No abstract

A sequence of two strike-slip earthquakes occurred on April 14 and 16, 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.

In this paper, we establish a novel multistep procedure for morphologic characterization of built environments in terms of built-up height and density. Thereby, we rely on elevation measurements from the TanDEM-X mission (TDM) and multispectral Sentinel-2 imagery. These earth observation systems feature a notable tradeoff between a fairly high spatial resolution and large-area coverage and, thus, allow for spatially continuous analysis of built environments around the globe. To this purpose, we follow an automated workflow which foresees the distinction of "built-up" and "non built-up" areas by relying on the so-called Global Urban Footprint processor (step 1). This information is deployed within a tailored filtering procedure for the TDM digital surface model data to extract elevation information for built-up areas (step 2). Subsequently, the intra-urban land cover is mapped under consideration of Sentinel-2 imagery and serves as basis to compute built-up heights and densities (step 3). These two measures are finally combined for a morphologic characterization of the built environment on an ordinal scale of measurement. Empirical validation efforts are provided based on comparative analysis with respect to more than 3.2 million individual building geometries and affiliated height measurements from cadastral data sources. The data sets cover the settlement areas of the capital cities and other major cities in Germany, England and the Netherlands. The experimental results underline the capability for a morphologic characterization of built environments with viable accuracies.

The M7.9 Wenchuan earthquake on May 12th, 2008 was the most destructive in China since 1976. The event caused huge damage and loss of life and exposed weaknesses both in the formulation and implementation of the regulations governing building in the affected provinces. Following the earthquake a massive relief and recovery operation was mounted by the Chinese government. The authors took part in field studies in the affected area which took place 5 and 11 months after the event, at which time recovery operations were well-advanced. The aims of the study were to assess the effects caused by the earthquake to the built environment and society, to collect information on the ongoing recovery efforts and future plans, and to demonstrate the use of tools that allow the collection of spatially referenced damage and recovery data. Based on available satellite imagery supplemented by ground observation, geodatabases were constructed containing information on damage and recovery in several parts of the affected area. The paper gives an overview of the recovery process, describes the methods used to construct these geodatabases, and offers some analysis of the data obtained. It is argued that such databases have great potential for the management of post-disaster recovery and for creating a permanent record of the recovery process.

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.

For the insurance and reinsurance industries, earthquake loss estimation is crucial not only to adequately price its product but also to manage the accumulation risk in the face of the ever-increasing exposure in highly seismic regions. Changes in the built environment and a continuously evolving earthquake science make it a necessity for the industry to constantly refine earthquake loss estimation models. In particular, it has been recognized for a long time that the vulnerability of buildings to ground shaking is a key parameter in any earthquake risk model. Current methods tend either to rely on the limited historical damage and loss data or on the numerical simulation of the response of individual buildings to the ground-shaking produced by earthquakes. Although both methods have their advantages and pitfalls, we are proposing here a simple solution, using transparent input data, that can be realistically used for the needs of the insurance and reinsurance industry, whether detailed information about the insured structures is available or not. The resulting product is known as GEVES (Global Earthquake Vulnerability Estimation System). It is primarily intended for evaluating the mean damage ratio (MDR) suffered by a portfolio of buildings classified by use, under the action of a given earthquake scenario (i.e. an earthquake of given size at a given distance from the portfolio of buildings). A key assumption was that macroseismic intensity rather than spectral displacement would be the basis of loss estimation. The paper describes the model with emphasis on its structure and the justification for the assumptions made. In addition to a new set of earthquake vulnerability functions, the paper also provides recommendations on some aspects of the earthquake hazard, in particular about how to define macroseismic intensity at the site of interest, for a given earthquake scenario. This paper also discusses validation of the GEVES model against calculated vulnerability approaches, and the treatment of uncertainty within the model.

Vulnerability functions often rely on data from expert opinion, post-earthquake investigations, or analytical simulations. Combining the information can be particularly challenging. In this paper, a Bayesian statistical framework is presented to combining disparate information. The framework is illustrated through application to earthquake mortality data obtained from the 2005 Pakistan earthquake and from PAGER. Three different models are tested including an exponential, a combination of Bernoulli and exponential and Bernoulli and gamma fit to model respectively zero and non-zero mortality rates. A novel Bayesian model for the Bernoulli-exponential and Bernoulli-gamma probability densities is introduced. It is found that the exponential distribution represents the zero casualties very poorly. The Bernoulli-exponential and Bernoulli-gamma models capture the data for both the zero and non-zero mortality rates. It is also shown that the Bernoulli-gamma model fits the 2005 Pakistan data the best and has uncertainties that are smaller than either the ones from the 2005 Pakistan data or the PAGER data.

On April 6, 2009 an earthquake of Magnitude 6.2 (M w ) struck the Abbruzzo region of Italy causing widespread damage to buildings in the city of L'Aquila and surrounding areas. This paper summarizes field observations made by the Earthquake Engineering Field Investigation Team (EEFIT) after the event. The paper presents an overview of seismological and geotechnical aspects of the earthquake as well as a summary of the observed damage to buildings and infrastructure. A brief overview of the earthquake casualties is also reported.