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Exploring the impact of various spectral indices on land cover change detection using change vector analysis: a case study of Crete island, Greece

Polykretis Christos, Gryllakis Emmanouil, Alexakis Dimitrios

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URIhttp://purl.tuc.gr/dl/dias/55806E25-131E-4738-9E12-C2553A9759F1-
Identifierhttps://doi.org/10.3390/rs12020319-
Identifierhttps://www.mdpi.com/2072-4292/12/2/319/htm-
Languageen-
Extent25 pagesen
Extent9,47 megabytesen
TitleExploring the impact of various spectral indices on land cover change detection using change vector analysis: a case study of Crete island, Greeceen
CreatorPolykretis Christosen
CreatorGryllakis Emmanouilen
CreatorΓρυλλακης Εμμανουηλel
CreatorAlexakis Dimitriosen
CreatorΑλεξακης Δημητριοςel
PublisherMDPIen
Content SummaryThe main objective of this study was to explore the impact of various spectral indices on the performance of change vector analysis (CVA) for detecting the land cover changes on the island of Crete, Greece, between the last two decades (1999–2009 and 2009–2019). A set of such indices, namely, normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), albedo, bare soil index (BSI), tasseled cap greenness (TCG), and tasseled cap brightness (TCB), representing both the vegetation and soil conditions of the study area, were estimated on Landsat satellite images captured in 1999, 2009, and 2019. Change vector analysis was then applied for five different index combinations resulting to the relative change outputs. The evaluation of these outputs was performed towards detailed land cover maps produced by supervised classification of the aforementioned images. The results from the two examined periods revealed that the five index combinations provided promising performance results in terms of kappa index (with a range of 0.60–0.69) and overall accuracy (with a range of 0.86–0.96). Moreover, among the different combinations, the use of NDVI and albedo were found to provide superior results against the other combinations. en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2021-09-29-
Date of Publication2020-
SubjectLand coveren
SubjectChange vector analysisen
SubjectSpectral indexen
SubjectLandsaten
SubjectCreteen
SubjectGreeceen
Bibliographic CitationC. Polykretis, M. Grillakis, and D. Alexakis, “Exploring the impact of various spectral indices on land cover change detection using change vector analysis: a case study of Crete island, Greece,” Remote Sens., vol. 12, no. 2, Jan. 2020. doi: 10.3390/rs12020319en

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