| dc.description.abstract | Urban parking quality is a persistent problem in rapidly growing cities, driven not only by limited land availability but also by spatial conditions, socio-economic characteristics, and the effectiveness of parking management systems. In Medan City, rapid motorization has not been matched by spatially informed parking planning, resulting in on-street parking congestion, inefficient land use, and declining urban environmental quality. This study aims to examine the relationships between spatial parking land characteristics, socio-economic factors, and parking management in influencing parking quality at both global and local spatial scales. This research employs a quantitative spatial approach using Geographic Information Systems (GIS). Spatial analysis is conducted through Multi-Criteria Evaluation (MCE) integrating Weighted Overlay, Fuzzy Membership, and the Analytic Hierarchy Process (AHP) to generate parking land suitability maps. Statistical analysis includes descriptive statistics, Ordinary Least Squares (OLS), and Geographically Weighted Regression (GWR) to identify global effects and spatial variations in local relationships at the sub-district level. The dataset consists of building density, road accessibility, proximity to public facilities, population density, vehicle ownership, and parking management indicators. The results indicate that spatial parking land characteristics and socio-economic variables have a significant influence on parking quality, with considerable spatial heterogeneity in the magnitude and direction of their effects. Parking management functions as a moderating variable, strengthening parking quality outcomes in areas with high spatial suitability. The novelty of this research lies in the integration of high-resolution raster-based spatial modeling with GWR analysis to map localized parking quality patterns, providing more precise, evidence-based recommendations for urban parking planning and policy formulation. | en_US |
