Remote sensing estimation of carbon fractions in the Chinese Yellow River estuary.MARINE GEORESOURCES & GEOTECHNOLOGY,36(2),202-210.
MLA Yu, Xiang,et al."Remote sensing estimation of carbon fractions in the Chinese Yellow River estuary".MARINE GEORESOURCES & GEOTECHNOLOGY 36.2(2018):202-210.

入库方式： OAI收割

来源：烟台海岸带研究所

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