Urban vegetation classification with high-resolution PlanetScope and SkySat multispectral imagery

A tétel rövid nézete
dc.contributor.authorSzabó, Loránd
dc.contributor.authorAbriha, Dávid
dc.contributor.authorPhinzi, Kwanele
dc.contributor.authorSzabó, Szilárd
dc.date.issued2021-07-14
dc.description.abstractIn this study two high-resolution satellite imagery, the PlanetScope, and SkySat were compared based on their classification capabilities of urban vegetation. During the research, we applied Random Forest and Support Vector Machine classification methods at a study area, center of Rome, Italy. We performed the classifications based on the spectral bands, then we involved the NDVI index, too. We evaluated the classification performance of the classifiers using different sets of input data with ROC curves and AUC values. Additional statistical analyses were applied to reveal the correlation structure of the satellite bands and the NDVI and General Linear Modeling to evaluate the AUC of different models. Although different classification methods did not result in significantly differing outcomes (AUC values between 0.96 and 0.99), SVM’s performance was better. The contribution of NDVI resulted in significantly higher AUC values. SkySat’s bands provided slightly better input data related to PlanetScope but the difference was minimal (~3%); accordingly, both satellites ensured excellent classification results.en
dc.formatapplication/pdf
dc.identifier.citationActa Geographica Debrecina Landscape & Environment series, Vol. 15 No. 1 (2021) , 66-75
dc.identifier.doihttps://doi.org/10.21120/LE/15/1/9
dc.identifier.eissn1789-7556
dc.identifier.issn1789-4921
dc.identifier.issue1
dc.identifier.jatitleLandsc. environ.
dc.identifier.jtitleActa Geographica Debrecina Landscape & Environment series
dc.identifier.urihttps://hdl.handle.net/2437/320652en
dc.identifier.volume15
dc.languageen
dc.relationhttps://ojs.lib.unideb.hu/landsenv/article/view/8358
dc.rights.accessOpen Access
dc.rights.ownerLandscape & Environment
dc.subjectvegetation classificationen
dc.subjecthigh-resolutionen
dc.subjectsatellite imageryen
dc.subjectPlaneten
dc.subjectSkySaten
dc.subjecturban vegetationen
dc.subjectNDVIen
dc.subjectROC curveen
dc.subjectclassification performanceen
dc.subjectRandom Foresten
dc.subjectSupport Vector Machineen
dc.titleUrban vegetation classification with high-resolution PlanetScope and SkySat multispectral imageryen
dc.typefolyóiratcikkhu
dc.typearticleen
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Acta Geographica Debrecina Landscape & Environment (DE-journals)