Explaining Intra-Urban Spatial Interaction with Theory-Informed Interpretable Machine Learning: Nonlinear Contributions of Complementarity, Intervening Opportunities, and Transferability
Understanding intra-urban spatial interaction is essential for context-sensitive urban planning. While classical spatial interaction theories provide strong conceptual foundations, systematically translating these theoretical concepts into quantifiable indicators remains a significant methodological challenge. Furtherm...