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Application of the Savitzky-Golay Filter to Land Cover Classification Using Temporal MODIS Vegetation Indices

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dc.contributor.authorKim, So-Ra-
dc.contributor.authorPrasad, Anup K.-
dc.contributor.authorEl-Askary, Hesham-
dc.contributor.authorLee, Woo-Kyun-
dc.contributor.authorKwak, Doo-Ahn-
dc.contributor.authorLee, Seung-Ho-
dc.contributor.authorKafatos, Menas-
dc.date.accessioned2021-09-05T07:16:27Z-
dc.date.available2021-09-05T07:16:27Z-
dc.date.created2021-06-15-
dc.date.issued2014-07-
dc.identifier.issn0099-1112-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/98046-
dc.description.abstractIn this study, the Savitzky-Golay filter was applied to smooth observed unnatural variations in the temporal profiles of the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) time series from the MODerate Resolution Imaging Spectroradiometer (MODIS). We computed two sets of land cover classifications based on the NDVI and EVI time series before and after applying the Savitzky-Golay filter. The resulting classification from the filtered versions of the vegetation indices showed a substantial improvement in accuracy when compared to the classifications from the unfiltered versions. The classification by the EVIsg had the highest (K) over cap (0.72) for all classes compared to those of the EVI (0.67), NDVI (0.63), and NDVIsg (0.62). Therefore, we conclude that the EVIsg is best suited for land cover classification compared to the other data sets in this study.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherAMER SOC PHOTOGRAMMETRY-
dc.subjectNDVI TIME-SERIES-
dc.subjectLEAF-AREA-
dc.subjectACCURACY-
dc.subjectIMAGERY-
dc.subjectBRAZIL-
dc.subjectEXTRACTION-
dc.subjectPARAMETERS-
dc.subjectAGREEMENT-
dc.subjectNOISE-
dc.subjectASIA-
dc.titleApplication of the Savitzky-Golay Filter to Land Cover Classification Using Temporal MODIS Vegetation Indices-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Woo-Kyun-
dc.identifier.doi10.14358/PERS.80.7.675-
dc.identifier.scopusid2-s2.0-84904293223-
dc.identifier.wosid000338607700011-
dc.identifier.bibliographicCitationPHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, v.80, no.7, pp.675 - 685-
dc.relation.isPartOfPHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING-
dc.citation.titlePHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING-
dc.citation.volume80-
dc.citation.number7-
dc.citation.startPage675-
dc.citation.endPage685-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaPhysical Geography-
dc.relation.journalResearchAreaGeology-
dc.relation.journalResearchAreaRemote Sensing-
dc.relation.journalResearchAreaImaging Science & Photographic Technology-
dc.relation.journalWebOfScienceCategoryGeography, Physical-
dc.relation.journalWebOfScienceCategoryGeosciences, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryRemote Sensing-
dc.relation.journalWebOfScienceCategoryImaging Science & Photographic Technology-
dc.subject.keywordPlusNDVI TIME-SERIES-
dc.subject.keywordPlusLEAF-AREA-
dc.subject.keywordPlusACCURACY-
dc.subject.keywordPlusIMAGERY-
dc.subject.keywordPlusBRAZIL-
dc.subject.keywordPlusEXTRACTION-
dc.subject.keywordPlusPARAMETERS-
dc.subject.keywordPlusAGREEMENT-
dc.subject.keywordPlusNOISE-
dc.subject.keywordPlusASIA-
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생명과학대학 (환경생태공학부)
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