Abstract
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.
Original language | English |
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Title of host publication | Proceedings of the 25th AGILE Conference on Geographic Information Science, 2022 |
Editors | E. Parseliunas, A. Mansourian, P. Partsinevelos, J. Suziedelyte-Visockiene |
Pages | 1-8 |
Number of pages | 8 |
Volume | 3 |
DOIs | |
Publication status | Published - 20 Jun 2022 |
Event | 25th AGILE Conference on Geographic Information Science, 2022: Artificial Intelligence in the service of Geospatial Technologies - Vilnius, Lithuania Duration: 14 Jun 2022 → 17 Jun 2022 Conference number: 25 https://agile-online.org/conference-2022 |
Publication series
Name | AGILE: GIScience Series |
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Volume | 63 |
Conference
Conference | 25th AGILE Conference on Geographic Information Science, 2022 |
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Abbreviated title | AGILE 2022 |
Country/Territory | Lithuania |
City | Vilnius |
Period | 14/06/22 → 17/06/22 |
Internet address |
Keywords
- Neighbourhoods
- User-generated content
- A-DBSCAN
- Alfama