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Remote sensing estimation of carbon fractions in the Chinese Yellow River estuary
Yu, Xiang1,2,3; Wang, Yebao1,2,3; Liu, Xiangyang4; Liu, Xin1,2
2018
Source PublicationMARINE GEORESOURCES & GEOTECHNOLOGY
ISSN1064-119X
Volume36Issue:2Pages:202-210
Corresponding AuthorLiu, Xin(xliu@yic.ac.cn)
AbstractReliable 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.
KeywordCarbon fractions Chinese Yellow River estuary MODIS remote sensing
DOI10.1080/1064119X.2017.1297876
WOS KeywordDISSOLVED ORGANIC-CARBON ; WATER-QUALITY ; CHLOROPHYLL-A ; SPECTRAL REFLECTANCE ; SURFACE-TEMPERATURE ; SPATIAL VARIATIONS ; MATTER ABSORPTION ; INORGANIC CARBON ; SATELLITE DATA ; TROPHIC STATE
Indexed BySCI
Language英语
Funding ProjectChinese Academy of Sciences[NSFC41371483] ; Chinese Academy of Sciences[KZZD-EW-14]
Funding OrganizationChinese Academy of Sciences
WOS Research AreaEngineering ; Oceanography ; Mining & Mineral Processing
WOS SubjectEngineering, Ocean ; Engineering, Geological ; Oceanography ; Mining & Mineral Processing
WOS IDWOS:000424062100006
PublisherTAYLOR & FRANCIS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/56975
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLiu, Xin
Affiliation1.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
Recommended Citation
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.(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.
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