Emily So

Estimating shaking-induced casualties and building damage for global earthquake events: a proposed modelling approach

Recent earthquakes such as the Haiti earthquake of 12 January 2010 and the Qinghai earthquake on 14 April 2010 have highlighted the importance of rapid estimation of casualties after the event for humanitarian response. Both of these events resulted in surprisingly high death tolls, casualties and survivors made homeless. In the Mw = 7.0 Haiti earthquake, over 200,000 people perished with more than 300,000 reported injuries and 2 million made homeless. The Mw = 6.9 earthquake in Qinghai resulted in over 2,000 deaths with a further 11,000 people with serious or moderate injuries and 100,000 people have been left homeless in this mountainous region of China. In such events relief efforts can be significantly benefitted by the availability of rapid estimation and mapping of expected casualties. This paper contributes to ongoing global efforts to estimate probable earthquake casualties very rapidly after an earthquake has taken place. The analysis uses the assembled empirical damage and casualty data in the Cambridge Earthquake Impacts Database (CEQID) and explores data by event and across events to test the relationships of building and fatality distributions to the main explanatory variables of building type, building damage level and earthquake intensity. The prototype global casualty estimation model described here uses a semi-empirical approach that estimates damage rates for different classes of buildings present in the local building stock, and then relates fatality rates to the damage rates of each class of buildings. This approach accounts for the effect of the very different types of buildings (by climatic zone, urban or rural location, culture, income level etc), on casualties. The resulting casualty parameters were tested against the overall casualty data from several historical earthquakes in CEQID; a reasonable fit was found.

A Global Earthquake Building Damage and Casualty Database

This chapter presents a preliminary overview of the Cambridge University Earthquake Damage Database (CUEDD) now the Cambridge Earthquake Impact Database (CEQID) with emphasis on its human casualty component. CUEDD is based on earthquake damage data assembled by the Martin Centre at Cambridge University since 1980, complemented by other more-recently published and some unpublished data. The database through its organised, expandable and web-accessible format, summarizes information on worldwide post-earthquake building damage surveys which have been carried out since the 1960s (www.ceqid.org). Currently it contains data on the performance of more than 1.3 million individual buildings, in 600 surveys following 50 separate earthquakes. The database provides total recorded casualties (deaths, seriously and moderately injured), and casualty rates as a proportion of population with definitions of injury levels used, and information on dominant types of injury, age groups affected, etc. It also provides geographically disaggregated data where possible, and associates them with tables and GIS maps. Sources of information on other aspects of human casualty information (epidemiological studies, health care impacts, etc.) are provided. Analytical tools enable relationships between casualty rates, building classes and ground motion parameters to be determined.

The 2016 Kumamoto Earthquakes: Cascading Geological Hazards and Compounding Risks

A sequence of two strike-slip earthquakes occurred on 14 and 16 April 2016 in the intraplate region of Kyushu Island, Japan, apart from subduction zones, and caused significant damage and disruption to the Kumamoto region. The analyses of regional seismic catalog and available strong motion recordings reveal striking characteristics of the events, such as migrating seismicity, earthquake surface rupture, and major foreshock-mainshock earthquake sequences. To gain valuable lessons from the events, a UK Earthquake Engineering Field Investigation Team (EEFIT) was dispatched to Kumamoto, and earthquake damage surveys were conducted to relate observed earthquake characteristics to building and infrastructure damage caused by the earthquakes. The lessons learnt from the reconnaissance mission have important implications on current seismic design practice regarding the required seismic resistance of structures under multiple shocks and the seismic design of infrastructure subject to large ground deformation. The observations also highlight the consequences of cascading geological hazards on community resilience. To share the gathered damage data widely, geo-tagged photos are organized using Google Earth and the kmz file is made publicly available.

Speed or deliberation: a comparison of post-disaster recovery in Japan, Turkey, and Chile

This paper compares recovery in the wake of three recent earthquakes: the Great East Japan Earthquake in March 2011; the Van earthquake in Turkey in October 2011; and the Maule earthquake in Chile in February 2010. The authors visited all three locations approximately 12-18 months after the incidents and interviewed earthquake specialists, disaster managers, urban planners, and local authorities. A key challenge to post-disaster recovery planning is balancing speed and deliberation. While affected communities must rebuild as quickly as possible, they must also seek to maximise the opportunities for improvement that disasters provide. The three case studies bring this dilemma into stark relief, as recovery was respectively slow, fast, and just right in the aftermath of the events: the Government of Japan adopted a deliberate approach to recovery and reconstruction; speed was of the essence in Turkey; and an effective balance between speed and deliberation was achieved in Chile.

