Ítem
Solo Metadatos

Analyzing fine-scale wetland composition using high resolution imagery and texture features

Mostrar el registro sencillo de la publicación
dc.creatorSzantoi, Zoltanspa
dc.creatorEscobedo, Franciscospa
dc.creatorAbd-Elrahman, Amrspa
dc.creatorSmith, Scotspa
dc.creatorPearlstine, Leonardspa
dc.date.accessioned2020-08-19T14:40:37Z
dc.date.available2020-08-19T14:40:37Z
dc.date.created2013-01-01spa
dc.description.abstractIn order to monitor natural and anthropogenic disturbance effects to wetland ecosystems, it is necessary to employ both accurate and rapid mapping of wet graminoid/sedge communities. Thus, it is desirable to utilize automated classification algorithms so that the monitoring can be done regularly and in an efficient manner. This study developed a classification and accuracy assessment method for wetland mapping of at-risk plant communities in marl prairie and marsh areas of the Everglades National Park. Maximum likelihood (ML) and Support Vector Machine (SVM) classifiers were tested using 30.5 cm aerial imagery, the normalized difference vegetation index (NDVI), first and second order texture features and ancillary data. Additionally, appropriate window sizes for different texture features were estimated using semivariogram analysis. Findings show that the addition of NDVI and texture features increased classification accuracy from 66.2% using the ML classifier (spectral bands only) to 83.71% using the SVM classifier (spectral bands, NDVI and first order texture features).eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1016/j.jag.2013.01.003
dc.identifier.issnISSN: 0303-2434
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/26962
dc.language.isoengspa
dc.publisherElsevierspa
dc.relation.citationEndPage212
dc.relation.citationStartPage204
dc.relation.citationTitleInternational Journal of Applied Earth Observation and Geoinformation
dc.relation.citationVolumeVol. 23
dc.relation.ispartofInternational Journal of Applied Earth Observation and Geoinformation, ISSN: 0303-2434, Vol.23 (August, 2013); pp. 204-212spa
dc.relation.urihttps://www.sciencedirect.com/science/article/abs/pii/S0303243413000135spa
dc.rights.accesRightsinfo:eu-repo/semantics/restrictedAccess
dc.rights.accesoRestringido (Acceso a grupos específicos)spa
dc.sourceInternational Journal of Applied Earth Observation and Geoinformationspa
dc.source.instnameinstname:Universidad del Rosario
dc.source.reponamereponame:Repositorio Institucional EdocUR
dc.subject.keywordWetland mappingspa
dc.subject.keywordHigh resolution imageryspa
dc.subject.keywordImage texturespa
dc.subject.keywordSupport Vector Machinespa
dc.titleAnalyzing fine-scale wetland composition using high resolution imagery and texture featuresspa
dc.title.TranslatedTitleAnálisis de la composición de humedales a escala fina utilizando imágenes de alta resolución y características de texturaspa
dc.typearticleeng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaArtículospa
Archivos
Colecciones
Artículos