Large-scale Urban Building Function Mapping using web-based Geospatial Data

Large-scale Urban Building Function Mapping using web-based Geospatial Data

Large-scale Urban Building Function Mapping using web-based Geospatial Data

In a pioneering study published in Geo-spatial Information Science, a research group led by Yuyu Zhou from The University of Hong Kong developed an integrated framework that achieves 94% accuracy in mapping building functions across 50 U.S. cities using multi-source web-based geospatial data, offering potential for worldwide application.

The team utilized TripAdvisor.com and Google Maps as primary data sources due to their extensive coverage and dynamic updating features.

The spatial pattern of POIs density (i.e. the number of POIs in 500 m grids) collected from Google Maps (left) and OSM (right) in large (a), middle (b), and small (c) size cities.
The spatial pattern of POIs density (i.e. the number of POIs in 500 m grids) collected from Google Maps (left) and OSM (right) in large (a), middle (b), and small (c) size cities.

Highlights

  • Broad Applicability: With the universal presence of Google Maps and TripAdvisor.com, this framework can potentially be applied to cities globally, offering a standardized method for urban building function mapping.
  •  Resource Efficiency: The study circumvents the expensive and tedious process of gathering social sensing datasets. Instead, it capitalizes on readily available online geospatial data, ensuring scalability and cost-effectiveness.
  •  Potential Extensions: The framework can further be utilized for a myriad of urban studies, from evaluating green spaces to assessing pedestrian exposure to environmental pollutants.

The research findings are promising. The proposed framework demonstrated an impressive average overall accuracy of 94% with a kappa coefficient of 0.63. While the study centred on U.S. cities, its potential for global application, especially in regions with data accessibility challenges, is immense.

Furthermore, as the digital footprint of cities grows, the researchers see opportunities to refine this approach. They recommend future endeavours to enhance mapping accuracy, especially in multi-functional buildings and in regions less covered by TripAdvisor.com and Google Maps.

This research provides a powerful tool for city planners, policy makers, and researchers, with the hope that the integrated framework becomes an essential asset in the global pursuit of sustainable, efficient, and inclusive urban spaces.

Large-scale Urban Building Function Mapping using web-based Geospatial Data

Post source : Chinese Academy of Sciences

About The Author

Anthony brings a wealth of global experience to his role as Managing Editor of Highways.Today. With an extensive career spanning several decades in the construction industry, Anthony has worked on diverse projects across continents, gaining valuable insights and expertise in highway construction, infrastructure development, and innovative engineering solutions. His international experience equips him with a unique perspective on the challenges and opportunities within the highways industry.

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