Learning from Earthquakes: Building Resilient Communities Through Earthquake Reconnaissance, Response and Recovery

Lead Research Organisation: University of Cambridge
Department Name: Architecture

Abstract

Earthquake reconnaissance plays an invaluable role in earthquake engineering, as it enables the collection of perishable data on building performance that are otherwise unobtainable. Such data can be used to prepare damage statistics, calibrate and validate engineering models and crucially, to decide what design and/or construction deficiencies lead to inadequate structural performance. This research goes beyond the immediate needs of engineers as it can provide the evidence base for the development of new disaster risk reduction policies and mitigation practices worldwide.
In the UK, earthquake field investigations have been conducted by EEFIT since 1982, reporting on the damage observed and inspiring research into building standards for earthquake resistant design and assessment. This research will use the experience gained in EP/I01778X/1 to continue and expand important work in reducing and eventually eradicating the risk of significant death, damage to the economy, and social upheaval resulting from earthquakes. This grant will enable UK based academics to continue to participate in earthquake field investigations conducted by EEFIT and to improve coordination with international equivalents in the USA, Australia and New Zealand, and Europe. grow UK earthquake risk reduction activities, improve the dissemination of EEFIT Mission findings and further increase their impact. Not only will this research continue to collect valuable information in the aftermath of a disaster, but it will also develop new methods of collecting and interpreting this data as well and further develop standard international disaster data collection protocols. This data will be housed in a unique future proof repository that will allow researchers and other stakeholders to easily access and use the information This is important as not only will it enable the UK to stay at the forefront of earthquake engineering research, but it will assist donor countries and other organizations to more accurately access the severity of the disaster and therefore to better target the correct amount of resource for relief and rebuilding efforts.
 
Description Albania earthquake reconnaissance mission findings
? Pre-1990 URM buildings in solid silicate and clay bricks showed a good seismic performance.
? Pre-1990 prefabricated large-panel buildings performed very well in the earthquake
? Damage in RC buildings was observed mainly in mid- to high-rise (above 8 storeys)
? Approximately one third of the collapsed buildings were mixed-use RC MRF buildings built during the 1990s:
? Modern multi-storeys RC MRF multi-family residential buildings in Durres sustained severe non-structural damage.
? ineffective law enforcement in the construction process was a significant contributor to high seismic vulnerability
Zagreb Remote Mission
? In terms of structural performance, the main building type affected was old unreinforced masonry structures with failures of gables, and out of plane failures evident in the City of Zagreb and the surrounding villages.
? For the conducting of remote missions:
o It is feasible to undertake remote earthquake reconnaissance mission with the support of locals trained in the use of the EEFIT app; however the quality of the data is yet to be fully validated.
o The EEFIT app and the SDI were effective for on-site and remote missions. Based on feedback from the mission improvements are ongoing
o Non-specialized social media platforms such as Twitter, Instagram, Facebook and Flickr provides text and image data useful for situation awareness. However, the lack of coordinates on Tweets and the kind of information extracted from the data make it challenging to use for earthquake reconnaissance.
o Damage photos on Social media are mainly restricted to more important and accessible buildings
Aegean Sea mission
? LastQuake app developed by the Euro-Mediterranean Seismological Centre (EMSC) collects text and image georeferenced data useful for earthquake reconnaissance
? To extract information from data collected from social media platforms such as Twitter and Instagram is necessary to use natural language processing (NLP). The usefulness and validity of this data is still to be confirmed.
Exploitation Route The international earthquake engineering and reconnaissance communities will be interested in these outcomes and the potential tools being developed in this project to standardise data collection and storage.
Sectors Communities and Social Services/Policy,Construction,Digital/Communication/Information Technologies (including Software),Education,Environment,Other

 
Description We conducted a feasibility exercise of both the tools being developed under this project and the possibility of carrying out field damage surveys after earthquakes. This was then used in practice by EEFIT in November 2020 after the Aegean Sea earthquake and tsunami.
First Year Of Impact 2020
Sector Other
Impact Types Societal

