Using OpenStreetMap point-of-interest data to model urban change—A feasibility study

User-generated content is a valuable resource for capturing all aspects of our environment and lives, and dedicated Volunteered Geographic Information (VGI) efforts such as OpenStreetMap (OSM) have revolutionized spatial data collection. While OSM data is widely used, considerably little attention h...

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Published inPloS one Vol. 14; no. 2; p. e0212606
Main Authors Zhang, Liming, Pfoser, Dieter
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 25.02.2019
Public Library of Science (PLoS)
Subjects
Accuracy
Analysis
Biology and Life Sciences
Coffee
Coffee (Beverage)
Coffeehouses
Criminal statistics
Data collection
Data Curation
Digital mapping
Earth Sciences
Ecology and Environmental Sciences
Feasibility studies
Geographic Information Systems
Geography
Geospatial data
Humans
Mathematical models
Navigation systems
Normal distribution
Open systems
Physical Sciences
Prices
Restaurants
Seasonal variations
Smart cities
Social Sciences
Spatial data
Statistical analysis
Statistical models
Trends
Urban Renewal
Urban studies
User generated content
United States
United States > US
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Summary:User-generated content is a valuable resource for capturing all aspects of our environment and lives, and dedicated Volunteered Geographic Information (VGI) efforts such as OpenStreetMap (OSM) have revolutionized spatial data collection. While OSM data is widely used, considerably little attention has been paid to the quality of its Point-of-interest (POI) component. This work studies the accuracy, coverage, and trend worthiness of POI data. We assess the accuracy and coverage using another VGI source that utilizes editorial control. OSM data is compared to Foursquare data by using a combination of label similarity and positional proximity. Using the example of coffee shop POIs in Manhattan we also assess the trend worthiness of OSM data. A series of spatio-temporal statistical models are tested to compare change in the number of coffee shops to home prices in certain areas. This work overall shows that, although not perfect, OSM POI data and specifically its temporal aspect (changeset) can be used to drive urban science research and to study urban change.
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Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0212606