Observing community resilience from space: Using nighttime lights to model economic disturbance and recovery pattern in natural disaster

•A framework to assess community resilience using nighttime light remote sensing data.•Geographical disparities of economic disturbance and recovery in Hurricane Katrina.•Community resilience is related to various factors at different phases of a disaster.•Fill the gap of empirical data and methods...

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Vydáno v:Sustainable cities and society Ročník 57; s. 102115
Hlavní autoři: Qiang, Yi, Huang, Qingxu, Xu, Jinwen
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.06.2020
Témata:
DMSP/OLS
Economic recovery
Empirical assessment
Natural disaster
Nighttime lights
Resilience
Natural disaster
DMSP/OLS
Nighttime lights
Economic recovery
Empirical assessment
Resilience
ISSN:2210-6707, 2210-6715
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Shrnutí:•A framework to assess community resilience using nighttime light remote sensing data.•Geographical disparities of economic disturbance and recovery in Hurricane Katrina.•Community resilience is related to various factors at different phases of a disaster.•Fill the gap of empirical data and methods for measuring community resilience. A major challenge for measuring community resilience is the lack of empirical observations in disasters. As an effective tool to observe human activities on the earth surface, night-time light (NTL) remote sensing images can fill the gap of empirical data for measuring community resilience in natural disasters. This study introduces a quantitative framework to model recovery patterns of economic activity in a natural disaster using the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) images. The utility of the framework is demonstrated in a retrospective study of Hurricane Katrina, which uncovered the great economic impact of Katrina and spatial variation of the disturbance and recovery pattern of economic activity. Environmental and socio-economic factors that potentially influence economic recovery were explored in statistical analyses. Instead of a static and holistic index, the framework measures resilience as a dynamic process. The analysis results provide actionable information for prompting resilience in diverse communities and in different phases of a disaster. In addition to Hurricane Katrina, the resilience modeling framework is applicable for other disaster types. The introduced approaches and findings increase our understanding about the complexity of community resilience and provide support for developing resilient and sustainable communities.
ISSN:2210-6707
2210-6715
DOI:10.1016/j.scs.2020.102115