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Land use/land cover change detection and urban sprawl analysis

2019Journal article Restricted access
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dc.contributor.authorViana, Cláudia M.
dc.contributor.authorOliveira, Sandra
dc.contributor.authorOliveira, Sérgio
dc.contributor.authorRocha, Jorge
dc.date.accessioned2019-07-01T10:33:27Z
dc.date.available2019-07-01T10:33:27Z
dc.date.issued2019
dc.description.abstractThis study presents a proposed application of the Time-Weighted Dynamic Time Warping (TWDTW) method for urban sprawl analysis. Four spectral indices were computed from a long time-series of Landsat satellite imagery, corresponding to 48 scenes acquired between 2006 and 2018. The spectral indices were the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built Index (NDBI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Bareness Index (NDBaI), which when processed resulted in 192 different images. The R package dtwSat was used for image processing, since it represents one of the few open source software programs available for processing large time-series datasets. The method was tested applied in the Alentejo Region of Southern Portugal; traditionally a rural region, where urban sprawl presents risks for the preservation of agricultural systems and for ecosystem sustainability. The sprawl analysis was integrated in a Geographic Information System (GIS), in which we computed an Expansion Index to quantitatively assess the three main urban land expansion types: infill, extension, and leapfrog. The results show that, between 2007 and 2012, the main changes are due to extension (50 ha), but with a significant amount of infill (36 ha) and leapfrog growth (4 ha), with this latter being the worst-case scenario. However, in the subsequent period, 2012-2017, urban growth decreased to about 10 ha, comprising both infill and extension, but notably leapfrog expansion disappeared. Our methodology proved to be flexible for managing irregular sampling and an out-of-phase time-series. The procedure offers a quantitative means of assessing urban sprawl dynamics and represents a potential strategy for defining sustainable urban development.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationViana, C. M., Oliveira, S., Oliveira, S. C., & Rocha, J. (2019). Land use/land cover change detection and urban sprawl analysis. In: H. R. Pourghasemi, & C. Gokceoglu (ed.). Spatial Modeling in GIS and R for Earth and Environmental Sciences. (Chapter 29, pp. 621-651). Elsevier. ISBN: 9780128152263.pt_PT
dc.identifier.isbn9780128152263
dc.identifier.urihttp://hdl.handle.net/10451/38912
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationModelo de otimização espacial do Uso do Solo Agrícola: Integração de Autómatos Celulares e algorítmos inteligentes na análise de dados quantitativos e qualitativos
dc.relationMODELAÇÃO DINÂMICA DA PERIGOSIDADE A MOVIMENTOS DE VERTENTE E DESENVOLVIMENTO DE UM PROTÓTIPO DE SISTEMA DE ALERTA À ESCALA REGIONAL MOVALERT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/B9780128152263000296pt_PT
dc.subjectUrban sprawlpt_PT
dc.subjectLand use/cover changept_PT
dc.subjectRemote sensingpt_PT
dc.subjectTime-Weighted Dynamic Time Warpingpt_PT
dc.subjectTime-seriespt_PT
dc.titleLand use/land cover change detection and urban sprawl analysispt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleModelo de otimização espacial do Uso do Solo Agrícola: Integração de Autómatos Celulares e algorítmos inteligentes na análise de dados quantitativos e qualitativos
oaire.awardTitleMODELAÇÃO DINÂMICA DA PERIGOSIDADE A MOVIMENTOS DE VERTENTE E DESENVOLVIMENTO DE UM PROTÓTIPO DE SISTEMA DE ALERTA À ESCALA REGIONAL MOVALERT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F115497%2F2016/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/OE/SFRH%2FBPD%2F85827%2F2012/PT
oaire.citation.endPage651pt_PT
oaire.citation.startPage621pt_PT
oaire.citation.titleSpatial Modeling in GIS and R for Earth and Environmental Sciencespt_PT
oaire.fundingStreamOE
person.familyNameM. Viana
person.familyNameOliveira
person.familyNameOliveira
person.familyNameRocha
person.givenNameCláudia
person.givenNameSandra
person.givenNameSérgio
person.givenNameJorge
person.identifier0000000069085031
person.identifier.ciencia-id0712-B263-3133
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person.identifier.ciencia-id1B10-8CE2-1F13
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person.identifier.orcid0000-0001-6858-4522
person.identifier.orcid0000-0002-6253-4353
person.identifier.orcid0000-0003-0883-8564
person.identifier.orcid0000-0002-7228-6330
person.identifier.ridA-9352-2019
person.identifier.ridAAK-5051-2020
person.identifier.ridM-8412-2016
person.identifier.ridF-3185-2017
person.identifier.scopus-author-id57200209862
person.identifier.scopus-author-id17435272900
person.identifier.scopus-author-id24779631800
person.identifier.scopus-author-id56428061000
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
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