Identification of Urban Functional Areas Based on Point of Interest data and Thiessen Polygons for a Sustainable Urban Management

In rapidly developing urban areas, land use changes frequently occur in conjunction with population growth. The determination of the existing land use structure via traditional methods, including field studies and remote sensing techniques, is an exceedingly time-consuming, costly, and labor-intensive process. To address this issue, this paper proposes an innovative model based on Point of Interest (POI) data, Thiessen polygons and Geographic Information Systems (GIS) in the process of identifying land use functions. The model’s workflow comprises data collection, spatial geodatabase design, data pre-processing, the construction of geoprocessing workflows with ModelBuilder, analysis, urban function identification, and model verification steps. This study employs Thiessen polygons to analyze the topological and spatial relationships among 127,265 geotagged POIs in Ankara, the capital of Türkiye. The model achieved a Kappa value of 0.82 and an overall accuracy of 84.5%, demonstrating a high level of reliability. Following this analysis, functional density ratios were calculated based on the distribution of POIs to identify areas characterized by either dominant or mixed land use. The proposed methodology is expected to contribute significantly to urban planning efforts by providing insights into the utilization patterns of urban land. Furthermore, this model has the potential to function as a decision support system, aiding city planners in the effective management and development of urban spaces by delineating existing functional areas.