Department of Geography and GeoInformation Science, George Mason University, Fairfax, VA, United States of America.
PLoS One. 2019 Feb 25;14(2):e0212606. doi: 10.1371/journal.pone.0212606. eCollection 2019.
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.
用户生成的内容是捕捉我们环境和生活各个方面的有价值资源，而专门的志愿地理信息（VGI）工作，如 OpenStreetMap（OSM），则彻底改变了空间数据的收集方式。虽然 OSM 数据被广泛使用，但人们对其兴趣点（POI）组件的质量关注甚少。这项工作研究了 POI 数据的准确性、覆盖范围和趋势价值。我们使用另一个利用编辑控制的 VGI 源来评估准确性和覆盖范围。通过使用标签相似性和位置接近性的组合，将 OSM 数据与 Foursquare 数据进行比较。我们还使用曼哈顿咖啡店 POI 的示例评估了 OSM 数据的趋势价值。测试了一系列时空统计模型，以比较某些地区咖啡店数量与房价的变化。总的来说，这项工作表明，尽管不完美，但 OSM POI 数据及其时间方面（变更集）可以用于推动城市科学研究和研究城市变化。
