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dc.contributor.authorBright, Ryan M.
dc.contributor.authorAstrup, Rasmus Andreas
dc.date.accessioned2020-01-13T09:23:16Z
dc.date.available2020-01-13T09:23:16Z
dc.date.created2019-09-10T15:19:39Z
dc.date.issued2019-04-10
dc.identifier.citationRemote Sensing. 2019, 11 (7), 1-24.nb_NO
dc.identifier.issn2072-4292
dc.identifier.urihttp://hdl.handle.net/11250/2635864
dc.description.abstractSurface albedo is an important physical attribute of the climate system and satellite retrievals are useful for understanding how it varies in time and space. Surface albedo is sensitive to land cover and structure, which can vary considerably within the area comprising the effective spatial resolution of the satellite-based retrieval. This is particularly true for MODIS products and for topographically complex regions, such as Norway, which makes it difficult to separate the environmental drivers (e.g., temperature and snow) from those related to land cover and vegetation structure. In the present study, we employ high resolution datasets of Norwegian land cover and structure to spectrally unmix MODIS surface albedo retrievals (MCD43A3 v6) to study how surface albedo varies with land cover and structure. Such insights are useful for constraining land cover-dependent albedo parameterizations in models employed for regional climate or hydrological research and for developing new empirical models. At the scale of individual land cover types, we found that the monthly surface albedo can be predicted at a high accuracy when given additional information about forest structure, snow cover, and near surface air temperature. Such predictions can provide useful empirical benchmarks for climate model predictions made at the land cover level, which is critical for instilling greater confidence in the albedo-related climate impacts of anthropogenic land use/land cover change (LULCC).nb_NO
dc.language.isoengnb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.subjectSpectral unmixingnb_NO
dc.subjectEmpirical modelingnb_NO
dc.subjectLinear endmembernb_NO
dc.subjectForest covernb_NO
dc.subjectForest managementnb_NO
dc.subjectForest structurenb_NO
dc.subjectBRDF/Albedonb_NO
dc.subjectNDSI Snow Covernb_NO
dc.titleCombining MODIS and National Land Resource Products to Model Land Cover-Dependent Surface Albedo for Norwaynb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.rights.holder2019 by the authors.nb_NO
dc.subject.nsiVDP::Landbruks- og Fiskerifag: 900nb_NO
dc.source.pagenumber1-24nb_NO
dc.source.volume11nb_NO
dc.source.journalRemote Sensingnb_NO
dc.source.issue7nb_NO
dc.identifier.doi10.3390/RS11070871
dc.identifier.cristin1723383
dc.relation.projectNorges forskningsråd: 255307nb_NO
cristin.unitcode7677,2,0,0
cristin.unitnameDivisjon for skog og utmark
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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