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dc.contributor.authorQuintano Pastor, María del Carmen 
dc.contributor.authorFernández Manso, Alfonso
dc.contributor.authorFernández Manso, Oscar
dc.date.accessioned2024-12-11T17:25:47Z
dc.date.available2024-12-11T17:25:47Z
dc.date.issued2018
dc.identifier.citationInternational Journal of Applied Earth Observation and Geoinformation, 2018, vol. 64, p. 221-224.es
dc.identifier.issn1569-8432
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/72412
dc.descriptionProducción Científica
dc.description.abstractNowadays Earth observation satellites, in particular Landsat, provide a valuable help to forest managers in post-fire operations; being the base of post-fire damage maps that enable to analyze fire impacts and to develop vegetation recovery plans. Sentinel-2A MultiSpectral Instrument (MSI) records data in similar spectral wavelengths that Landsat 8 Operational Land Imager (OLI), and has higher spatial and temporal resolutions. This work compares two types of satellite-based maps for evaluating fire damage in a large wildfire (around 8000 ha) located in Sierra de Gata (central-western Spain) on 6–11 August 2015. 1) burn severity maps based exclusively on Landsat data; specifically, on differenced Normalized Burn Ratio (dNBR) and on its relative versions (Relative dNBR, RdNBR, and Relativized Burn Ratio, RBR) and 2) burn severity maps based on the same indexes but combining pre-fire data from Landsat 8 OLI with post-fire data from Sentinel-2A MSI data. Combination of both Landsat and Sentinel-2 data might reduce the time elapsed since forest fire to the availability of an initial fire damage map. Interpretation of ortho-photograph Pléiades 1 B data (1:10,000) provided us the ground reference data to measure the accuracy of both burn severity maps. Results showed that Landsat based burn severity maps presented an adequate assessment of the damage grade (κ statistic = 0.80) and its spatial distribution in wildfire emergency response. Further using both Landsat and Sentinel-2 MSI data the accuracy of burn severity maps, though slightly lower (κ statistic = 0.70) showed an adequate level for be used by forest managers.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevier
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.classificationSentinel-2
dc.subject.classificationLandsat
dc.subject.classificationdNBR
dc.subject.classificationBurn severity
dc.subject.classificationMediterranean ecosystems
dc.titleCombination of Landsat and Sentinel-2 MSI data for initial assessing of burn severity.es
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2017 Elsevier
dc.identifier.doi10.1016/j.jag.2017.09.014es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/abs/pii/S0303243417302039es
dc.peerreviewedSIes
dc.description.projectMinisterio de Economía y Competitividad/FEDER (proyecto GESFIRE AGL201348189-C2-1-R)
dc.description.projectJunta de Castilla y León (proyecto FIRECYL LE033U14)
dc.rightsAtribución-NoComercial-SinDerivados 4.0 Internacional
dc.type.hasVersioninfo:eu-repo/semantics/submittedVersiones


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