Risk assessment of people trapped in earthquake based on km grid: a case study of the 2014 Ludian earthquake, China

Wei, Benyong; Nie, Guigen; Su, Guiwu; Sun, Lei; Bai, Xianfu; Qi, Wenbao

doi:10.1080/19475705.2017.1318795

Cited by 34 publications

(13 citation statements)

References 25 publications

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“…In order to improve the efficiency of our estimations, we developed a two-step casualty estimation method. In the first step, we combined the geomorphologic features of the earthquake zone, seismic parameters and gridded population data [ 37 , 38 ] into Building Damage Evaluation Model [ 39 ] and Casualty Estimation Model [ 40 ] to predict casualties in the disaster area very quickly. In the second step, the high-resolution remote sensing data acquired pre and post-earthquake was used to extract damage building information.…”

Section: Methodsmentioning

confidence: 99%

A Rapid Public Health Needs Assessment Framework for after Major Earthquakes Using High-Resolution Satellite Imagery

Zhao

Ding

Wang

et al. 2018

IJERPH

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Background: Earthquakes causing significant damage have occurred frequently in China, producing enormous health losses, damage to the environment and public health issues. Timely public health response is crucial to reduce mortality and morbidity and promote overall effectiveness of rescue efforts after a major earthquake. Methods: A rapid assessment framework was established based on GIS technology and high-resolution remote sensing images. A two-step casualties and injures estimation method was developed to evaluate health loss with great rapidity. Historical data and health resources information was reviewed to evaluate the damage condition of medical resources and public health issues. Results: The casualties and injures are estimated within a few hours after an earthquake. For the Wenchuan earthquake, which killed about 96,000 people and injured about 288,000, the estimation accuracy is about 77%. 242/294 (82.3%) of the medical existing institutions were severely damaged. About 40,000 tons of safe drinking water was needed every day to ensure basic living needs. The risk of water-borne and foodborne disease, respiratory and close contact transmission disease is high. For natural foci diseases, the high-risk area of schistosomiasis was mapped in Lushan County as an example. Finally, temporary settlements for victims of earthquake were mapped. Conclusions: High resolution Earth observation technology can provide a scientific basis for public health emergency management in the major disasters field, which will be of great significance in helping policy makers effectively improve health service ability and public health emergency management in prevention and control of infectious diseases and risk assessment.

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Section: Methodsmentioning

confidence: 99%

A Rapid Public Health Needs Assessment Framework for after Major Earthquakes Using High-Resolution Satellite Imagery

Zhao

Ding

Wang

et al. 2018

IJERPH

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“…where RD is the mortality rate of the earthquake (the ratio of the number of casualties to the total population), RA is the proportion of collapsed and destroyed buildings in the earthquake area, α is the overall LL in the earthquake area, ρ is the population density in the earthquake area, and P t is the average occupancy rate of personnel (i.e., the average proportion of personnel in buildings during the earthquake). Among them, the average occupancy rate mainly refers to the research of relevant scholars: during the daytime, the average occupancy rate is 0.75, whereas at night, the occupancy rate is set as 1 (Xu et al, 2008;Wei et al, 2017).…”

Section: Lethal Level Modelmentioning

confidence: 99%

Research on lethal levels of buildings based on historical seismic data

Xia

Nie

et al. 2023

Front. Earth Sci.

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Due to the influences of buildings, geographical and geomorphological environments, road conditions, etc., the probabilities and numbers of casualties in different areas after an earthquake are different. Accordingly, we propose the concept of the lethal level, which attains different grades representing the mortality rate of differing intensities. Different regions have unique lethal levels, and regional lethal levels are affected mainly by the proportion of each building type and the corresponding lethal level, as different types of buildings also have unique lethal levels. Based on data of 52 historical earthquake disasters, we constructed a lethal level calculation model and obtained the lethal level of each building type. The results reveal that the lethal level ranges of different building types are fixed and unequal; moreover, the ranges of different building types overlap each other. The lethal level range of adobe structures is 0.85–1, that of civil structures is 0.75–0.95, that of brick-wood structures is 0.6–0.9, that of brick-concrete structures is 0.33–0.6, that of wood structures is 0.2–0.35, and that of reinforced concrete structures is 0.1–0.25. Based on the lethal levels of these building types, the overall level of a region can be quantified and graded, and this classification does not depend on the geographical location or administrative boundaries. In pre-earthquake evaluation efforts, the lethal level of an area can be derived through field research. After an earthquake, the number of casualties can be quickly assessed based on the mortality rate corresponding to the intensity of the area. This approach can further provide scientific support for risk zoning and risk assessment research.

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“…Dai et al [ 27 ] used a spatiotemporal clustering method to analyze post-earthquake population evacuations and determine earthquake impacts based on mobile signaling data. In combination with traditional empirical assessment models, the application of mobile signaling data can provide timely and powerful technical support for post-disaster emergency relief, thus further improving the efficiency of emergency relief [ 42 ]. However, the study of mobile phone signaling data is still in the exploration stage.…”

Section: Introductionmentioning

confidence: 99%

Application of Mobile Signaling Data in Determining the Seismic Influence Field: A Case Study of the 2017 Mw 6.5 Jiuzhaigou Earthquake, China

Guo

Wei

Nie

et al. 2022

IJERPH

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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.

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Risk assessment of people trapped in earthquake based on km grid: a case study of the 2014 Ludian earthquake, China

Cited by 34 publications

References 25 publications

A Rapid Public Health Needs Assessment Framework for after Major Earthquakes Using High-Resolution Satellite Imagery

A Rapid Public Health Needs Assessment Framework for after Major Earthquakes Using High-Resolution Satellite Imagery

Research on lethal levels of buildings based on historical seismic data

Application of Mobile Signaling Data in Determining the Seismic Influence Field: A Case Study of the 2017 Mw 6.5 Jiuzhaigou Earthquake, China

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