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dc.contributor.authorWang, Shengleien_NZ
dc.contributor.authorLi, Junshengen_NZ
dc.contributor.authorZhang, Bingen_NZ
dc.contributor.authorSpyrakos, Evangelosen_NZ
dc.contributor.authorTyler, Andrew N.en_NZ
dc.contributor.authorShen, Qianen_NZ
dc.contributor.authorZhang, Fangfangen_NZ
dc.contributor.authorKutser, Tiiten_NZ
dc.contributor.authorLehmann, Moritz K.en_NZ
dc.contributor.authorWu, Yanhongen_NZ
dc.contributor.authorPeng, Dailiangen_NZ
dc.date.accessioned2019-11-27T01:30:32Z
dc.date.available2018-11-01en_NZ
dc.date.available2019-11-27T01:30:32Z
dc.date.issued2018en_NZ
dc.identifier.citationWang, S., Li, J., Zhang, B., Spyrakos, E., Tyler, A. N., Shen, Q., … Peng, D. (2018). Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index. Remote Sensing of Environment, 217, 444–460. https://doi.org/10.1016/j.rse.2018.08.026en
dc.identifier.issn0034-4257en_NZ
dc.identifier.urihttps://hdl.handle.net/10289/13195
dc.description.abstractEutrophication of inland waters is considered a serious global environmental problem. Satellite remote sensing (RS) has been established as an important source of information to determine the trophic state of inland waters through the retrieval of optically active water quality parameters such as chlorophyll-a (Chl-a). However, the use of RS techniques for assessment of the trophic state of inland waters on a global scale is hindered by the performance of retrieval algorithms over highly dynamic and complex optical properties that characterize many of these systems. In this study, we developed a new RS approach to assess the trophic state of global inland water bodies based on Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and the Forel-Ule index (FUI). First, the FUI was calculated from MODIS data by dividing natural water colour into 21 indices from dark blue to yellowish-brown. Then the relationship between FUI and the trophic state index (TSI) was established based on in-situ measurements and MODIS products. The water-leaving reflectance at 645 nm band was employed to distinguish coloured dissolved organic matter (CDOM)-dominated systems in the FUI-based trophic state assessment. Based on the analysis, the FUI-based trophic state assessment method was developed and applied to assess the trophic states of 2058 large inland water bodies (surface area >25 km2) distributed around the world using MODIS data from the austral and boreal summers of 2012. Our results showed that FUI can be retrieved from MODIS with a considerable accuracy (92.5%, R2 = 0.92) by comparing with concurrent in situ measurements over a wide range of lakes, and the overall accuracy of the FUI-based trophic state assessment method is 80.0% (R2 = 0.75) validated by an independent dataset. Of the global large water bodies considered, oligotrophic large lakes were found to be concentrated in plateau regions in central Asia and southern South America, while eutrophic large lakes were concentrated in central Africa, eastern Asia, and mid-northern and southeast North America.
dc.format.mimetypeapplication/pdf
dc.language.isoenen_NZ
dc.publisherElsevieren_NZ
dc.rightsThis is an author’s accepted version of an article published in the journal: Remote Sensing of Environment. © 2018 Elsevier.
dc.subjectScience & Technologyen_NZ
dc.subjectLife Sciences & Biomedicineen_NZ
dc.subjectTechnologyen_NZ
dc.subjectEnvironmental Sciencesen_NZ
dc.subjectRemote Sensingen_NZ
dc.subjectImaging Science & Photographic Technologyen_NZ
dc.subjectEnvironmental Sciences & Ecologyen_NZ
dc.subjectTrophic stateen_NZ
dc.subjectGlobal inland watersen_NZ
dc.subjectForel-Ule indexen_NZ
dc.subjectMODISen_NZ
dc.subjectREMOTE-SENSING DATAen_NZ
dc.subjectOCEAN COLORen_NZ
dc.subjectATMOSPHERIC CORRECTIONen_NZ
dc.subjectLAKE TAIHUen_NZ
dc.subjectLANDSAT TMen_NZ
dc.subjectCOMPLEX COASTALen_NZ
dc.subjectSEAWIFS IMAGERYen_NZ
dc.subjectSHALLOW WATERSen_NZ
dc.subjectSATELLITE DATAen_NZ
dc.subjectCHLOROPHYLL-Aen_NZ
dc.titleTrophic state assessment of global inland waters using a MODIS-derived Forel-Ule indexen_NZ
dc.typeJournal Article
dc.identifier.doi10.1016/j.rse.2018.08.026en_NZ
dc.relation.isPartOfRemote Sensing of Environmenten_NZ
pubs.begin-page444
pubs.elements-id226678
pubs.end-page460
pubs.publication-statusPublisheden_NZ
pubs.volume217en_NZ
dc.identifier.eissn1879-0704en_NZ


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