Spatial Assessment of Community Resilience from 2012 Hurricane Sandy Using Nighttime Light

Quantitative assessment of community resilience is a challenge due to the lack of empirical data about human dynamics in disasters. To fill the data gap, this study explores the utility of nighttime lights (NTL) remote sensing images in assessing community recovery and resilience in natural disaster...

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Bibliographic Details
Published inRemote sensing (Basel, Switzerland) Vol. 13; no. 20; p. 4128
Main Authors Xu, Jinwen, Qiang, Yi
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.10.2021
Subjects
Archives & records
community resilience
Disasters
Economic indicators
Empirical analysis
GDP
GIS
Gross Domestic Product
Housing
human dynamics
Hurricanes
Land cover
Local communities
Mathematical analysis
Meteorological satellites
Natural disasters
Night
Nighttime
nighttime light remote sensing
Population
Regression analysis
Remote sensing
Resilience
Spatial analysis
Storm damage
Wind damage
Wind speed
Workflow
United States > US
New Jersey
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Summary:Quantitative assessment of community resilience is a challenge due to the lack of empirical data about human dynamics in disasters. To fill the data gap, this study explores the utility of nighttime lights (NTL) remote sensing images in assessing community recovery and resilience in natural disasters. Specifically, this study utilized the newly-released NASA moonlight-adjusted SNPP-VIIRS daily images to analyze spatiotemporal changes of NTL radiance in Hurricane Sandy (2012). Based on the conceptual framework of recovery trajectory, NTL disturbance and recovery during the hurricane were calculated at different spatial units and analyzed using spatial analysis tools. Regression analysis was applied to explore relations between the observed NTL changes and explanatory variables, such as wind speed, housing damage, land cover, and Twitter keywords. The result indicates potential factors of NTL changes and urban-rural disparities of disaster impacts and recovery. This study shows that NTL remote sensing images are a low-cost instrument to collect near-real-time, large-scale, and high-resolution human dynamics data in disasters, which provide a novel insight into community recovery and resilience. The uncovered spatial disparities of community recovery help improve disaster awareness and preparation of local communities and promote resilience against future disasters. The systematical documentation of the analysis workflow provides a reference for future research in the application of SNPP-VIIRS daily images.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs13204128