Rapid detection of earthquake damage areas using VIIRS nearly constant contrast night-time light data

Fan, Xiwei; Nie, Guigen; Deng, Yongming; An, Junling; Zhou, Junxue; Li, Huayue

doi:10.1080/01431161.2018.1460512

Cited by 33 publications

(19 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The overall accuracy, TRP, FPR and standard Kappa of using NTL to detect damage due to earthquakes were estimated to be 75.5%, 35.9%, 8.9%, and 0.31, respectively, in the Gorkha Nepal Earthquake. Previous research [41] used VIIRS NCC nighttime light to detect damage caused by three earthquakes with estimated overall accuracies of 75.0%, 68.4%, and 14.9%. Our result concurs with the highest accuracy of these three cases.…”

Section: Discussionmentioning

confidence: 99%

NPP-VIIRS DNB Daily Data in Natural Disaster Assessment: Evidence from Selected Case Studies

et al. 2018

View full text Add to dashboard Cite

Whereas monthly and annual nighttime light (NTL) composite datasets are being increasingly used to estimate socioeconomic status, use of the National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) Day/Night Band (DNB) daily data has been limited for detecting and assessing the impact of short-term disastrous events. This study explores the application of daily NPP-VIIRS DNB data in assessing the impact of three types of natural disasters: earthquakes, floods, and storms. Daily DNB images one month prior to and 10 days after a disastrous event were collected and a Percent of Normal Light (PNL) image was produced as the ratio of the mean DNB radiance of the pre- and post-disaster images. Areas with a PNL value lower than one were considered as being affected by the event. The results were compared with the damaged proxy map and the flood proxy map generated using synthetic aperture radar data as well as the reported power outage rates. Our analyses show that overall NPP-VIIRS DNB daily data are useful for detecting damages and power outages caused by earthquake, storm, and flood events. Cloud coverage was identified as a major limitation in using the DNB daily data; rescue activities, traffic, and socioeconomic status of the areas also affect the use of DNB daily data in assessing the impact of natural disasters. Our findings offer new insight into the use of the daily DNB data and provide a practical guide for researchers and practitioners who may consider using such data in different situations or regions.

show abstract

Section: Discussionmentioning

confidence: 99%

NPP-VIIRS DNB Daily Data in Natural Disaster Assessment: Evidence from Selected Case Studies

et al. 2018

View full text Add to dashboard Cite

show abstract

“…A comprehensive review of applications of NTL data can be found in Levin et al (2017) [20] and [21]. In the field of disaster management, previous work has applied NTL to detect property damage [22][23][24], power outages [25][26][27], and estimate economic recovery [15,16]. For example, and Wang et al (2018) used NTL data to detect power outages in natural disasters [25,27].…”

Section: Introductionmentioning

confidence: 99%

“…Due to these new features, the VIIRS daily images become a valuable data source to study human dynamics at a fine spatiotemporal resolution in natural disasters. Previous studies utilized the VIIRS daily images to detecting power outages [27,33], building and infrastructure damages [23,24]. Despite the potential of VIIRS images in disaster monitoring, its utility in assessing community recovery and resilience has not been systematically evaluated.…”

Section: Introductionmentioning

confidence: 99%

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

Qiang

2021

Remote Sensing

View full text Add to dashboard Cite

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.

show abstract

“…However, the retrieval error of the earthquake-injured population in Turkey was less than 50% of the actual survey value, which was due to the serious damage caused by the use of poor construction materials in some cities. Fan et al [73] used the confusion-matrix method to extract the urban areas affected by the earthquake based on NPP-VIIRS data. The overall accuracy for the two major Chilean earthquakes in 2014 and 2015 were 75% and 68.7%, respectively.…”

Section: Comparison Of Accuracy Of Retrieved Characteristics Of Naturmentioning

confidence: 99%

Rapid Assessment of a Typhoon Disaster Based on NPP-VIIRS DNB Daily Data: The Case of an Urban Agglomeration along Western Taiwan Straits, China

et al. 2019

View full text Add to dashboard Cite

Rapid assessment of natural disasters is essential for disaster analysis and spatially explicit strategic decisions of post-disaster reconstruction but requires timely available data. The recent daily data of the National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) day/night band (DNB) provide new opportunities to detect and evaluate natural disasters. Here, we introduce an application of NPP-VIIRS DNB daily data for rapidly assessing the damage of a severe typhoon that struck the urban agglomerations along the western Taiwan Straits in China. Our research explored the methods of rapid identification and extraction of the areas based on changes in nighttime light (NTL) after the typhoon disaster by using a statistical radiation-normalization method. We analyzed the correlations of NTL image derivatives with human population, population density, and gross domestic product (GDP). The strong correlations were found between NTL image light density and population density (R2 = 0.83) and between the total nighttime light intensity and GDP (R2 = 0.96) at the prefecture level. In addition, we examined the interrelationships between changes in NTL images and the areas affected by the typhoon and proposed a method to predict the affected population. Finally, the affected area and the affected population in the study area could be rapidly retrieved based on the proposed remote sensing method. The overall accuracy was 83.2% for the detection of the affected population after disaster and the recovery rate of the affected area was 86.9% in the third week after the typhoon. This research demonstrates that the NTL image-based change detection method is simple and effective, and further explains that the NPP-VIIRS DNB daily data are useful for rapidly assessing affected areas and affected populations after typhoon disasters, and for timely quantifying the degree of recovery at a large spatial scale.

show abstract

Rapid detection of earthquake damage areas using VIIRS nearly constant contrast night-time light data

Cited by 33 publications

References 29 publications

NPP-VIIRS DNB Daily Data in Natural Disaster Assessment: Evidence from Selected Case Studies

NPP-VIIRS DNB Daily Data in Natural Disaster Assessment: Evidence from Selected Case Studies

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

Rapid Assessment of a Typhoon Disaster Based on NPP-VIIRS DNB Daily Data: The Case of an Urban Agglomeration along Western Taiwan Straits, China

Contact Info

Product

Resources

About