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dc.creatorBlanco P.D.spa
dc.creatorColditz R.R.spa
dc.creatorLopez Saldana G.spa
dc.creatorHardtke L.A.spa
dc.creatorLlamas R.M.spa
dc.creatorMari N.A.spa
dc.creatorFischer A.spa
dc.creatorCaride C.spa
dc.creatorAcenolaza P.G.spa
dc.creatordel Valle H.F.spa
dc.creatorLillo-Saavedra M.spa
dc.creatorCoronato F.spa
dc.creatorOpazo S.A.spa
dc.creatorMorelli F.spa
dc.creatorAnaya J.A.spa
dc.creatorSione W.F.spa
dc.creatorZamboni P.spa
dc.creatorArroyo V.B.spa
dc.date.accessioned2015-10-09T13:18:26Z
dc.date.available2015-10-09T13:18:26Z
dc.date.created2013
dc.identifier.issn344257
dc.identifier.urihttp://hdl.handle.net/11407/1401
dc.description.abstractLand cover maps at different resolutions and mapping extents contribute to modeling and support decision making processes. Because land cover affects and is affected by climate change, it is listed among the 13 terrestrial essential climate variables. This paper describes the generation of a land cover map for Latin America and the Caribbean (LAC) for the year 2008. It was developed in the framework of the project Latin American Network for Monitoring and Studying of Natural Resources (SERENA), which has been developed within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLaTIF). The SERENA land cover map for LAC integrates: 1) the local expertise of SERENA network members to generate the training and validation data, 2) a methodology for land cover mapping based on decision trees using MODIS time series, and 3) class membership estimates to account for pixel heterogeneity issues. The discrete SERENA land cover product, derived from class memberships, yields an overall accuracy of 84% and includes an additional layer representing the estimated per-pixel confidence. The study demonstrates in detail the use of class memberships to better estimate the area of scarce classes with a scattered spatial distribution. The land cover map is already available as a printed wall map and will be released in digital format in the near future. The SERENA land cover map was produced with a legend and classification strategy similar to that used by the North American Land Change Monitoring System (NALCMS) to generate a land cover map of the North American continent, that will allow to combine both maps to generate consistent data across America facilitating continental monitoring and modeling. © 2012 Elsevier Inc.eng
dc.language.isoeng
dc.relation.isversionofhttp://www.sciencedirect.com/science/article/pii/S0034425713000035spa
dc.sourceScopusspa
dc.typeArticleeng
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.contributor.affiliationNational Patagonian Center-Argentinean National Research Council, Terrestrial Ecology Unit, U9120ACD Puerto Madryn, Chubut, Argentinaspa
dc.contributor.affiliationNational Commission for the Knowledge and Use of Biodiversity (CONABIO), Av. Liga Periférico-Insurgentes Sur 4903, Parques del Pedregal, Tlalpan 14010, Mexico City, D.F., Mexicospa
dc.contributor.affiliationDepartment of Forestry, School of Agronomy, Technical University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugalspa
dc.contributor.affiliationClimate and Water Institute-INTA, B1712WAA Castelar, Buenos Aires, Argentinaspa
dc.contributor.affiliationCenter of Scientific Research, Technological Transfer to Productivity-Argentinean National Research Council, CP 3105 Diamante, Entre Ríos, Argentinaspa
dc.contributor.affiliationAutonomous University of Entre Ríos, CP 3100 Paraná, Entre Ríos, Argentinaspa
dc.contributor.affiliationUniversity of Concepción, Department of Electronic Engineering, 4070386 Concepción, Chilespa
dc.contributor.affiliationUniversity of Magallanes, Science and Agricultural Technology School, 621-0427 Punta Arenas, Chilespa
dc.contributor.affiliationCenter for Weather Forecasting and Climate Studies, INPE, SP 12227-010 Sao José dos Campos, Brazilspa
dc.contributor.affiliationUniversity of Medellín, Faculty of Engineering, Medellín, Colombiaspa
dc.contributor.affiliationNational University of Luján, 6700 Luján, Buenos Aires, Argentinaspa
dc.contributor.affiliationNational Agrarian University - La Molina (UNALM), Lima, Peruspa
dc.identifier.doi10.1016/j.rse.2012.12.025
dc.subject.keywordClass membershipseng
dc.subject.keywordDecision treeseng
dc.subject.keywordGOFC-GOLDeng
dc.subject.keywordLand cover classificationeng
dc.subject.keywordLatin Americaeng
dc.subject.keywordMODISeng
dc.subject.keywordRedLaTIF networkeng
dc.subject.keywordSERENA projecteng
dc.relation.ispartofenRemote Sensing of Environment, 15 de mayo de 2013, volume 132, pp 13-31eng
dc.title.englishA land cover map of Latin America and the Caribbean in the framework of the SERENA projecteng
dc.type.driverinfo:eu-repo/semantics/article


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