Evaluation and Analysis of the Evolution and Completeness of Building Data in Volunteered Geographic Information (Case Study: OpenStreetMap Building Information in Mashhad City)

Introduction and Objectives: The advent of digital sensors, smartphones, crowdsourced applications, and vibrant social media platforms has dramatically transformed the landscape of geographic data accessibility. This transformation is even more pronounced with the emergence of user-generated content, a hallmark of Web 2.0 technologies. This participatory phenomenon is termed Volunteered Geographic Information (VGI), of which OpenStreetMap (OSM) serves as a prominent illustration. OSM offers an extensive repository of detailed and frequently updated geospatial data concerning physical infrastructures, including buildings, roads, and other vital landmarks. Though OSM provides this wealth of data free of charge and continues to expand its database, the quality of the information necessitates meticulous evaluation to determine its suitability for various practical applications. Research across the globe has underscored the efficacy of VGI; however, there remains a significant gap in studies investigating the quality of spatial information pertaining specifically to buildings within OSM, particularly in regions like Iran. This study aims to address this gap by focusing on three critical aspects: first, it will evaluate the quality of building data captured in OSM; second, it will analyze the enhancements and overall completeness of this data from the years 2018 to 2023; and third, it will explore the intricate relationship between land use patterns and population density, utilizing the building data derived from OSM. Through this comprehensive examination, the study hopes to shed light on the integrity of VGI in representing urban landscapes.

Materials and Methods: The study area, encompassing districts 9 and 11 of Mashhad, was divided into a grid of 1 x 1 km cells, serving as the foundational framework for our analysis. Within each cell, we assessed three key metrics from 2018 to 2023: building density, completeness, and the quantity of buildings documented in OpenStreetMap (OSM) data. Notably, the ratio of officially registered charges to the overall count of charges within the voluntary dataset indicates the extent to which official data is represented in the voluntary dataset. This metric reflects the completeness of the voluntary data relative to official sources. Subsequently, we analyzed the correlation between building density and data completeness for each grid cell. Additionally, demographic parameters, including population and land use, were incorporated into the evaluation process.

Results and Discussion: The construction data sourced from OpenStreetMap (OSM) across the 9th and 11th districts of Mashhad has witnessed an impressive twentyfold increase from 2018 to 2023. This extraordinary expansion is particularly evident in the eastern and northeastern sectors of the city, where development has surged. Among the various land use categories identified, residential areas, followed by residential-commercial zones, commercial spaces, and educational institutions, display the highest frequency of construction activities in that specific order. Moreover, there exists a notable and robust correlation between the OSM building data and the population residing within each building block. However, this connection has exhibited significant fluctuations throughout the analyzed period, indicating varying patterns of growth and development. Furthermore, an intriguing relationship emerges between the density index and the completeness of the data; in regions where the density of OSM building data is greater, users tend to exhibit a heightened willingness to create and delineate new buildings, reflecting an active engagement in urban development.

Conclusion: An in-depth examination of completeness index values reveals a noteworthy discrepancy in the OpenStreetMap (OSM) dataset, which significantly underrepresents the actual number of buildings when compared to official records. This research compellingly illustrates that, although OSM data can serve as a valuable resource for geographical analyses in urban environments—especially within bustling metropolises such as Mashhad—there exists a pressing necessity for enhancements and validation of the data to attain a higher level of accuracy. Moreover, a meticulous evaluation of key performance indicators can provide profound insights that not only enhance the reliability of the OSM dataset but also bolster its applications in urban planning and other related fields, thereby paving the way for more informed decision-making processes.