| Title |
Streetwise: Mapping Citizens' Perceived Spatial Qualities |
| ID_Doc |
43347 |
| Authors |
Colombo, M; Pincay, J; Lavrovsky, O; Iseli, L; Van Wezemael, J; Portmann, E |
| Title |
Streetwise: Mapping Citizens' Perceived Spatial Qualities |
| Year |
2021 |
| Published |
|
| DOI |
10.5220/0010532208100818 |
| Abstract |
Streetwise is the first map of spatial quality of urban design of Switzerland. Streetwise measures the human perception of spatial situations and uses crowdsourcing methods for this purpose: a large number of people are shown pairs of street-level images of public space online; by clicking on an image, they each give an evaluation about the place they consider has a better atmosphere, which is the focus of this article. With the gathered data, a machine learning model was trained, which allowed learning features that motivate people to choose one image over another. The trained model was then used to estimate a score representing the perceived atmosphere in a large number of images from different urban areas within the Zurich metropolitan region, which could then be visualized on a map to offer a comprehensive overview of the atmosphere of the analyzed cities. The accuracy obtained from the evaluation of the machine learning model indicates that the method followed can perform as well as a group of humans. |
| Author Keywords |
Smart Citizens; Smart City; Crowdsourcing; Neural Networks |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000783390600090 |
| WoS Category |
Computer Science, Information Systems; Computer Science, Interdisciplinary Applications |
| Research Area |
Computer Science |
| PDF |
https://doi.org/10.5220/0010532208100818
|