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Land use/land cover change detection and urban sprawl analysis

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Resumo:This 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.
Autores principais:Viana, Cláudia M.
Outros Autores:Oliveira, Sandra; Oliveira, Sérgio; Rocha, Jorge
Assunto:Urban sprawl Land use/cover change Remote sensing Time-Weighted Dynamic Time Warping Time-series
Ano:2019
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso restrito
Instituição associada:Universidade de Lisboa
Idioma:inglês
Origem:Repositório da Universidade de Lisboa
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author Viana, Cláudia M.
author2 Oliveira, Sandra
Oliveira, Sérgio
Rocha, Jorge
author2_role author
author
author
author_facet Viana, Cláudia M.
Oliveira, Sandra
Oliveira, Sérgio
Rocha, Jorge
author_role author
contributor_name_str_mv Repositório Científico de Acesso Aberto da ULisboa
country_str PT
creators_json_txt [{\"Person.name\":\"Viana, Cláudia M.\",\"Person.identifier.orcid\":\"0000-0001-6858-4522\"},{\"Person.name\":\"Oliveira, Sandra\",\"Person.identifier.orcid\":\"0000-0002-6253-4353\"},{\"Person.name\":\"Oliveira, Sérgio\",\"Person.identifier.orcid\":\"0000-0003-0883-8564\"},{\"Person.name\":\"Rocha, Jorge\",\"Person.identifier.orcid\":\"0000-0002-7228-6330\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Repositório Científico de Acesso Aberto da ULisboa
datacite.creators.creator.creatorName.fl_str_mv Viana, Cláudia M.
Oliveira, Sandra
Oliveira, Sérgio
Rocha, Jorge
datacite.date.Accepted.fl_str_mv 2019-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2019-07-01T10:33:27Z
datacite.date.embargoed.fl_str_mv 2019-07-01T10:33:27Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_16ec
datacite.subjects.subject.fl_str_mv Urban sprawl
Land use/cover change
Remote sensing
Time-Weighted Dynamic Time Warping
Time-series
datacite.titles.title.fl_str_mv Land use/land cover change detection and urban sprawl analysis
dc.contributor.none.fl_str_mv Repositório Científico de Acesso Aberto da ULisboa
dc.creator.none.fl_str_mv Viana, Cláudia M.
Oliveira, Sandra
Oliveira, Sérgio
Rocha, Jorge
dc.date.Accepted.fl_str_mv 2019-01-01T00:00:00Z
dc.date.available.fl_str_mv 2019-07-01T10:33:27Z
dc.date.embargoed.fl_str_mv 2019-07-01T10:33:27Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10451/38912
dc.language.none.fl_str_mv eng
dc.publisher.none.fl_str_mv Elsevier
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_16ec
dc.subject.none.fl_str_mv Urban sprawl
Land use/cover change
Remote sensing
Time-Weighted Dynamic Time Warping
Time-series
dc.title.fl_str_mv Land use/land cover change detection and urban sprawl analysis
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_6501
description This 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.
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funding.funder.alternateName_str_mv FCT
FCT
funding.funder.identifier_str_mv http://doi.org/10.13039/501100001871
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funding.funder.name_str_mv Fundação para a Ciência e a Tecnologia
Fundação para a Ciência e a Tecnologia
funding.name_str_mv OE
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person_str_mv Viana, Cláudia M.
Viana, Cláudia M.
