2007 August 15 Magnitude 7.9 Earthquake near the Coast of Central Peru

A field reconnaissance mission was led to the areas affected by the disaster caused by the Magnitude 7.9 earthquake event of 15/08/2007 near the city of Pisco in Peru. The main objectives of the mission were to collect data and make observations leading to improvements in design methods and techniques for strengthening and retrofit, and to assist the phase of reconstruction. The mission focused on the behaviour of non-engineered structures, in particular those of adobe constructions. The findings of the mission confirmed that most of the damage was observed on adobe houses constructed with traditional non anti-seismic techniques which either collapsed or nearly collapsed, causing 519 deaths, 1,366 injuries and more than 58,000 houses destroyed. The mission also confirmed that buildings constructed according to modern earthquake resistant design standards performed with no evident damage. All the parties contacted during the mission, especially the EC Delegation, showed particular interest in the results of the present mission report, which will be taken into consideration when planning the reconstruction phase, especially of the most distant rural areas, where close collaboration between the Governmental Institutions, International Organizations, Universities and NGO¿s, will be needed to assist the population for the adoption of earthquake resistant designs in the reconstruction of the destroyed houses.JRC.G.5-European laboratory for structural assessmen

Disaster Reconnaissance Missions: Is a Hybrid Approach the Way Forward?

When a catastrophic natural hazard event occurs, it causes human casualties, damage to buildings and infrastructure, and affects livelihoods, society, and the wider economy. Much of the damage caused by natural disasters is visible only for a short time, because search and rescue, demolition and rebuilding often start within a few days. It is therefore important that damage assessments start rapidly after an event. For the earthquake community, the need for speedy but systematic post-earthquake investigations has led to the formation of several international earthquake reconnaissance teams whose aim is to be available for rapid deployment after an earthquake. They are composed of earthquake specialists from different disciplines, and generally include team members from the affected countries. Each team conducts a survey whose exact scope depends on the scale and type of damage. But the study generally includes investigations of the seismological and geological aspects of the event, the damage to buildings and to infrastructure, and the way in which relief and rescue have been conducted. On return, the team typically communicates their findings through technical meetings and produces a report which is commonly made available on openly accessible websites. The Learning from Earthquakes programme of the California-based Earthquake Engineering Research Institute (EERI1) has the most experience in such field reconnaissance missions and has conducted more than 150 investigations since it began after the 1971 San Fernando, California earthquake. In the United Kingdom, the Earthquake Engineering Field Investigation Team (EEFIT2) is a joint venture between industry and universities and has conducted more than 30 investigations since its formation in 1982 following the Irpinia (Italy) earthquake of 1980. Similar organisations exist in several other countries (Spence, 2014). The cross-cultivation of these findings across different historical events have been fundamental in improving our science. The cumulative findings of the missions have been instrumental in formulating research programmes worldwide, which have studied aspects of the physical damage, response, and recovery from multiple events. These research programmes in turn have led to steady improvements of national and international codes of practice for building, as well as assisting in understanding the vulnerability of different types of affected facilities and in developing ways to enhance earthquake safety internationally (Spence and So, 2021). Disasters that occurred in 2020 and 2021 during the COVID-19 pandemic challenged the disaster risk resilience community to come up with alternative ways of achieving the objectives of a reconnaissance activity. With international travel being disrupted, teams were unable to physically go to the disaster-stricken areas for a field study of damage to buildings and infrastructure. This situation was attempted to be overcome through hybrid missions. These combined remotely coordinated fieldwork and assessment of alternative data sources for deployment for a remote investigation, as detailed in what follows

Global Mapping of Exposure and Physical Vulnerability Dynamics in Least Developed Countries using Remote Sensing and Machine Learning

As the world marked the midterm of the Sendai Framework for Disaster Risk Reduction 2015-2030, many countries are still struggling to monitor their climate and disaster risk because of the expensive large-scale survey of the distribution of exposure and physical vulnerability and, hence, are not on track in reducing risks amidst the intensifying effects of climate change. We present an ongoing effort in mapping this vital information using machine learning and time-series remote sensing from publicly available Sentinel-1 SAR GRD and Sentinel-2 Harmonized MSI. We introduce the development of "OpenSendaiBench" consisting of 47 countries wherein most are least developed (LDCs), trained ResNet-50 deep learning models, and demonstrated the region of Dhaka, Bangladesh by mapping the distribution of its informal constructions. As a pioneering effort in auditing global disaster risk over time, this paper aims to advance the area of large-scale risk quantification in informing our collective long-term efforts in reducing climate and disaster risk.Comment: This is the camera-ready paper for the accepted poster at the 2nd Machine Learning for Remote Sensing Workshop, 12th International Conference on Learning Representations (ICLR) in Vienna, Austria, on the 11th of May 2024. Access the poster here: https://zenodo.org/doi/10.5281/zenodo.10903886 Watch the video version of our poster here: https://youtu.be/N6ithJeCF4

