Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/8641
DC FieldValueLanguage
dc.contributor.authorSales, Marcio H. Ribeiro-
dc.contributor.authorSouza, Carlos M.-
dc.contributor.authorKyriakidis, Phaedon-
dc.date.accessioned2016-07-11T11:39:18Z-
dc.date.available2016-07-11T11:39:18Z-
dc.date.issued2013-04-
dc.identifier.citationIEEE Transactions on Geoscience and Remote Sensing, 2013, vol. 51, no. 4, pp. 2250 - 2259en_US
dc.identifier.issn1962892-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/8641-
dc.description.abstractThe Moderate Resolution Imaging Spectroradiometer (MODIS) has been used in several remote sensing studies, including land, ocean, and atmospheric applications. The advantages of this sensor are its high spectral resolution, with 36 spectral bands; its high revisiting frequency; and its public domain availability. The first seven bands of MODIS are in the visible, near-infrared, and mid-infrared spectral regions of the electromagnetic spectrum which are sensitive to spectral changes due to deforestation, burned areas, and vegetation regrowth, among other land-use changes, making near-real-time forest monitoring a suitable application. However, the different spatial resolution of the spectral bands placed in these spectral regions imposes challenges to combine them in forest monitoring applications. In this paper, we present an algorithm based on geostatistics to downscale five 500-m MODIS pixel bands to match two 250-m pixel bands. We also discuss the advantages and limitations of this method in relation to existing downscaling algorithms. Our proposed method merges the data to the best spatial resolution and better retains the spectral information of the original data.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofIEEE Transactions on Geoscience and Remote Sensingen_US
dc.rights© IEEEen_US
dc.subjectCorrelationen_US
dc.subjectMODISen_US
dc.subjectMarketing and salesen_US
dc.subjectPrincipal component analysisen_US
dc.subjectSpatial resolutionen_US
dc.subjectWavelet transformsen_US
dc.titleFusion of MODIS Images Using Kriging With External Driften_US
dc.typeArticleen_US
dc.collaborationInstituto do Homem e Meio Ambiente da Amazôniaen_US
dc.subject.categoryEnvironmental Engineeringen_US
dc.journalsSubscriptionen_US
dc.countryBrazilen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1109/TGRS.2012.2208467en_US
dc.dept.handle123456789/54en
dc.relation.issue4en_US
dc.relation.volume51en_US
cut.common.academicyear2012-2013en_US
dc.identifier.spage2250en_US
dc.identifier.epage2259en_US
item.openairetypearticle-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.languageiso639-1en-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-4222-8567-
crisitem.author.parentorgFaculty of Engineering and Technology-
crisitem.journal.journalissn1558-0644-
crisitem.journal.publisherIEEE-
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