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

Simple item page
cg.contributor.affiliationInternational Water Management Instituteen_US
cg.contributor.crpWater, Land and Ecosystemsen_US
cg.identifier.doihttps://doi.org/10.1016/j.rse.2014.10.015en_US
cg.identifier.wlethemeDecision Analysis and Informationen_US
cg.identifier.wlethemeManaging Resource Variability and Competing Useen_US
cg.issn0034-4257en_US
cg.journalRemote Sensing of Environmenten_US
cg.volume158en_US
dc.contributor.authorFluet-Chouinard, E.en_US
dc.contributor.authorLehner, B.en_US
dc.contributor.authorRebelo, Lisa-Mariaen_US
dc.contributor.authorPapa, F.en_US
dc.contributor.authorHamilton, S.K.en_US
dc.date.accessioned2016-03-09T06:16:04Zen_US
dc.date.available2016-03-09T06:16:04Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/72516en_US
dc.titleDevelopment of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing dataen_US
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_US
dcterms.accessRightsOpen Accessen_US
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_US
dcterms.extentpp. 348-361en_US
dcterms.issued2015-03en_US
dcterms.languageenen_US
dcterms.licenseCopyrighted; all rights reserveden_US
dcterms.publisherElsevieren_US
dcterms.subjectfloodingen_US
dcterms.subjectfloodplainsen_US
dcterms.subjectmappingen_US
dcterms.subjectland coveren_US
dcterms.subjectsatellite imageryen_US
dcterms.subjectremote sensingen_US
dcterms.subjectsurface wateren_US
dcterms.subjecttopographyen_US
dcterms.subjectdecision support systemsen_US
dcterms.subjectdatabasesen_US
dcterms.subjecthydrologyen_US
dcterms.subjectmodelsen_US
dcterms.subjectwetlandsen_US
dcterms.subjectecosystemsen_US
dcterms.typeJournal Articleen_US

Files

License bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.75 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

IWMI Journal Articles
Decision Analysis and Information
Managing Resource Variability and Competing Use
WLE Journal Articles