Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data

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cg.contributor.affiliationInternational Water Management Instituteen
cg.contributor.crpWater, Land and Ecosystems
cg.creator.identifierLisa-Maria Rebelo: 0000-0002-8785-7810en
cg.identifier.doihttps://doi.org/10.1016/j.rse.2014.10.015en
cg.identifier.wlethemeDecision Analysis and Informationen
cg.identifier.wlethemeManaging Resource Variability and Competing Useen
cg.issn0034-4257en
cg.journalRemote Sensing of Environmenten
cg.volume158en
dc.contributor.authorFluet-Chouinard, E.en
dc.contributor.authorLehner, B.en
dc.contributor.authorRebelo, Lisa-Mariaen
dc.contributor.authorPapa, F.en
dc.contributor.authorHamilton, S.K.en
dc.date.accessioned2016-03-09T06:16:04Zen
dc.date.available2016-03-09T06:16:04Zen
dc.identifier.urihttps://hdl.handle.net/10568/72516
dc.titleDevelopment of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing dataen
dcterms.abstractLarge-scale estimates of the area of terrestrial surface waters have greatly improved over time, in particular through the development of multi-satellite methodologies, but the generally coarse spatial resolution (tens of kms) of global observations is still inadequate for many ecological applications. The goal of this study is to introduce a new, globally applicable downscaling method and to demonstrate its applicability to derive fine resolution results from coarse global inundation estimates. The downscaling procedure predicts the location of surface water cover with an inundation probability map that was generated by bagged decision trees using globally available topographic and hydrographic information from the SRTM-derived HydroSHEDS database and trained on the wetland extent of the GLC2000 global land cover map. We applied the downscaling technique to the Global Inundation Extent from Multi-Satellites (GIEMS) dataset to produce a new high-resolution inundation map at a pixel size of 15 arc-seconds, termed GIEMS-D15. GIEMS-D15 represents three states of land surface inundation extents: mean annual minimum (total area, 6.5 × 106 km2 ), mean annual maximum (12.1 × 106 km2 ), and long-term maximum ( 17.3 × 106 km2 ); the latter depicts the largest surface water area of any global map to date. While the accuracy of GIEMS-D15 reflects distribution errors introduced by the downscaling process as well as errors from the original satellite estimates, overall accuracy is good yet spatially variable. A comparison against regional wetland cover maps generated by independent observations shows that the results adequately represent large floodplains and wetlands. GIEMS-D15 offers a higher resolution delineation of inundated areas than previously available for the assessment of global freshwater resources and the study of large floodplain and wetland ecosystems. The technique of applying inundation probabilities also allows for coupling with coarse-scale hydro-climatological model simulations.en
dcterms.accessRightsOpen Access
dcterms.bibliographicCitationFluet-Chouinard, E.; Lehner, B.; Rebelo, Lisa-Maria; Papa, F.; Hamilton, S. K. 2015. Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data. Remote Sensing of Environment, 158:348-361. doi: http://dx.doi.org/10.1016/j.rse.2014.10.015en
dcterms.extentpp. 348-361en
dcterms.issued2015-03en
dcterms.languageen
dcterms.licenseCopyrighted; all rights reserved
dcterms.publisherElsevieren
dcterms.subjectfloodingen
dcterms.subjectfloodplainsen
dcterms.subjectmappingen
dcterms.subjectland coveren
dcterms.subjectsatellite imageryen
dcterms.subjectremote sensingen
dcterms.subjectsurface wateren
dcterms.subjecttopographyen
dcterms.subjectdecision support systemsen
dcterms.subjectdatabasesen
dcterms.subjecthydrologyen
dcterms.subjectmodelsen
dcterms.subjectwetlandsen
dcterms.subjectecosystemsen
dcterms.typeJournal Article

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