Spatial quantification of human–environment coupling using multi-source geospatial data and geospatial analytics: evidence from Prishtina, Kosovo

Rapid urban expansion in transitional regions intensifies interactions between human activities and ecological systems, yet quantitatively capturing the spatial balance between anthropogenic pressure and ecological capacity remains a major scientific challenge. Existing approaches often conceptualize human–environment interactions or focus on land-change outcomes without explicitly measuring coupling strength, direction, and spatial dynamics. This study introduces a quantitative geospatial analytics framework to assess human–environment coupling across space and time, using Prishtina (Kosovo) as a representative transitional urban system.

The framework conceptualizes the urban system through two spatially explicit and normalized gradients: an anthropogenic forcing gradient, representing cumulative human pressure, and a geo-ecological capacity gradient, capturing the environment’s ability to regulate and respond to that pressure. These gradients are derived from harmonized multi-source geospatial indicators, including satellite-based environmental proxies and complementary spatial datasets, and are integrated through standardized preprocessing, normalization, and data-driven weighting procedures to ensure spatial comparability and analytical robustness.

Human–environment coupling is quantified using a normalized spatial index ranging from 0 to 1, where higher values indicate balanced interactions and lower values signal increasing imbalance between anthropogenic forcing and ecological capacity. Spatial statistical techniques, including spatial autocorrelation and hotspot analysis, are applied to examine clustering patterns, transition zones, and emerging disequilibrium, while temporal analysis supports the exploration of coupling trajectories under rapid urban transformation.

The proposed framework enables spatially explicit investigation of human–environment coupling heterogeneity within Prishtina and supports the identification of zones characterized by balance, dominance, or transition. By integrating multi-source geospatial data with advanced geospatial analytics, the study offers a transferable quantitative approach for diagnosing human–environment interactions and informing sustainability-oriented spatial planning in transitional urban regions.