Whole process assessment of flood resilience in urban and rural communities based on nighttime lights: A case study of Zhuozhou flood

Urban and rural communities are facing an increasingly severe risk of climate-related disasters, which underscores the urgency of enhancing their resilience to disasters. Existing research on climate disaster resilience faces issues such as difficulty in data acquisition and insufficient quantification in assessment methods. This study utilized the nighttime light (NTL) data to monitor the disturbance and recovery of socioeconomic activities during the flood event in Zhuozhou in July 2023(“23.7” flood). Based on the system function curve, a quantitative resilience assessment index was calculated using the temporal change characteristics of the NTL data. Factors that potentially influence resilience were explored by Geodetector. The findings indicate that the urban core areas were most severely affected by the flood. Although the recovery speed in the urban core areas was faster, the rural areas demonstrated stronger resilience than the urban core areas. Flood resilience in community is predominantly influenced by the degree of vegetation coverage and road density, succeeded by settlement density, GDP and population density. The approach proposed in this research enables resilience assessment of the whole disaster process. The outcomes can help Zhuozhou to formulate targeted flood control policies for urban and rural communities, and can also provide reference for research on flood resilience.