In this paper, the Swedish cities Gävle and Göteborg are compared regarding how well activity-based hotspots can capture pedestrian movement. The aim with this paper is to produce a further understanding about how the built environment affects human activities, as well as applying new methods for analyzing big geospatial data. The project is carried out with user generated travel data that comes from the company Trivector and their app TravelVu. Space syntax theory and methods are applied to the street networks to investigate if there are any correlations between the connectivity and the number of travels per street, which in turn is based on natural streets. The results indicate that there is a correlation between connectivity and number of travels per street. But with the use of naturally generated hotspots that are based on human activity, the correlation increases greatly, which imply that in areas with high human activity the connectivity of streets better captures the human movement than in areas with low activity.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hig-34224 |
| Date | January 2020 |
| Creators | Luther, Gustav |
| Publisher | Högskolan i Gävle, Samhällsbyggnad |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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