RESUMEN
The outbreak of the coronavirus disease 2019 (COVID-19) epidemic has resulted in large threats and damage to society and the economy. In this study, we evaluate and verify the comprehensive resilience and spatiotemporal impact of the COVID-19 epidemic from January to June 2022 in mainland China based on multisource data. First, we adopt a combination of the mandatory determination method and the coefficient of variation method to determine the weight of the urban resilience assessment index. Furthermore, Beijing, Shanghai, and Tianjin were selected to verify the feasibility and accuracy of the resilience assessment results based on the nighttime light data. Finally, the epidemic situation was dynamically monitored and verified with population migration data. The results show that urban comprehensive resilience of mainland China is shown in the distribution pattern of higher resilience in the middle east and south and lower resilience in the northwest and northeast. Moreover, the average light intensity index is inversely proportional to the number of newly confirmed and treated cases of COVID-19 in the local area. This study provides a scientific reference to improve the comprehensive resilience of cities to achieve the goals of sustainable development (SDGs 11): make cities and human settlements resilient and sustainable.
RESUMEN
Seismic disasters are sudden and unpredictable, often causing massive damage, casualties and socioeconomic losses. Rapid and accurate determination of the scale and degree of destruction of the seismic influence field in an affected area can aid in timely emergency rescue work after an earthquake. In this study, the relationship between the changes in four types of mobile signaling data and the seismic influence field was explored in the 2017 Jiuzhaigou earthquake-hit area, China, by using the methods of comparative analysis, regression analysis and spatial autocorrelation analysis. The results revealed that after the earthquake, the number of mobile signaling significantly decreased. The higher the intensity, the more obvious the reduction of mobile signaling data and the later the recovery time. The Loginmac and WiFi data showed greater sensitivity than Gid and Station. There was a significant correlation between the changes in the mobile signaling numbers and the seismic intensity, which can more accurately reflect the approximate extent of the seismic influence field and the degree of actual damage. The changes in mobile signaling can provide a helpful reference for the rapid determination of seismic influence fields.