Over the past 20 years, our understanding of volcanic eruption impacts on the built environment has transformed from being primarily observational with small datasets to one grounded in field investigations, laboratory experiments, and quantitative modeling, with an emphasis on stakeholder collaboration and co-creation. Here, we summarize key advances and knowledge gaps of impacts across volcanic hazards and built environment types from the past 20 + years. Studies have concentrated on impacts from tephra fall (ash) and to buildings, with less examination of other hazards' impacts to critical infrastructure. As we look to the next decade, we speculate on likely research directions, including the increasing role of new technologies, higher resolution modeling, transdisciplinary collaborations, and evidence-based mitigative solutions.

This paper describes CEQID, a database of earthquake damage and casualty data assembled since the 1980s based on post-earthquake damage surveys conducted by a range of research groups. Following 2017–2019 updates, the database contains damage data for more than five million individual buildings in over 1000 survey locations following 79 severely damaging earthquakes worldwide. The building damage data for five broadly defined masonry and reinforced concrete building classes has been assembled and a uniform set of six damage levels assigned. Using estimated peak ground acceleration (PGA) for each survey location based on USGS Shakemap data, a set of lognormal fragility curves has been developed to estimate the probability of exceedance of each damage level for each class, and separate fragility curves for each of five geographical regions are presented. A revised set of fragility curves has also been prepared in which the bias in the curve resulting from the uncertainty in the ground motion parameter has been removed. The uncertainty in the fragility curves is evaluated and discussed and the curves are compared with those from other studies. A resistance index for each class of building is developed and cross-regional comparisons using this resistance index are presented.

In an effort to incorporate building fragility into seismic risk assessment, simple formulations of fragility functions are developed, such as a cumulative lognormal distribution, which describe the probability of damage of a building experiencing a given ground motion. We show here that when a lognormal fragility function is empirically estimated from data with uncertainty on the intensity of ground motion experienced by buildings, the estimate is biased towards fragility functions with larger variances. We show that this bias, due to the uncertainty on the ground motion, can be semi-analytically determined and we devise a methodology to correct for it.

This study explores the performance of GEOCAN, a remote-sensing and crowdsourcing platform for assessing earthquake damage, by using georeferenced ground-based damage assessments. This paper discusses methods for the application of remote sensing in post-earthquake damage assessment and reports on a GEOCAN crowd-sourcing study following the 22 February 2011 Christchurch event and its validation using field studies. It describes the principal data sets used, discusses in detail the problems of validation, and considers the extent of omission and commission errors. It is clear that although commission errors in the GEOCAN damage estimation are low, the omission error is significant (64%); the extent of these and the causal factors are analyzed with a decision model. The results show that the image-based analysis in this case does not reproduce the spatial pattern or magnitude of the damage impact. Finally, recommendations to improve the performance of GEOCAN in subsequent deployments are made.

This paper aims to review the nature and practice of earthquake reconnaissance missions since the earliest examples to today’s practice, and to try to show some of the ways in which the practice of earthquake engineering today has benefitted from field observations. To give some historical background, the nature of some of the earliest recorded field missions are reviewed, notably that of Mallet following the 1857 Neapolitan earthquake; the achievements of the UNESCO-supported missions of the period 1963–1980 are considered; and the nature and contributions made by several national earthquake reconnaissance teams (EERI based in the United States, EEFIT based in the UK, and more briefly the Japanese Society for Civil Engineering, the German Earthquake Task Force, and AFPS based in France) are reviewed. The paper then attempts to summarise what have been the most important contributions from the field observations to several aspects of earthquake engineering, particularly to understanding the performance of buildings, both engineered and non-engineered, including historical structures, to geotechnical effects, to gaining understanding of the social and economic consequences of earthquakes, and to loss estimation from future scenario events. The uses and limitations of remote sensing technologies to assess damage caused by an earthquake are considered. Finally, possible changes in earthquake field missions to meet anticipated future challenges and opportunities are discussed.

This paper presents structured and cost-effective methods for assessing the physical vulnerability of at-risk communities to the range of volcanic hazards, developed as part of the MIA-VITA project (2009–2012). An initial assessment of building and infrastructure vulnerability has been carried out for a set of broadly defined building types and infrastructure categories, with the likelihood of damage considered separately for projectile impact, ash fall loading, pyroclastic density current dynamic pressure and earthquake ground shaking intensities. In refining these estimates for two case study areas: Kanlaon volcano in the Philippines and Fogo volcano in Cape Verde, we have developed guidelines and methodologies for carrying out physical vulnerability assessments in the field. These include identifying primary building characteristics, such as construction material and method, as well as subsidiary characteristics, for example the size and prevalence of openings, that may be important in assessing eruption impacts. At-risk buildings around Kanlaon were found to be dominated by timber frame buildings that exhibit a high vulnerability to pyroclastic density currents, but a low vulnerability to failure from seismic shaking. Around Fogo, the predominance of unreinforced masonry buildings with reinforced concrete slab roofs suggests a high vulnerability to volcanic earthquake but a low vulnerability to ash fall loading. Given the importance of agriculture for local livelihoods around Kanlaon and Fogo, we discuss the potential impact of infrastructure vulnerability for local agricultural economies, with implications for volcanic areas worldwide. These methodologies and tools go some way towards offering a standardised approach to carrying out future vulnerability assessments for populated volcanic areas.

