Dynamic shading assessment and route optimization for pedestrian lanes: a case study of Wuhan's central urban area

Shading plays a crucial role in improving urban microclimate and reducing the risk of direct solar exposure for pedestrians. Current studies on urban shading analysis primarily rely on indirect indicators such as tree crown projected area or vegetation coverage. However, these methods cannot adequately capture dynamic shading variations, seasonal differences, or the overlapping shading effects of multiple elements. Focusing on Wuhan's central urban area, this study used multi-source open data to develop a dynamic method to generate and calculate the shading areas of pedestrian lanes from buildings and tree canopies, and proposed a classification framework to characterize shading features across temporal variations, spatial patterns, and pedestrian lane types. To reveal the driving factors of pedestrian lane shading distributions, Optuna hyperparameter optimization, multi-model comparison, and SHAP analysis were performed with 5 shading-related factors. Results indicated that the annual average shading rate of pedestrian lanes in Wuhan was 35.10%, with trees and buildings contributing 66.98% and 43.41%, respectively, and overlap shading accounting for 10.40%. The shading distributions exhibited significant spatiotemporal heterogeneity. SHAP attribution revealed that among the selected indicators, the total tree canopy vertical projection proportion and building height were the primary positive driving factors. Based on the findings, this study proposed specific optimization strategies for pedestrian lane shading and developed a dynamic pedestrian route optimization add-in for both shade-seeking in summer and sunlight-seeking in winter. The proposed method could support climate-adaptive optimization of urban road networks and solar-comfort-based pedestrian path planning in map navigation.