Akademik Veri Yönetim Sistemi
Journal of Housing and the Built Environment, 2025 (SSCI, Scopus)
Housing prices play a crucial role in shaping urban dynamics, as they reflect the structural, locational, environmental, cultural, and demographic characteristics of a region. Understanding the factors influencing housing prices is essential for urban planning, real estate valuation, and policy-making. This study aims to analyze the determinants of housing prices in a selected urban area and examine their spatial heterogeneity. To achieve this, a dataset was created using housing sales data and 21 independent variables. A combination of Ordinary Least Squares (OLS), mRMR, ReliefF, and FTest methods was employed for feature selection, identifying the most influential variables affecting housing prices. The relationship between these variables and housing prices was further analyzed using regression and machine learning methods. To explore the spatial variability of these relationships, a Geographically Weighted Regression (GWR) model was applied, generating spatially varying coefficient estimates. The results were mapped in a Geographic Information Systems (GIS) environment, revealing significant spatial patterns. The findings indicate that housing prices in the study area are primarily driven by structural and locational characteristics, but their effects vary across different parts of the city. This variation confirms the presence of spatial heterogeneity in housing prices, which is closely linked to urban dynamics such as development trends, accessibility, and land use distribution. The study highlights how spatial patterns in housing prices provide insights into the transformation and growth of urban areas. By integrating advanced feature selection methods based on machine learning and spatial modeling within a GIS framework, this research offers a new approach to housing price analysis. The findings contribute to real estate valuation, urban planning, and policy development by providing a deeper understanding of spatial price variations and their implications for future urban development, infrastructure investments, and housing policies.