This Report was commissioned by the GEM Foundation as a component of the GEM Inventory Data Capture Tools (IDCT Project). Funding came from the GEM Foundation through IDCT, and additional funding was provided by the Willis Research Network. The report discusses methods for the application of remote sensing in post-earthquake damage assessment, and reports on a GEOCAN crowd-sourcing study following the 22.2.2011 Christchurch event, and its validation using field studies. It describes the principal datasets used, discusses in detail the problems of validation, and considers the extent of omission and commission errors. It is clear that although commission errors in the GEOCAN damage estimation are low, there are significant omission errors; the extent of these and the factors affecting the extent of omission errors are analysed with a decision model. Recommendations to improve the performance of GEOCAN in subsequent deployments are made.

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.

The large explosive eruption of Merapi volcano, Indonesia, in 2010 presented a key, and rare, opportunity to study the impacts of a major explosive eruption in a densely populated area. Pyroclastic density currents (PDCs) produced throughout the 2010 eruption were unusually destructive, causing near complete devastation across a 22km2 swath of the densely populated southern flanks and casualties to the end of their runout at 15.5km from the volcano. The majority (>120) of the more than 200 fatalities occurred more than 12km from the volcano, where many people were caught in PDCs as they were evacuating. The 2010 eruption (VEI 4) exhibited a range of PDC behaviour in a complex multi-stage event that marked a change in eruption behaviour at Merapi, being the first eruption of this magnitude and style since 1872. This shift in style may mark a change in regime, and so understanding the potential impact of such large explosive eruptions is essential for future risk-assessment at Merapi. We describe a new impact assessment methodology that allowed us to collect important empirical geological, damage and casualty information and reconstruct impact dynamics associated with the PDCs. In contrast to previous PDC impact studies, we combined remote, field, laboratory and GIS assessments and were able to enter the affected areas safely and before their disturbance by rains or human activity. By integrating the results of our geological, damage and medical studies, we could reconstruct the spatial and temporal dynamics of the PDCs and their main hazard characteristics. Our interdisciplinary methods and preliminary findings are discussed here. In the areas damaged by PDCs, we used empirical damage data and calculations of material and structural resistance to lateral force to estimate approximate dynamic pressures. Dynamic pressures associated with the 5 November paroxysm exceeded 15kPa more than 6km from source and rapidly attenuated over a distance of less than 1km at the end of the PDC runouts. Analysis of thermal indicators, such as deformed plastic, and correlation with information on burns injuries and fires provided estimates of ambient temperatures associated with the PDCs. Even at the relatively low temperatures estimated for the PDCs (200–300°C) they were lethal to people inside as well as outside buildings, in part because of the building design that enabled the PDCs to rapidly infiltrate inside. Such detailed quantitative data can be used to support numerical PDC and impact modelling and risk assessment at dome-forming volcanoes, providing an improved understanding of the complexity of PDCs and their associated impacts on exposed populations.

This paper discusses methods for the application of remote sensing in post earthquake damage assessment, and reports on a GEO-CAN crowd-sourcing study following the 22.2.2011 Christchurch event, and its validation using field studies. It describes the principal datasets used, discusses in detail the problems of validation, and considers the extent of omission and commission errors. It is clear that although commission errors in the GEO-CAN damage estimation are low, there are significant omission errors; but the precise extent of these is difficult to define, because of the nature of the datasets used. The paper concludes with some recommendations for improving data collection for future investigations.

The UK Earthquake Engineering Field Investigation Team (Eefit) was established as an independent society in 1982. Between 1984 and 2011, it carried out field missions to 29 earthquake zones, with reports on all of them freely available online. Over a hundred UK-based engineers have participated, split almost equally between industry and academia. There have been a number of significant benefits, including training through observations of the practical effects of ground shaking, fostering strong links between practising and academic participants, establishing international links and gathering data for research into a wide range of earthquake engineering topics. The paper outlines Eefit’s history and development, sets out its achievements and presents details of a recent 5-year government grant that will extend its effectiveness still further.

This paper discusses a methodology to collect building inventory data by combining image processing techniques, field work or tools such as Google Street View and applying statistical inferences. Following the methodology outlined in Marinescu (2002), a family of Gabor filters are first constructed, which are then applied to an optical high-resolution image. The output from the processed image is segmented using Self-Organising Maps. This paper examines the relationship between the segmented areas in the image and the building type distribution within each segmented area, by deriving the distribution from field data. The relationship between the average number of buildings in these cells against the number of grid cells allocated to each segmentation cluster is also investigated. Finally, using these results, the overall building inventory distribution for the whole of the case study site of Pylos is presented.