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Analysis and modeling of urban land cover change in Setúbal and Sesimbra, Portugal

2010-06-01Artigo científico Acesso aberto
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dc.contributor.authorAraya, Yikalo H.
dc.contributor.authorCabral, Pedro
dc.contributor.institutionNOVA Information Management School (NOVA IMS)
dc.contributor.pblMolecular Diversity Preservation International (MDPI)
dc.date.accessioned2019-05-22T22:15:52Z
dc.date.available2019-05-22T22:15:52Z
dc.date.issued2010-06-01
dc.descriptionAraya, Y. H., & Cabral, P. (2010). Analysis and modeling of urban land cover change in Setúbal and Sesimbra, Portugal. Remote Sensing, 2(6), 1549-1563. https://doi.org/10.3390/rs2061549
dc.description.abstractThe expansion of cities entails the abandonment of forest and agricultural lands, and these lands' conversion into urban areas, which results in substantial impacts on ecosystems. Monitoring these changes and planning urban development can be successfully achieved using multitemporal remotely sensed data, spatial metrics, and modeling. In this paper, urban land use change analysis and modeling was carried out for the Concelhos of Setúbal and Sesimbra in Portugal. An existing land cover map for the year 1990, together with two derived land cover maps from multispectral satellite images for the years 2000 and 2006, were utilized using an object-oriented classification approach. Classification accuracy assessment revealed satisfactory results that fulfilled minimum standard accuracy levels. Urban land use dynamics, in terms of both patterns and quantities, were studied using selected landscape metrics and the Shannon Entropy index. Results show that urban areas increased by 91.11% between 1990 and 2006. In contrast, the change was only 6.34% between 2000 and 2006. The entropy value was 0.73 for both municipalities in 1990, indicating a high rate of urban sprawl in the area. In 2006, this value, for both Sesimbra and Setúbal, reached almost 0.90. This is demonstrative of a tendency toward intensive urban sprawl. Urban land use change for the year 2020 was modeled using a Cellular Automata based approach. The predictive power of the model was successfully validated using Kappa variations. Projected land cover changes show a growing tendency in urban land use, which might threaten areas that are currently reserved for natural parks and agricultural lands.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent15
dc.format.extent1106922
dc.identifier.doi10.3390/rs2061549
dc.identifier.issn2072-4292
dc.identifier.otherPURE: 13282157
dc.identifier.otherPURE UUID: dbc36c77-da7a-4c51-8e39-e899e554e09a
dc.identifier.otherScopus: 84860390333
dc.identifier.otherWOS: 000208401600008
dc.identifier.otherORCID: /0000-0001-8622-6008/work/64041771
dc.identifier.urihttp://www.scopus.com/inward/record.url?scp=84860390333&partnerID=8YFLogxK
dc.identifier.urlhttps://www.scopus.com/pages/publications/84860390333
dc.language.isoeng
dc.peerreviewedyes
dc.subjectChange detection
dc.subjectLand cover change modeling
dc.subjectLandscape metrics
dc.subjectObject-oriented image classification
dc.subjectGeneral Earth and Planetary Sciences
dc.subjectSDG 15 - Life on Land
dc.titleAnalysis and modeling of urban land cover change in Setúbal and Sesimbra, Portugalen
dc.typejournal article
degois.publication.firstPage1549
degois.publication.issue6
degois.publication.lastPage1563
degois.publication.titleRemote Sensing
degois.publication.volume2
dspace.entity.typePublication
rcaap.rightsopenAccess

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