https://www.ciencia-id.pt/0712-B263-3133
0712-B263-3133
http://orcid.org/0000-0001-6858-4522
0000-0001-6858-4522
Oliveira, Sandra
Oliveira, Sandra
https://www.ciencia-id.pt/8A16-4976-FD63
8A16-4976-FD63
http://orcid.org/0000-0002-6253-4353
0000-0002-6253-4353
Oliveira, Sérgio
Oliveira, Sérgio
https://www.ciencia-id.pt/1B10-8CE2-1F13
1B10-8CE2-1F13
http://orcid.org/0000-0003-0883-8564
0000-0003-0883-8564
Rocha, Jorge
Rocha, Jorge
https://www.ciencia-id.pt/EC15-76DC-9B96
EC15-76DC-9B96
http://orcid.org/0000-0002-7228-6330
0000-0002-7228-6330
publishDate 2019
publisher.none.fl_str_mv Elsevier
reponame_str Repositório da Universidade de Lisboa
repository_id_str urn:repositoryAcronym:ul
service_str_mv urn:repositoryAcronym:ul
spelling engElsevierpt_PTThis 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.application/pdfpt_PTLand use/land cover change detection and urban sprawl analysisPersonalViana, Cláudia M.DSpacehttp://dspace.org/items/f0bca8f1-525f-49ba-a2ab-c4794d88e2c8DSpacehttp://dspace.org/items/f0bca8f1-525f-49ba-a2ab-c4794d88e2c8M. VianaCláudiaCiência IDhttps://www.ciencia-id.pt0712-B263-3133ORCIDhttp://orcid.org0000-0001-6858-4522Researcher IDhttps://www.researcherid.comA-9352-2019Scopus Author IDhttps://www.scopus.com57200209862Scopus Author IDhttps://www.scopus.com57208061564PersonalOliveira, SandraDSpacehttp://dspace.org/items/d30eb4c5-8ef1-426b-8e80-baa646b30f0eDSpacehttp://dspace.org/items/d30eb4c5-8ef1-426b-8e80-baa646b30f0eOliveiraSandraCiência IDhttps://www.ciencia-id.pt8A16-4976-FD63ORCIDhttp://orcid.org0000-0002-6253-4353Researcher IDhttps://www.researcherid.comAAK-5051-2020Scopus Author IDhttps://www.scopus.com17435272900PersonalOliveira, SérgioDSpacehttp://dspace.org/items/eb79e9a4-db50-4237-8cfa-5ef7a22b243aDSpacehttp://dspace.org/items/eb79e9a4-db50-4237-8cfa-5ef7a22b243aOliveiraSérgioCiência IDhttps://www.ciencia-id.pt1B10-8CE2-1F13ORCIDhttp://orcid.org0000-0003-0883-8564Researcher IDhttps://www.researcherid.comM-8412-2016Scopus Author IDhttps://www.scopus.com24779631800PersonalRocha, JorgeDSpacehttp://dspace.org/items/9c7dabc1-d6c6-4636-9293-6babe2ba64c9DSpacehttp://dspace.org/items/9c7dabc1-d6c6-4636-9293-6babe2ba64c9RochaJorgeCiência IDhttps://www.ciencia-id.ptEC15-76DC-9B96ORCIDhttp://orcid.org0000-0002-7228-6330Researcher IDhttps://www.researcherid.comF-3185-2017Researcher IDhttps://www.researcherid.comF-3185-2017Scopus Author IDhttps://www.scopus.com56428061000HostingInstitutionOrganizationalRepositório Científico de Acesso Aberto da ULisboae-mailmailto:repositorio@reitoria.ulisboa.ptrepositorio@reitoria.ulisboa.ptISBNIsPartOf97801281522632019-07-01T10:33:27Z20192019-01-01T00:00:00ZHandlehttp://hdl.handle.net/10451/38912http://purl.org/coar/access_right/c_16ecrestricted accessUrban sprawlLand use/cover changeRemote sensingTime-Weighted Dynamic Time WarpingTime-series2080052 bytesFundação para a Ciência e a TecnologiaModelo de otimização espacial do Uso do Solo Agrícola: Integração de Autómatos Celulares e algorítmos inteligentes na análise de dados quantitativos e qualitativosCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaMODELAÇÃO DINÂMICA DA PERIGOSIDADE A MOVIMENTOS DE VERTENTE E DESENVOLVIMENTO DE UM PROTÓTIPO DE SISTEMA DE ALERTA À ESCALA REGIONAL MOVALERTOECrossref Funder IDhttp://doi.org/10.13039/501100001871literaturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_16ecapplication/pdffulltexthttps://repositorio.ulisboa.pt/bitstreams/d2aea1b3-d01d-4e8f-b93e-4d4024da9878/downloadSpatial Modeling in GIS and R for Earth and Environmental Sciences621651
spellingShingle Land use/land cover change detection and urban sprawl analysis
Viana, Cláudia M.
Urban sprawl
Land use/cover change
Remote sensing
Time-Weighted Dynamic Time Warping
Time-series
status SINGLETON
subject.fl_str_mv Urban sprawl
Land use/cover change
Remote sensing
Time-Weighted Dynamic Time Warping
Time-series
title Land use/land cover change detection and urban sprawl analysis
title_full Land use/land cover change detection and urban sprawl analysis
title_fullStr Land use/land cover change detection and urban sprawl analysis
title_full_unstemmed Land use/land cover change detection and urban sprawl analysis
title_short Land use/land cover change detection and urban sprawl analysis
title_sort Land use/land cover change detection and urban sprawl analysis
topic Urban sprawl
Land use/cover change
Remote sensing
Time-Weighted Dynamic Time Warping
Time-series
topic_facet Urban sprawl
Land use/cover change
Remote sensing
Time-Weighted Dynamic Time Warping
Time-series
url http://hdl.handle.net/10451/38912
visible 1