Publicação
Mapping a historic neighbourhood through user-generated content: the case of Alfama, Lisbon (Portugal)
| Resumo: | Participant-based methods aimed at extracting neighbourhood definitions are labour and time intensive. On the other hand, user-generated content (UGC) can provide locations to assess the extent of neighbourhoods. We investigated the definitions of Alfama - a historic neighbourhood in Lisbon (Portugal) - using six sources of UGC and applied a modification of the DBSCAN algorithm developed in the literature. By generating shapes from each source, we were able to visually and quantitatively evaluate their agreement as well as their differences.We demonstrate how different profiles of user activity from each source yielded varied geographies of Alfama. Although discrete representations are not the optimal choice, practical applications such as urban planning usually demand sharp definitions. Lastly, our approach can be extended and improved by adding more sources of UGC data and by picking other case studies. |
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| Autores principais: | Tang, Vicente |
| Outros Autores: | Puri, Jaskaran; Painho, Marco |
| Assunto: | Neighbourhoods User-generated content A-DBSCAN Alfama |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | documento de conferência |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | Participant-based methods aimed at extracting neighbourhood definitions are labour and time intensive. On the other hand, user-generated content (UGC) can provide locations to assess the extent of neighbourhoods. We investigated the definitions of Alfama - a historic neighbourhood in Lisbon (Portugal) - using six sources of UGC and applied a modification of the DBSCAN algorithm developed in the literature. By generating shapes from each source, we were able to visually and quantitatively evaluate their agreement as well as their differences.We demonstrate how different profiles of user activity from each source yielded varied geographies of Alfama. Although discrete representations are not the optimal choice, practical applications such as urban planning usually demand sharp definitions. Lastly, our approach can be extended and improved by adding more sources of UGC data and by picking other case studies. |
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