Publicação
Future land use/cover change and tourism development: integrating land use policy and tourist decision behaviour
| Resumo: | With the growth in tourism demand as a vital economic activity worldwide, the tourism system may reach critical thresholds, encompassing transformations of territories towards its touristification. This process has led to land use/cover change (LUCC). In Portugal high levels of tourism demand have resulted in a tourism development model set on land use artificialisation and intensification. Even though tourism development has spatial implications, there are few empirical studies in the literature, mostly because tourism direct LUCC is difficult to track. This book chapter proposes a Cellular Automata–Agent-based model to integrate tourism demand forecasts and suitable areas for future tourism development to explore LUCC in 2030 in a region in Southwest Portugal. The results inform spatial planners and decision-makers when designing land use policies that by 2030 patterns of tourism demand increase of 3.5% may result in a 61% increase in tourism LUCC. |
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| Autores principais: | Boavida-Portugal, Inês |
| Assunto: | Land use change Land cover change Tourism development Simulation Agent-based models Cellular Automata Geosimulation |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | capítulo de livro |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| Resumo: | With the growth in tourism demand as a vital economic activity worldwide, the tourism system may reach critical thresholds, encompassing transformations of territories towards its touristification. This process has led to land use/cover change (LUCC). In Portugal high levels of tourism demand have resulted in a tourism development model set on land use artificialisation and intensification. Even though tourism development has spatial implications, there are few empirical studies in the literature, mostly because tourism direct LUCC is difficult to track. This book chapter proposes a Cellular Automata–Agent-based model to integrate tourism demand forecasts and suitable areas for future tourism development to explore LUCC in 2030 in a region in Southwest Portugal. The results inform spatial planners and decision-makers when designing land use policies that by 2030 patterns of tourism demand increase of 3.5% may result in a 61% increase in tourism LUCC. |
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