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Publicação
Inteligência Espacial na modelação dos clusters turísticos em Portugal Continental
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O turismo é uma das principais atividades económicas atualmente, por isso torna-se
bastante importante a compreensão do comportamento dos turistas no espaço e no tempo
para que haja um bom planeamento da oferta turística no local de destino. Com o
aparecimento de novas tecnologias, surgem novos métodos capazes de complementar os
métodos tradicionais, como é o caso das fotografias geotagged, que nos permitem saber
a localização exata no tempo e no espaço de onde e quando são partilhadas as fotografias
dos turistas.
Nos últimos anos com a evolução das tecnologias têm surgido plataformas online de
economia partilhada (ex.: Airbnb) que dão aos turistas uma maior diversidade e
acessibilidade de ofertas de alojamento aos turistas, tornando a atividade turística cada
vez mais acessível.
Nesta dissertação foram utilizadas fotografias geotagged partilhadas pelos utilizadores da
rede social Flickr durante os anos de 2015 e início de 2020, de forma a analisar o
comportamento espácio-temporal dos turistas em Portugal Continental. Este conjunto de
fotografias foi dividido em 4 tipos: fotografias de locais e visitantes (404 360), fotografias
de turistas (113 625), fotografias de turistas na época fria (62 329) e fotografias de turistas
na época quente (51 296).
Com a utilização de métodos estatísticos verificou-se que os locais mais atrativos tendem
a localizar junto ao litoral, havendo algumas exceções como a cidade de Évora. Mas
verificou-se que existem 3 áreas de grande atração: a região do Algarve, junto à cidade
do Porto e principalmente junto à cidade de Lisboa. Verificou-se ainda que os locais onde
se tendem a concentrar mais fotografias, são os locais onde tendem a existir uma maior
concentração de alojamentos locais.
Tourism is one of the main economic activities today, so it is very important to understand the behavior of tourists in space and time in order to have a good planning of the touristic offer at the destination. With the emergence of new technologies, new methods are emerging that complement traditional methods, such as geotagged photos, which allow us to know the exact location in time and space from where and when tourists' photographs are shared. In recent years with the evolution of technologies have emerged online platforms of shared economy (e.g.: Airbnb) that give tourists a greater diversity and accessibility of accommodation offers to tourists, making the tourist activity increasingly accessible. In this dissertation, geotagged photos shared by Flickr social network users during the years 2015 and early 2020 were used to analyze the spatiotemporal behavior of tourists in Portugal Contnental. This set of photographs was divided into 4 types: photographs of locals and visitors (404 360), photographs of tourists (113 625), photographs of tourists in the cold season (62 329) and photographs of tourists in the warm season (51 296). With the use of statistical methods, it was verified that the most attractive places tend to be located along the coast, with some exceptions such as the city of Évora. It was also verified that there are 3 areas of great attraction: the Algarve region, next to the city of Porto and mainly next to the city of Lisbon. It was also verified that the places where there tend to concentrate more photos, are the places where there tends to be a greater concentration of local lodgings.
Tourism is one of the main economic activities today, so it is very important to understand the behavior of tourists in space and time in order to have a good planning of the touristic offer at the destination. With the emergence of new technologies, new methods are emerging that complement traditional methods, such as geotagged photos, which allow us to know the exact location in time and space from where and when tourists' photographs are shared. In recent years with the evolution of technologies have emerged online platforms of shared economy (e.g.: Airbnb) that give tourists a greater diversity and accessibility of accommodation offers to tourists, making the tourist activity increasingly accessible. In this dissertation, geotagged photos shared by Flickr social network users during the years 2015 and early 2020 were used to analyze the spatiotemporal behavior of tourists in Portugal Contnental. This set of photographs was divided into 4 types: photographs of locals and visitors (404 360), photographs of tourists (113 625), photographs of tourists in the cold season (62 329) and photographs of tourists in the warm season (51 296). With the use of statistical methods, it was verified that the most attractive places tend to be located along the coast, with some exceptions such as the city of Évora. It was also verified that there are 3 areas of great attraction: the Algarve region, next to the city of Porto and mainly next to the city of Lisbon. It was also verified that the places where there tend to concentrate more photos, are the places where there tends to be a greater concentration of local lodgings.
Descrição
Palavras-chave
Turismo Big Data Redes sociais Análise espacial Fotografias geotagged