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Abstract

Summary

Directly evaluating the effectiveness of urban planning is a challenging task. However, if its influence on the real estate market can be demonstrated, this opens up the possibility of improving territorial management mechanisms and enhancing the effectiveness of urban planning decisions. Based on this premise, the aim of the study is to assess the impact of urban territorial planning on real estate pricing using a statistical and geoinformation approach. The research was conducted based on 949 real estate sale and rental advertisements in the city of Irpin, Kyiv region. Data collection was carried out through web scraping using Python (libraries BeautifulSoup, Requests, Selenium). Geographic coordinates were obtained for 176 properties through geocoding with Google Maps. The analysis employed descriptive statistics, correlation and regression analysis, as well as GIS technologies (QGIS and the kriging method for spatial interpolation). The study considered both non-spatial factors (area, number of rooms, renovation) and spatial factors (distance to parks, landfills, and green spaces). Statistically significant effects were observed for some non-spatial factors, particularly renovation. Spatial factors did not show significant relationships, which can be explained by their relatively uniform distribution across the city. The application of the kriging method also did not reveal clear spatial patterns. The findings demonstrated the dominant role of non-spatial characteristics in shaping real estate prices compared to spatial factors of urban planning. The practical significance of the study lies in the potential for a comprehensive statistical and geoinformation approach to support decision-making in urban planning and the real estate market.

EAGE Publications BV © 2025 The Authors © European Association of Geoscientists and Engineers
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2025-10-06
2026-01-13

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/content/papers/10.3997/2214-4609.202552049
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The Relationship Between Urban Land-Use Planning and Real Estate Prices: A Statistical and Geoinformation Approach
Conference Proceedings 2025, 1 (2025); https://doi.org/10.3997/2214-4609.202552049
/content/papers/10.3997/2214-4609.202552049
/content/papers/10.3997/2214-4609.202552049
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