Selection of a network of large lakes and reservoirs suitable for global environmental change analysis using Earth Observation

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dc.contributor.author Politi, Eirini
dc.contributor.author MacCallum, S.
dc.contributor.author Cutler, M. E. J.
dc.contributor.author Merchant, C. J.
dc.contributor.author Rowan, J. S.
dc.contributor.author Dawson, T. P.
dc.date.accessioned 2016-08-17T13:25:20Z
dc.date.available 2016-08-17T13:25:20Z
dc.date.issued 2016-06-28
dc.identifier.citation Politi, E., MacCallum S., Cutler M.E.J., Merchant C.J., Rowan J.S. and Dawson T.P. (2016) 'Selection of a network of large lakes and reservoirs suitable for global environmental change analysis using Earth Observation', International Journal of Remote Sensing, 37(13), pp. 3042-3060. http://dx.doi.org/10.1080/01431161.2016.1192702 en
dc.identifier.volume 37 en
dc.identifier.issued 13 en
dc.identifier.startpage 3042 en
dc.identifier.endpage 3060 en
dc.identifier.issn 0143-1161
dc.identifier.issn 1366-5901
dc.identifier.uri http://hdl.handle.net/10468/3001
dc.identifier.doi 10.1080/01431161.2016.1192702
dc.description.abstract The GloboLakes project, a global observatory of lake responses to environmental change, aims to exploit current satellite missions and long remote-sensing archives to synoptically study multiple lake ecosystems, assess their current condition, reconstruct past trends to system trajectories, and assess lake sensitivity to multiple drivers of change. Here we describe the selection protocol for including lakes in the global observatory based upon remote-sensing techniques and an initial pool of the largest 3721 lakes and reservoirs in the world, as listed in the Global Lakes and Wetlands Database. An 18-year-long archive of satellite data was used to create spatial and temporal filters for the identification of waterbodies that are appropriate for remote-sensing methods. Further criteria were applied and tested to ensure the candidate sites span a wide range of ecological settings and characteristics; a total 960 lakes, lagoons, and reservoirs were selected. The methodology proposed here is applicable to new generation satellites, such as the European Space Agency Sentinel-series. en
dc.description.sponsorship Natural Environment Research Council, United Kingdom (Grant number NE/J024279/) en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Taylor and Francis en
dc.rights © 2016 The Authors. Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. en
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ en
dc.subject GloboLakes en
dc.subject (A)ATSR en
dc.subject Environmental change en
dc.subject Lakes en
dc.subject Site selection en
dc.title Selection of a network of large lakes and reservoirs suitable for global environmental change analysis using Earth Observation en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Eirini Politi, Environmental Research Institute, University College Cork, Cork, Ireland. +353-21-490-3000 Email: eirini.politi@ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2016-08-15T10:32:52Z
dc.description.version Published Version en
dc.internal.rssid 360245785
dc.contributor.funder Natural Environment Research Council, United Kingdom en
dc.description.status Peer reviewed en
dc.identifier.journaltitle International Journal of Remote Sensing en
dc.internal.copyrightchecked Yes. en
dc.internal.licenseacceptance Yes en
dc.internal.IRISemailaddress eirini.politi@ucc.ie en


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© 2016 The Authors. Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Except where otherwise noted, this item's license is described as © 2016 The Authors. Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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