Modelling Land-Use and Land-Cover Changes: A Hybrid Approach to a Coastal Area
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Outros Autores: | , |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10451/47563 |
Resumo: | In this chapter, a hybrid approach integrating cellular automata (CA), fuzzy logic, logistic regression, and Markov chains for modelling and prediction of land-use and land-cover (LULC) change at the local scale, using geographic information with fine spatial resolution is presented. A spatial logistic regression model was applied to determine the transition rules that were used by a conventional CA model. The overall dimension of LULC change was estimated using a Markov chain model. The proposed CA-based model (termed CAMLucc) in combination with physical variables and land-use planning data was applied to simulate LULC change in Portimão, Portugal between 1947 and 2010 and to predict its future spatial patterns for 2020 and 2025. The main results of this research show that Portimão has been facing massive growth in artificial surfaces, particularly near the main urban settlements and along the coastal area, and reveal an early and intensive urban sprawl over time. |
id |
RCAP_5340c7cfd42dc2eff1885e3c4aeb2ab3 |
---|---|
oai_identifier_str |
oai:repositorio.ul.pt:10451/47563 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Modelling Land-Use and Land-Cover Changes: A Hybrid Approach to a Coastal AreaLand-UseLand-CoverCoastal AreaModelling and predictionIn this chapter, a hybrid approach integrating cellular automata (CA), fuzzy logic, logistic regression, and Markov chains for modelling and prediction of land-use and land-cover (LULC) change at the local scale, using geographic information with fine spatial resolution is presented. A spatial logistic regression model was applied to determine the transition rules that were used by a conventional CA model. The overall dimension of LULC change was estimated using a Markov chain model. The proposed CA-based model (termed CAMLucc) in combination with physical variables and land-use planning data was applied to simulate LULC change in Portimão, Portugal between 1947 and 2010 and to predict its future spatial patterns for 2020 and 2025. The main results of this research show that Portimão has been facing massive growth in artificial surfaces, particularly near the main urban settlements and along the coastal area, and reveal an early and intensive urban sprawl over time.IGI GlobalRepositório da Universidade de LisboaFaria de Deus, RaquelTenedório, José A.Rocha, Jorge2021-04-27T13:55:09Z20212021-01-01T00:00:00Zbook partinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10451/47563engFaria de Deus, R., Tenedório, J. A., & Rocha, J. (2021). Modelling Land-Use and Land-Cover Changes: A Hybrid Approach to a Coastal Area. In: Tenedório, J. A., Estanqueiro, R., & Henriques, C. D. (Ed.), Methods and Applications of Geospatial Technology in Sustainable Urbanism (pp. 57-102). IGI Global. http://doi:10.4018/978-1-7998-2249-3.ch003978179982249310.4018/978-1-7998-2249-3.ch003metadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-11-20T18:06:03Zoai:repositorio.ul.pt:10451/47563Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-11-20T18:06:03Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Modelling Land-Use and Land-Cover Changes: A Hybrid Approach to a Coastal Area |
title |
Modelling Land-Use and Land-Cover Changes: A Hybrid Approach to a Coastal Area |
spellingShingle |
Modelling Land-Use and Land-Cover Changes: A Hybrid Approach to a Coastal Area Faria de Deus, Raquel Land-Use Land-Cover Coastal Area Modelling and prediction |
title_short |
Modelling Land-Use and Land-Cover Changes: A Hybrid Approach to a Coastal Area |
title_full |
Modelling Land-Use and Land-Cover Changes: A Hybrid Approach to a Coastal Area |
title_fullStr |
Modelling Land-Use and Land-Cover Changes: A Hybrid Approach to a Coastal Area |
title_full_unstemmed |
Modelling Land-Use and Land-Cover Changes: A Hybrid Approach to a Coastal Area |
title_sort |
Modelling Land-Use and Land-Cover Changes: A Hybrid Approach to a Coastal Area |
author |
Faria de Deus, Raquel |
author_facet |
Faria de Deus, Raquel Tenedório, José A. Rocha, Jorge |
author_role |
author |
author2 |
Tenedório, José A. Rocha, Jorge |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Faria de Deus, Raquel Tenedório, José A. Rocha, Jorge |
dc.subject.por.fl_str_mv |
Land-Use Land-Cover Coastal Area Modelling and prediction |
topic |
Land-Use Land-Cover Coastal Area Modelling and prediction |
description |
In this chapter, a hybrid approach integrating cellular automata (CA), fuzzy logic, logistic regression, and Markov chains for modelling and prediction of land-use and land-cover (LULC) change at the local scale, using geographic information with fine spatial resolution is presented. A spatial logistic regression model was applied to determine the transition rules that were used by a conventional CA model. The overall dimension of LULC change was estimated using a Markov chain model. The proposed CA-based model (termed CAMLucc) in combination with physical variables and land-use planning data was applied to simulate LULC change in Portimão, Portugal between 1947 and 2010 and to predict its future spatial patterns for 2020 and 2025. The main results of this research show that Portimão has been facing massive growth in artificial surfaces, particularly near the main urban settlements and along the coastal area, and reveal an early and intensive urban sprawl over time. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-04-27T13:55:09Z 2021 2021-01-01T00:00:00Z |
dc.type.driver.fl_str_mv |
book part |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10451/47563 |
url |
http://hdl.handle.net/10451/47563 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Faria de Deus, R., Tenedório, J. A., & Rocha, J. (2021). Modelling Land-Use and Land-Cover Changes: A Hybrid Approach to a Coastal Area. In: Tenedório, J. A., Estanqueiro, R., & Henriques, C. D. (Ed.), Methods and Applications of Geospatial Technology in Sustainable Urbanism (pp. 57-102). IGI Global. http://doi:10.4018/978-1-7998-2249-3.ch003 9781799822493 10.4018/978-1-7998-2249-3.ch003 |
dc.rights.driver.fl_str_mv |
metadata only access info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
metadata only access |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
IGI Global |
publisher.none.fl_str_mv |
IGI Global |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
mluisa.alvim@gmail.com |
_version_ |
1817549135128035328 |