Detecting tents to estimate the displaced populations for post-disaster relief using high resolution satellite imagery

Abstract Estimating the number of refugees and internally displaced persons is important for planning and managing an efficient relief operation following disasters and conflicts. Accurate estimates of refugee numbers can be inferred from the number of tents. Extracting tents from high-resolution satellite imagery has recently been suggested. However, it is still a significant challenge to extract tents automatically and reliably from remote sensing imagery. This paper describes a novel automated method, which is based on mathematical morphology, to generate a camp map to estimate the refugee numbers by counting tents on the camp map. The method is especially useful in detecting objects with a clear shape, size, and significant spectral contrast with their surroundings. Results for two study sites with different satellite sensors and different spatial resolutions demonstrate that the method achieves good performance in detecting tents. The overall accuracy can be up to 81% in this study. Further improvements should be possible if over-identified isolated single pixel objects can be filtered. The performance of the method is impacted by spectral characteristics of satellite sensors and image scenes, such as the extent of area of interest and the spatial arrangement of tents. It is expected that the image scene would have a much higher influence on the performance of the method than the sensor characteristics.

Enhanced change detection index for disaster response, recovery assessment and monitoring of accessibility and open spaces (camp sites)

Abstract The availability of Very High Resolution (VHR) optical sensors and a growing image archive that is frequently updated, allows the use of change detection in post-disaster recovery and monitoring for robust and rapid results. The proposed semi-automated GIS object-based method uses readily available pre-disaster GIS data and adds existing knowledge into the processing to enhance change detection. It also allows targeting specific types of changes pertaining to similar man-made objects. This change detection method is based on pre/post normalized index, gradient of intensity, texture and edge similarity filters within the object and a set of training data. Once the change is quantified, based on training data, the method can be used automatically to detect change in order to observe recovery over time in large areas. Analysis over time can also contribute to obtaining a full picture of the recovery and development after disaster, thereby giving managers a better understanding of productive management practices.

The Capabilities of Earth Observation to Contribute along the Risk Cycle

The complexity of earthquake events and their manifold effects uncovers a strong niche for interdisciplinary and multidisciplinary analyses. Remote sensing data and methods are nowadays widely deployed to contribute information along the risk cycle. In this chapter, we document these contributions and discuss limitations simultaneously by means of an in-depth literature survey and presentation of selected examples. These include hazard-centered analysis such as site characterization and quantification of surface deformations in preevent and postevent applications. Furthermore, preevent seismic vulnerability-centered assessments of the built and natural environment are presented, which build upon the capability of remote sensing to map elements at risk, area wide. Lastly, damage assessment for postevent applications is discussed and completed by demonstrating recovery monitoring capabilities.

Enhanced change detection index for disaster response, recovery assessment and monitoring of buildings and critical facilities—A case study for Muzzaffarabad, Pakistan

Abstract The availability of Very High Resolution (VHR) optical sensors and a growing image archive that is frequently updated, allows the use of change detection in post-disaster recovery and monitoring for robust and rapid results. The proposed semi-automated GIS object-based method uses readily available pre-disaster GIS data and adds existing knowledge into the processing to enhance change detection. It also allows targeting specific types of changes pertaining to similar man-made objects such as buildings and critical facilities. The change detection method is based on pre/post normalized index, gradient of intensity, texture and edge similarity filters within the object and a set of training data. More emphasis is put on the building edges to capture the structural damage in quantifying change after disaster. Once the change is quantified, based on training data, the method can be used automatically to detect change in order to observe recovery over time in potentially large areas. Analysis over time can also contribute to obtaining a full picture of the recovery and development after disaster, thereby giving managers a better understanding of productive management and recovery practices. The recovery and monitoring can be analyzed using the index in zones extending from to epicentre of disaster or administrative boundaries over time.

Assignments of Judgment-Based Fatality Rates

The following chapter discusses the assignments of judgment-based fatality rates. The reference earthquakes and data used to derive a set of proposed fatality rates given the collapses of different structural types are systematically examined.

Supporting Literature for Deriving Fatality Rates

One of the main issues of casualty modeling has been a lack of good empirical data from past events from which to derive realistic fatality rates. The quality and consistency of data are also major concerns; hence in collating data for this book, a concerted effort was made in obtaining and assembling global casualty information from recent earthquakes.