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dc.contributor.authorBarreira González, Pablo 
dc.contributor.authorBarros, Joana
dc.date.accessioned2019-03-11T11:33:41Z
dc.date.available2019-03-11T11:33:41Z
dc.date.issued2017-03
dc.identifier.bibliographicCitationInternational Journal of Geographical Information Science, 2017, v. 31, n. 3, p. 617-636en
dc.identifier.issn1365-8816
dc.identifier.issn1365-8824
dc.identifier.urihttp://hdl.handle.net/10017/36426
dc.description.abstractCellular automata (CA) models have been widely employed to simulate urban growth and land use change. In order to represent urban space more realistically, new approaches to CA models have explored the use of vector data instead of traditional regular grids. However, the use of irregular CA-based models brings new challenges as well as opportunities. The most strongly affected factor when using an irregular space is neighbourhood. Although neighbourhood definition in an irregular environment has been reported in the literature, the question of how to model the neighbourhood effect remains largely unexplored. In order to shed light on this question, this paper proposed the use of spatial metrics to characterise and measure the neighbourhood effect in irregular CA-based models. These metrics, originally developed for raster environments, namely the enrichment factor and the neighbourhood index, were adapted and applied in the irregular space employed by the model. Using the results of these metrics, distance-decay functions were calculated to reproduce the push-and pull effect between the simulated land uses. The outcomes of a total of 55 simulations (5 sets of different distance functions and 11 different neighbourhood definition distances) were compared with observed changes in the study area during the calibration period. Our results demonstrate that the proposed methodology improves the outcomes of the urban growth simulation model tested and could be applied to other irregular CA-based models.en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)en
dc.rights© Taylor & Francis, 2017en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.rights.urihttps://authorservices.taylorandfrancis.com/sharing-your-work/en
dc.subjectIrregular spaceen
dc.subjectNeighbourhooden
dc.subjectCellular automataen
dc.subjectModellingen
dc.subjectSimulationen
dc.titleConfiguring the neighbourhood effect in irregular cellular automata based modelsen
dc.typeinfo:eu-repo/semantics/articleen
dc.subject.ecienciaGeografíaes_ES
dc.subject.ecienciaGeographyen
dc.contributor.affiliationUniversidad de Alcalá. Departamento de Geología, Geografía y Medio Ambientees_ES
dc.date.updated2019-03-11T11:27:45Z
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.identifier.doi10.1080/13658816.2016.1219035
dc.relation.projectIDCSO2012-38158-C02-01 (Ministerio de Economía y Competitividad)es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.identifier.uxxiAR/0000029396
dc.identifier.publicationtitleInternational Journal of Geographical Information Scienceen
dc.identifier.publicationvolume31
dc.identifier.publicationlastpage636
dc.identifier.publicationissue3
dc.identifier.publicationfirstpage617


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