Exploring the impacts of future tourism development on land use/cover changes
Main Author: | |
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Publication Date: | 2016 |
Other Authors: | , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | https://hdl.handle.net/10316/88997 https://doi.org/10.1016/j.apgeog.2016.10.009 |
Summary: | Land use/cover changes (LUCC) are central to tourism because land is used in multiple ways as a resource for tourism-focused activities. Tourism is essentially a geographical phenomenon, encompassing the movement and flow of people (seen as the demand side) and spatial distribution patterns relating to land use consumption (seen as the supply side). However, the impacts of tourism on LUCC are difficult to track and monitor. Contributing factors of this problem include a lack of empirical studies, shortage of micro-level LUCC datasets, and scarce methodological frameworks which can be used for assessments. This paper aims to provide a LUCC modelling approach in order to explore the impacts of tourism development on built-up areas. We developed a Cellular automata model (CA) which integrates Markovian transition probabilities and logistic regression transition suitability maps. LUCC rules for tourism development are framed within the national land use policy guidelines for the development of new tourism accommodation establishments (TAE). This primarily takes into consideration land cover compatibility and the proposed development's proximity to the coastline. Three scenarios were established to explore the impacts of tourism development in LUCC for the year 2020 in a Portuguese coastal region: business as usual (BAU); tourism trends (TOUR); and natural restrictions (NATR). TOUR results indicate that the tourism and urban land use/cover growth is higher and focuses heavily on the coastal region (within 5,000 m) when compared to the other scenarios. The overall results for BAU and NATR show a general convergence with the land use policy guidelines in terms of tourism nucleation and new TAE distance to the coastline. |
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Exploring the impacts of future tourism development on land use/cover changesCellular automataMarkov chainsScenario developmentLand use policyLand use/cover changes (LUCC) are central to tourism because land is used in multiple ways as a resource for tourism-focused activities. Tourism is essentially a geographical phenomenon, encompassing the movement and flow of people (seen as the demand side) and spatial distribution patterns relating to land use consumption (seen as the supply side). However, the impacts of tourism on LUCC are difficult to track and monitor. Contributing factors of this problem include a lack of empirical studies, shortage of micro-level LUCC datasets, and scarce methodological frameworks which can be used for assessments. This paper aims to provide a LUCC modelling approach in order to explore the impacts of tourism development on built-up areas. We developed a Cellular automata model (CA) which integrates Markovian transition probabilities and logistic regression transition suitability maps. LUCC rules for tourism development are framed within the national land use policy guidelines for the development of new tourism accommodation establishments (TAE). This primarily takes into consideration land cover compatibility and the proposed development's proximity to the coastline. Three scenarios were established to explore the impacts of tourism development in LUCC for the year 2020 in a Portuguese coastal region: business as usual (BAU); tourism trends (TOUR); and natural restrictions (NATR). TOUR results indicate that the tourism and urban land use/cover growth is higher and focuses heavily on the coastal region (within 5,000 m) when compared to the other scenarios. The overall results for BAU and NATR show a general convergence with the land use policy guidelines in terms of tourism nucleation and new TAE distance to the coastline.Elsevier2016-12info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://hdl.handle.net/10316/88997https://hdl.handle.net/10316/88997https://doi.org/10.1016/j.apgeog.2016.10.009eng01436228https://www.sciencedirect.com/science/article/pii/S0143622816306154?via%3Dihub#!Boavida-Portugal, InêsRocha, JorgeFerreira, Carlos Manuel Batista Cardosoinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2020-05-25T03:40:18Zoai:estudogeral.uc.pt:10316/88997Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T05:36:51.575331Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Exploring the impacts of future tourism development on land use/cover changes |
title |
Exploring the impacts of future tourism development on land use/cover changes |
spellingShingle |
Exploring the impacts of future tourism development on land use/cover changes Boavida-Portugal, Inês Cellular automata Markov chains Scenario development Land use policy |
title_short |
Exploring the impacts of future tourism development on land use/cover changes |
title_full |
Exploring the impacts of future tourism development on land use/cover changes |
title_fullStr |
Exploring the impacts of future tourism development on land use/cover changes |
title_full_unstemmed |
Exploring the impacts of future tourism development on land use/cover changes |
title_sort |
Exploring the impacts of future tourism development on land use/cover changes |
author |
Boavida-Portugal, Inês |
author_facet |
Boavida-Portugal, Inês Rocha, Jorge Ferreira, Carlos Manuel Batista Cardoso |
author_role |
author |
author2 |
Rocha, Jorge Ferreira, Carlos Manuel Batista Cardoso |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Boavida-Portugal, Inês Rocha, Jorge Ferreira, Carlos Manuel Batista Cardoso |
dc.subject.por.fl_str_mv |
Cellular automata Markov chains Scenario development Land use policy |
topic |
Cellular automata Markov chains Scenario development Land use policy |
description |
Land use/cover changes (LUCC) are central to tourism because land is used in multiple ways as a resource for tourism-focused activities. Tourism is essentially a geographical phenomenon, encompassing the movement and flow of people (seen as the demand side) and spatial distribution patterns relating to land use consumption (seen as the supply side). However, the impacts of tourism on LUCC are difficult to track and monitor. Contributing factors of this problem include a lack of empirical studies, shortage of micro-level LUCC datasets, and scarce methodological frameworks which can be used for assessments. This paper aims to provide a LUCC modelling approach in order to explore the impacts of tourism development on built-up areas. We developed a Cellular automata model (CA) which integrates Markovian transition probabilities and logistic regression transition suitability maps. LUCC rules for tourism development are framed within the national land use policy guidelines for the development of new tourism accommodation establishments (TAE). This primarily takes into consideration land cover compatibility and the proposed development's proximity to the coastline. Three scenarios were established to explore the impacts of tourism development in LUCC for the year 2020 in a Portuguese coastal region: business as usual (BAU); tourism trends (TOUR); and natural restrictions (NATR). TOUR results indicate that the tourism and urban land use/cover growth is higher and focuses heavily on the coastal region (within 5,000 m) when compared to the other scenarios. The overall results for BAU and NATR show a general convergence with the land use policy guidelines in terms of tourism nucleation and new TAE distance to the coastline. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-12 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10316/88997 https://hdl.handle.net/10316/88997 https://doi.org/10.1016/j.apgeog.2016.10.009 |
url |
https://hdl.handle.net/10316/88997 https://doi.org/10.1016/j.apgeog.2016.10.009 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
01436228 https://www.sciencedirect.com/science/article/pii/S0143622816306154?via%3Dihub#! |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Elsevier |
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Elsevier |
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