基于动态轨迹数据的城市滨水空间雨洪韧性评价方法研究——以深圳市盐田区为例OACHSSCD

Urban flood resilience assessment requires the integration of multidimensional factors,including socioeconomic conditions,population exposure,and built environment characteristics.Traditional population exposure assessments primarily rely on static population data,which often fail to capture real-time human activity patterns,leading to evaluation biases.To enhance the adaptive capacity of waterfront spaces to flood disturbances,this study proposes a novel flood resilience assessment method for built environments that incorporates movement trajectory data.Taking Yantian District,Shenzhen,as a case study,we employ the entropy-weighted TOPSIS method to construct a comprehensive evaluation framework,considering flood absorption,adaptation,and recovery capacities(e.g.,green space ratio,road network density)as well as population exposure features(static population density and dynamic movement trajectory density).A comparative analysis is conducted between static-dynamic integrated assessments and static-only assessments.The findings reveal that:(1)the incorporation of dynamic trajectory data significantly improves the accuracy of resilience assessments;and(2)static-only assessment methods tend to systematically overestimate regional resilience levels.This research provides a new data perspective and methodological framework for urban flood resilience assessment,particularly highlighting the critical role of dynamic human activity characteristics in enhancing evaluation precision.