Please use this identifier to cite or link to this item: https://repositorio.inpa.gov.br/handle/1/20003
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dc.contributor.authorSantos, João Roberto dos-
dc.contributor.authorMaldonado, Francisco Dario-
dc.contributor.authorLopes, A. L.B.-
dc.contributor.authorDisperati, Attilio Antonio-
dc.contributor.authorServello, Emerson Luiz-
dc.contributor.authorLisboa, G. S.-
dc.date.accessioned2020-06-16T17:30:37Z-
dc.date.available2020-06-16T17:30:37Z-
dc.date.issued2008-
dc.identifier.urihttps://repositorio.inpa.gov.br/handle/1/20003-
dc.description.abstractThe main task is to apply in the Araucaria angustifolia (Brazilian pine) biome, the multi-temporal change detection algorithm "RCNA multi-spectral", using TM/Landsat-7 and CCD/CBERS-2 images. The study area is located in Central-South Paraná State, characterized by remnants of Mixed Ombrophilous Forest formations and by a traditional agricultural and cattle raising activities. The approach of change detection is based on the multivariate analysis (two spectral bands), with data from two sensor systems TM/Landsat image (8th Aug., 1999) and CCD/CBERS-2 (8th Aug., 2006). The multi-spectral RCNA is based in angular parameters, those angles are calculated in function of the axis formed by the straight line of regression of those points labeled in the field survey as no-change.The image for detection was transformed from a continuous image (floating-point) to thematic, through a slicing and labeling process. Hence it is possible to discriminate five thematic classes: two related to degradation, two referring to regeneration and one of no-change. The change detection map shows: in the timeframe studied 10.6 % of all area under study presents degradation patterns, derived from the clearcut activity, followed by changes of land use, with the complete removal the Mixed Ombrophilous Forest. In conclusion, we found out that the application of both multi-sensor and multi-spectral RCNA technique in Brazilian Pine landscape is robust and that the complex radiometric correction is not necessary. This simplifies the operational use of RCNA technique, demonstrating that the results can be adapted, considering the complexity of the area under study. © 2008 International Society for Photogrammetry and Remote Sensing. All rights reserved.en
dc.language.isoen-
dc.publisherInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives-
dc.relation.ispartofVolume 37, Pags. 1027-1030pt_BR
dc.rightsRestrito-
dc.subjectDigital Arithmeticen
dc.subjectForestryen
dc.subjectLand Useen
dc.subjectMappingen
dc.subjectMonitoringen
dc.subjectMultivariant Analysisen
dc.subjectRadiometryen
dc.subjectRemote Sensingen
dc.subjectVegetationen
dc.subjectChange Detectionen
dc.subjectDegradation Patternsen
dc.subjectFloating Pointsen
dc.subjectLand Coveren
dc.subjectMultivariate Analysisen
dc.subjectOperational Useen
dc.subjectRadiometric Correctionsen
dc.subjectSensor Systemsen
dc.subjectReforestationen
dc.titleChange detection in the mixed ombrophilous Forest using multispectral radiometric rotation approachen
dc.typeTrabalho Apresentado em Eventopt_BR
Appears in Collections:Trabalhos Apresentados em Evento

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