Exploring the urban function trade-offs/synergies of spatial reorganization via distance gradient analysis

The development of functions within cities determines the intensity of spatial reorganization. Therefore, the quantitative analysis of urban functions is of importance. However, existing methods for quantifying urban functions remain underexplored. To bridge this gap, we propose a distance gradient-based approach to quantitatively analyze urban functional development. Specifically, we introduce a shift-share model to compute the distance gradients of different urban functions across cities. Then, an empirical study is conducted using Points-of-Interest (POI) data from the Yangtze River Delta urban agglomeration for 2013 and 2022 as the primary dataset. The varying gradient values indicate whether urban functions develop through trade-offs or synergy. The contributions of this study are: (1) We provide a more refined classification of urban functions compared to the coarse categorization used in existing methods; (2) The use of the shift-share model allows for a quantitative assessment of urban functional development; and (3) To explore reasons behind the distance gradients, we employ the SHAP model to analyze the driving factors behind the gradient effects. By applying our approach to the Yangtze River Delta, our findings indicate that urban functional evolution exhibits distinct distance-dependent patterns, with trade-offs and synergies varying across spatial scales. Additionally, nighttime light intensity and road network density changes play significant roles in shaping spatial reorganization.