Spatio-temporal dynamics of regions of interest obtained from geotagged photos
Ano de defesa: | 2020 |
---|---|
Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | eng |
Instituição de defesa: |
Universidade Federal de Viçosa
Ciência da Computação |
Programa de Pós-Graduação: |
Não Informado pela instituição
|
Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
|
Palavras-chave em Português: | |
Link de acesso: | https://locus.ufv.br//handle/123456789/30984 |
Resumo: | Regions of Interest are types of geographic data that highlight areas with some type of interest within a city, they can be used to support user’s travel planning, as well as to improve the distribution of resources in that planning area. It is in the interest of the tourist agencies of the government not only to obtain the Regions of Interest where the visitors focus their attention but understand their behavior in order to improve the tourist experience in the geographic area. Social media data as a source of geographic information record the interactions between users and their surrounding environment and have the potential to discover valuable information. Methods and techniques of spatial data mining had been used and improved in order to help understand these behaviors. Tourism as one of the most economically important industries in Cuba and being vulnerable to different events such as natural disasters, political relations or the passage of time has received much attention and methods have been developed to obtain, monitor, and evaluate the recovery and status of the Regions of Interest within a geographical area. In this work, the metadata of the geotagged photos from Flickr is used as a data source to obtain the Regions of Interest and to understand the spatial and temporal dynamics. Havana, the most important touristic city of Cuba is used as the geographic area. Keywords: Regions of Interest. Spatial footprints. Spatio-temporal dynamics. Tourism. |