Quantifying scenic areas using crowdsourced data
Bibliographic Data
| ID | 21246962 |
|---|---|
| Authors | Chanuki Illushka Seresinhe (0000-0001-6599-1325, University of Warwick, corresponding author), Helen Susannah Moat (0000-0001-8974-9277, University of Warwick), Tobias Preis (0000-0001-9185-0892, University of Warwick) |
| Year | 2018 |
| Volume | 45 |
| Issue | 3 |
| Pages | 567-582 |
| Publication date | 2018-05-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environment and Planning B Urban Analytics and City Science (JOURNAL) |
| Journal identifiers | ISSN: 2399-8083 • E-ISSN: 2399-8091 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/0265813516687302 |
| OpenAlex | W2582005091 |
| Language | EN |
| Citations received | 12 |
| References cited | 48 |
For centuries, philosophers, policy-makers and urban planners have debated whether aesthetically pleasing surroundings can improve our wellbeing. To date, quantifying how scenic an area is has proved challenging, due to the difficulty of gathering large-scale measurements of scenicness. In this study we ask whether images uploaded to the website Flickr, combined with crowdsourced geographic data from OpenStreetMap, can help us estimate how scenic people consider an area to be. We validate our findings using crowdsourced data from Scenic-Or-Not, a website where users rate the scenicness of photos from all around Great Britain. We find that models including crowdsourced data from Flickr and OpenStreetMap can generate more accurate estimates of scenicness than models that consider only basic census measurements such as population density or whether an area is urban or rural. Our results provide evidence that by exploiting the vast quantity of data generated on the Internet, scientists and policy-makers may be able to develop a better understanding of people's subjective experience of the environment in which they live
Cartography · Census · Crowdsourcing · Data science · Geography · Population · Sociology · The Internet · Upload · World Wide Web · Computer Science · Impact of Light on Environment and Health · Land Use and Ecosystem Services · Urban Green Space and Health
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| Citations per year | 1.71 |
|---|---|
| Citation span | 2019 - 2024 (6) |
| Highly cited | No |