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Assessing contextual descriptive features for plot-based classification of urban areas

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Assessing contextual descriptive features for plot-based classification of urban areas

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dc.contributor.author Hermosilla, T. es_ES
dc.contributor.author Ruiz Fernández, Luis Ángel es_ES
dc.contributor.author Recio Recio, Jorge Abel es_ES
dc.contributor.author Cambra López, María es_ES
dc.date.accessioned 2015-12-16T14:17:19Z
dc.date.available 2015-12-16T14:17:19Z
dc.date.issued 2012-05-15
dc.identifier.issn 0169-2046
dc.identifier.uri http://hdl.handle.net/10251/58900
dc.description.abstract A methodology for mapping urban land-use types integrating information from multiple data sources (high spatial resolution imagery, LiDAR data, and cadastral plots) is presented. A large set of complementary descriptive features that allow distinguishing different urban structures (historical, urban, residential, and industrial) is extracted and, after a selection process, a plot-based image classification approach applied, facilitating to directly relate the classification results and the urban descriptive parameters computed to the existent land-use/land-cover units in geospatial databases. The descriptive features are extracted by considering different hierarchical scale levels with semantic meaning in urban environments: buildings, plots, and urban blocks. Plots are characterised by means of image-based (spectral and textural), three-dimensional, and geometrical features. In addition, two groups of contextual features are defined: internal and external. Internal contextual features describe the main land cover types inside the plot (buildings and vegetation). External contextual features describe each object in terms of the properties of the urban block to which it belongs. After the evaluation in an heterogeneous Mediterranean urban area, the land-use classification accuracy values obtained show that the complementary descriptive features proposed improve the characterisation of urban typologies. A progressive introduction of the different groups of descriptive features in the classification tests show how the subsequent addition of internal and external contextual features have a positive effect by increasing the final accuracy of the urban classes considered in this study. © 2012 Elsevier B.V. es_ES
dc.description.sponsorship The authors appreciate the financial support provided by the Spanish Ministry of Science and Innovation and FEDER in the framework of the projects CGL2009-14220 and CGL2010-19591/BTE, and the support of the Spanish Instituto Geografico Nacional (IGN). en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation Spanish Ministry of Science and Innovation and FEDER Projects CGL2009-14220 and CGL2010-19591/BTE es_ES
dc.relation Spanish Instituto Geografico Nacional (IGN) es_ES
dc.relation.ispartof Landscape and Urban Planning es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Classification es_ES
dc.subject Contextual features es_ES
dc.subject High-resolution imagery es_ES
dc.subject Land-use mapping es_ES
dc.subject LiDAR es_ES
dc.subject Urban areas es_ES
dc.subject Classification approach es_ES
dc.subject Classification results es_ES
dc.subject Classification tests es_ES
dc.subject Contextual feature es_ES
dc.subject Geo-spatial database es_ES
dc.subject Geometrical features es_ES
dc.subject High resolution imagery es_ES
dc.subject High spatial resolution imagery es_ES
dc.subject Image-based es_ES
dc.subject Integrating information es_ES
dc.subject Land-cover types es_ES
dc.subject Landuse classifications es_ES
dc.subject LIDAR data es_ES
dc.subject Multiple data sources es_ES
dc.subject Selection process es_ES
dc.subject Urban environments es_ES
dc.subject Urban structure es_ES
dc.subject Feature extraction es_ES
dc.subject Land use es_ES
dc.subject Optical radar es_ES
dc.subject Semantics es_ES
dc.subject Three dimensional es_ES
dc.subject Classification (of information) es_ES
dc.subject Accuracy assessment es_ES
dc.subject Database es_ES
dc.subject Hierarchical system es_ES
dc.subject Image classification es_ES
dc.subject Land classification es_ES
dc.subject Mapping method es_ES
dc.subject Pattern recognition es_ES
dc.subject Spatial resolution es_ES
dc.subject Typology es_ES
dc.subject Urban area es_ES
dc.subject.classification INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA es_ES
dc.subject.classification BIOLOGIA ANIMAL es_ES
dc.subject.classification PRODUCCION ANIMAL es_ES
dc.title Assessing contextual descriptive features for plot-based classification of urban areas es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.landurbplan.2012.02.008
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Cartográfica Geodesia y Fotogrametría - Departament d'Enginyeria Cartogràfica, Geodèsia i Fotogrametria es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ciencia Animal - Departament de Ciència Animal es_ES
dc.description.bibliographicCitation Hermosilla, T.; Ruiz Fernández, LÁ.; Recio Recio, JA.; Cambra López, M. (2012). Assessing contextual descriptive features for plot-based classification of urban areas. Landscape and Urban Planning. 106(1):124-137. doi:10.1016/j.landurbplan.2012.02.008 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.landurbplan.2012.02.008 es_ES
dc.description.upvformatpinicio 124 es_ES
dc.description.upvformatpfin 137 es_ES
dc.type.version info:eu repo/semantics/publishedVersion es_ES
dc.description.volume 106 es_ES
dc.description.issue 1 es_ES
dc.relation.senia 222339 es_ES


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