Abstract

This article demonstrates the potential of Defense Meteorological Satellite Program-Operational Linescan System stable nighttime light imagery for county-level earthquake resilience analysis. In this article, we firstly intercalibrated the nighttime light data and calculated the total sum of stable lights for each of the 261 counties affected by the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Mw</i> 7.9 Wenchuan earthquake from 1992 to 2013; secondly established an earthquake resilience model based on a nighttime light index to analyze the static and dynamic resilience of different counties; and lastly discussed the possible influencing factors from geographic, disaster-related, political and socioeconomic perspectives. The results first show that the static resilience of the extremely hard-hit counties in the Wenchuan earthquake-affected area increased from south to north along the long axis of the intensity zone, and plain and hilly counties exhibited faster short-term economic recovery than plateau and mountainous counties. Moreover, all extremely hard-hit counties except Wenchuan, Dujiangyan and Pingwu recovered to the normal level before 2011, whereas 52% of the counties in the generally affected areas recovered within three years. Through linear regression analysis, we also found that the different earthquake resilience capabilities across counties are most likely related to the soil liquefaction risk, average elevation, land-use degree, and socioeconomic factors, such as the industrial structure, the population age distribution, and social welfare.

Highlights

  • E ARTHQUAKES, which have a wide range of negative impacts and long recovery times, constitute some of the most devastating natural disasters

  • According to the literature [2]–[4], the concept of disaster resilience includes two connotations: the first is the ability of a system to withstand the shock of a disaster and reduce disaster losses; the second is the ability of a system to quickly adapt and return to a pre-event or stable state

  • We see a decline in the total sum of lights (TSOL) curve of generally affected (GA) counties but increases in the TSOL curves of severely damaged (SD) and extremely hard-hit (EH) counties

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Summary

Introduction

E ARTHQUAKES, which have a wide range of negative impacts and long recovery times, constitute some of the most devastating natural disasters. Date of publication October 21, 2021; date of current version November 5, 2021. Resilience, in contrast to vulnerability or fragility, is a key concept commonly used in disaster research that refers to the ability to recover from disasters [1]. According to the literature [2]–[4], the concept of disaster resilience includes two connotations: the first is the ability of a system to withstand the shock of a disaster and reduce disaster losses (static resilience or robustness); the second is the ability of a system to quickly adapt and return to a pre-event or stable state (dynamic resilience or rapidity)

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