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

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.EU FP

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

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.EU FP

Formation sur la spiritualité pour les étudiants en médecine canadiens : la perception des étudiants d’une séance de compétences cliniques portant sur l’anamnèse spirituelle

Implication Statement Spirituality involves one’s sense of purpose, connection with others, and ability to find meaning in life. We implemented a three-year pilot of a spiritual history taking (SHT) clinical skills session. In small groups, medical students discussed and practiced SHT with clinical scenarios and the FICA framework and received preceptor and peer feedback. Post-session focus groups and interviews demonstrated student perceptions of improved comfort, knowledge, and awareness of discussing spirituality with patients. This innovation may support improved clinical skills teaching across other health professions institutions to better prepare students to recognize patients’ spiritual needs and provide more holistic, culturally competent care.Énoncé des implications de la recherche La spiritualité touche au sentiment d’avoir un but, à la relation à l’autre et à la capacité de trouver un sens à la vie. Nous avons introduit, comme projet pilote de trois ans, une séance de compétences cliniques portant sur l’anamnèse spirituelle (AS). En petits groupes, les étudiants pratiquaient et discutaient de l’anamnèse spirituelle à l’aide de scénarios cliniques et du questionnaire d’anamnèse spirituelle FICA, et recevaient ensuite des commentaires de la part de leur précepteur et de leurs pairs. Les groupes de discussion et les entretiens après les séances ont montré que les étudiants se sentaient mieux informés, plus à l’aise et plus conscients de la nécessité de parler de spiritualité avec les patients. Cette initiative peut contribuer à améliorer l’enseignement des compétences cliniques dans d’autres professions de santé pour mieux préparer les étudiants à reconnaître les besoins spirituels des patients et à fournir des soins plus holistiques et culturellement adaptés

Case studies on data-rich and data-poor countries

The aim of Work Package 5 is to assess the needs of decision-makers and end-users involved in the process of post-disaster recovery and to provide useful guidance, tools and recommendations for extracting information from the affected area to help with their decisions. This report follows from Deliverables D5.1 “Comparison of outcomes with end-user needs” and D5.2 “Semi-automated data extraction” where the team had set out to explore the needs of decision-makers and suggested protocols for tools to address their information requirements. This report begins with a summary of findings from the scenario planning game and a review of end-user priorities; it will then describe the methods of detecting post-disaster recovery evaluation and monitoring attributes to aid decision making. The proposed methods in the deliverables D2.6 “Supervised/Unsupervised change detection” and D5.2 “Semi-automated data extraction” for use in post-disaster recovery evaluation and monitoring are tested in detail for data-poor and data-rich scenarios. Semi-automated and automated methods of finding the recovery indicators pertaining to early recovery and monitoring are discussed. Step-by-step guidance for an analyst to follow in order to prepare the images and GIS data layers necessary to execute the semi-automated and automated methods are discussed in section 2. The outputs are presented in detail using case studies in section 3. In order to develop and assess the proposed detection methods, images from two case studies, namely Van in Turkey and Muzaffarabad in Pakistan, both recovering from recent earthquakes, have been used to highlight the differences between data-rich and data-poor countries and hence the constraints on outputs on the proposed methods

Error Compensation of Single-Qubit Gates in a Surface Electrode Ion Trap Using Composite Pulses

The fidelity of laser-driven quantum logic operations on trapped ion qubits tend to be lower than microwave-driven logic operations due to the difficulty of stabilizing the driving fields at the ion location. Through stabilization of the driving optical fields and use of composite pulse sequences, we demonstrate high fidelity single-qubit gates for the hyperfine qubit of a $^{171}\text{Yb}^+$ ion trapped in a microfabricated surface electrode ion trap. Gate error is characterized using a randomized benchmarking protocol, and an average error per randomized Clifford group gate of $3.6(3)\times10^{-4}$ is measured. We also report experimental realization of palindromic pulse sequences that scale efficiently in sequence length