Please use this identifier to cite or link to this item:
http://hdl.handle.net/1893/27730
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DC Field | Value | Language |
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dc.contributor.author | Wang, Shenglei | en_UK |
dc.contributor.author | Li, Junsheng | en_UK |
dc.contributor.author | Zhang, Bing | en_UK |
dc.contributor.author | Spyrakos, Evangelos | en_UK |
dc.contributor.author | Tyler, Andrew N | en_UK |
dc.contributor.author | Shen, Qian | en_UK |
dc.contributor.author | Zhang, Fangfang | en_UK |
dc.contributor.author | Kuster, Tiit | en_UK |
dc.contributor.author | Lehmann, Moritz K. | en_UK |
dc.contributor.author | Wu, Yanhong | en_UK |
dc.contributor.author | Peng, Dailiang | en_UK |
dc.date.accessioned | 2018-09-07T12:24:51Z | - |
dc.date.available | 2018-09-07T12:24:51Z | - |
dc.date.issued | 2018-11-30 | en_UK |
dc.identifier.uri | http://hdl.handle.net/1893/27730 | - |
dc.description.abstract | Eutrophication 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. | en_UK |
dc.language.iso | en | en_UK |
dc.publisher | Elsevier BV | en_UK |
dc.relation | Wang S, Li J, Zhang B, Spyrakos E, Tyler AN, Shen Q, Zhang F, Kuster T, Lehmann MK, Wu Y & Peng D (2018) Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index. Remote Sensing of Environment, 217, pp. 444-460. https://doi.org/10.1016/j.rse.2018.08.026 | en_UK |
dc.rights | This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Accepted refereed manuscript of: Wang S, Li J, Zhang B, Spyrakos E, Tyler AN, Shen Q, Zhang F, Kuster T, Lehmann MK, Wu Y & Peng D (2018) Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index. Remote Sensing of Environment, 217, pp. 444-460. DOI: 10.1016/j.rse.2018.08.026 ©2018, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ | en_UK |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en_UK |
dc.subject | Trophic state | en_UK |
dc.subject | Global inland waters | en_UK |
dc.subject | Forel-Ule index | en_UK |
dc.subject | MODIS | en_UK |
dc.title | Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index | en_UK |
dc.type | Journal Article | en_UK |
dc.rights.embargodate | 2019-09-06 | en_UK |
dc.rights.embargoreason | [RSE-D-16-01414.pdf] Publisher requires embargo of 12 months after formal publication. | en_UK |
dc.identifier.doi | 10.1016/j.rse.2018.08.026 | en_UK |
dc.citation.jtitle | Remote Sensing of Environment | en_UK |
dc.citation.issn | 0034-4257 | en_UK |
dc.citation.volume | 217 | en_UK |
dc.citation.spage | 444 | en_UK |
dc.citation.epage | 460 | en_UK |
dc.citation.publicationstatus | Published | en_UK |
dc.citation.peerreviewed | Refereed | en_UK |
dc.type.status | AM - Accepted Manuscript | en_UK |
dc.contributor.funder | National Key Research and Development Program of China | en_UK |
dc.contributor.funder | China Scholarship Council | en_UK |
dc.contributor.funder | Youth Innovation Promotion Association of the Chinese Academy of Sciences | en_UK |
dc.contributor.funder | National Natural Science Foundation of China | en_UK |
dc.contributor.funder | National Natural Science Foundation of China | en_UK |
dc.contributor.funder | National Natural Science Foundation of China | en_UK |
dc.author.email | evangelos.spyrakos@stir.ac.uk | en_UK |
dc.citation.date | 05/09/2018 | en_UK |
dc.contributor.affiliation | Biological and Environmental Sciences | en_UK |
dc.contributor.affiliation | Biological and Environmental Sciences | en_UK |
dc.contributor.affiliation | Biological and Environmental Sciences | en_UK |
dc.identifier.isi | WOS:000447570900033 | en_UK |
dc.identifier.scopusid | 2-s2.0-85052866018 | en_UK |
dc.identifier.wtid | 991639 | en_UK |
dc.contributor.orcid | 0000-0002-8590-9736 | en_UK |
dc.contributor.orcid | 0000-0003-0604-5827 | en_UK |
dc.contributor.orcid | 0000-0002-6034-0555 | en_UK |
dc.contributor.orcid | 0000-0003-1159-0723 | en_UK |
dc.date.accepted | 2018-08-21 | en_UK |
dcterms.dateAccepted | 2018-08-21 | en_UK |
dc.date.filedepositdate | 2018-09-07 | en_UK |
rioxxterms.apc | not required | en_UK |
rioxxterms.type | Journal Article/Review | en_UK |
rioxxterms.version | AM | en_UK |
local.rioxx.author | Wang, Shenglei| | en_UK |
local.rioxx.author | Li, Junsheng|0000-0002-8590-9736 | en_UK |
local.rioxx.author | Zhang, Bing| | en_UK |
local.rioxx.author | Spyrakos, Evangelos| | en_UK |
local.rioxx.author | Tyler, Andrew N|0000-0003-0604-5827 | en_UK |
local.rioxx.author | Shen, Qian|0000-0002-6034-0555 | en_UK |
local.rioxx.author | Zhang, Fangfang| | en_UK |
local.rioxx.author | Kuster, Tiit| | en_UK |
local.rioxx.author | Lehmann, Moritz K.| | en_UK |
local.rioxx.author | Wu, Yanhong| | en_UK |
local.rioxx.author | Peng, Dailiang|0000-0003-1159-0723 | en_UK |
local.rioxx.project | 2016YFB0501502|National Key Research and Development Program of China| | en_UK |
local.rioxx.project | Project ID unknown|China Scholarship Council| | en_UK |
local.rioxx.project | 2015128|Youth Innovation Promotion Association of the Chinese Academy of Sciences| | en_UK |
local.rioxx.project | 41325004|National Natural Science Foundation of China| | en_UK |
local.rioxx.project | 41471308|National Natural Science Foundation of China| | en_UK |
local.rioxx.project | 41671203|National Natural Science Foundation of China| | en_UK |
local.rioxx.freetoreaddate | 2019-09-06 | en_UK |
local.rioxx.licence | http://www.rioxx.net/licenses/under-embargo-all-rights-reserved||2019-09-05 | en_UK |
local.rioxx.licence | http://creativecommons.org/licenses/by-nc-nd/4.0/|2019-09-06| | en_UK |
local.rioxx.filename | RSE-D-16-01414.pdf | en_UK |
local.rioxx.filecount | 1 | en_UK |
local.rioxx.source | 0034-4257 | en_UK |
Appears in Collections: | Biological and Environmental Sciences Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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RSE-D-16-01414.pdf | Fulltext - Accepted Version | 3.78 MB | Adobe PDF | View/Open |
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