 
Title EEFIT - Learning from Earthquake pilot questionnaire 
Description A pilot online questionnaire was designed and published by the team's RA Enrica Verrucci to elicit opinions from randomly selected EEFIT members on what is required from a spatial data infrastructure (SDI). The platform is intended to permit better management and sharing of the data collected by EEFIT. The survey asks the responders to evaluate how data is currently being acquired and used before, during and after field missions, and their views on how a framework of geographic data, metadata, and tools can be interactively connected and used to make future earthquake field missions more effective. 
Type Of Material Improvements to research infrastructure 
Year Produced 2018 
Provided To Others? No  
Impact The emails explaining the project and the survey was sent out by Allan Brereton, the EEFIT Secretary/Treasurer and helped advertised the ambitions of the EPSRC-funded project to members of IStructE and EEFIT. The results of this survey will be directly used to develop the SDI, which is central to the project. 
URL http://opinio.ucl.ac.uk/s?s=53298
 
Title EEFIT spatial data infrastructure (SDI) prototype 
Description This spatial data infrastructure is being developed and tested with geospatial data collated from the recent mission to Sulawesi, Indonesia, following the devastating earthquake and tsunami on the 28th September 2018 (https://eefit-indonesia.com). The geospatial data at the very minimum will be a set of coordinates locating a photograph taken from the field. This could and will be complemented by building damage survey data and other survey results in the future. The final product, which is a main deliverable of the project will be used as part of a suite of materials produced by the Learning from Earthquakes project to support the reconaissance teams pre-, during and post-EFFIT missions. Important to note that the revised guidelines have legal implications for EEFIT (e.g., GDPR, data protection officer, data encryption), which is all being carefully reviewed. 
Type Of Material Data handling & control 
Year Produced 2018 
Provided To Others? No  
Impact The SDI will become a standardised way of capturing field reconnaissance data following earthquakes. It will ensure that the data is centrally held by EEFIT post-mission, currently there are no central repositories for digital information collected on site. This will be an invaluable resource, and will help promote consistency in processing and using data by interested stakeholders. 
 
Description LfE Zagreb Earthquake Remote Reconnaissance Mission Field Damage Surveys 
Organisation University of Zagreb
Country Croatia 
Sector Academic/University 
PI Contribution University of Cambridge led the LfE team in conducting a remote reconnaissance mission after the March 2020 Zagreb earthquake.
Collaborator Contribution Professor Josip Atalic and Professor Marta Ĺ avor Novak from the Faculty of Civil Engineering supported master students Helena Majetic and Anamarija Babic in the planning, remote learning and implementation of damage surveys through the LfE damage app in the field from 18/05/2020 - 22/05/2020.
Impact Online blog and report, and joint EEFIT and SECED presentation to an international online audience on the 27th January 2021.
Start Year 2020
 
Title EEFIT Mobile app 
Description The EEFIT Mobile app uses an existing off-the-shelf platform called Device Magic and is built following the tier assessment rationale, which depends on the amount of time the user is allowed to spend on site. The data collected is commensurate to this time and gets hierarchically organised so that there is no repetition, whilst guaranteeing that an increasingly detailed level of information is gathered in each successive tier. 
Type Of Technology Webtool/Application 
Year Produced 2019 
Impact The app has currently been tested during the following EEFIT Missions: the Albania Mission launched after the 26 November 2019 earthquake, the first-ever launched remote mission, after the March 2020 earthquake in Zagreb, Croatia, and the EEFIT Aegean Earthquake & Tsunami Mission. The EEFIT Mobile App Version 2.0 includes data capture relevant to earthquake damage and tsunami damage. The Mobile App liaises closely with the platform defined as spatial data infrastructure (SDI) for data managing and supports the automatic mapping of the data gathered on-site. 
URL https://research.ncl.ac.uk/learningfromearthquakes/outputs/theeefitmobileapp.html
 
Title SDI 
Description An SDI is an infrastructure aimed at supporting the data management (including storage), discovery, access, and easy retrieval and reuse of the geographic data collected and can be designed to support very varied users' needs. Unlike storage devices, the use of metadata (i.e, data about the data) assists in the classification of the data and, in turn, promotes the integration of data coming from disparate sources and thus limiting - if not eliminating - the need for parallel and costly data collection campaigns. The EEFIT Spatial Data Infrastructure is designed with a user's needs-centred approach to accommodate data collected in reconnaissance and recovery missions as well as training. Since missions can occur without internet connectivity, the SDI is designed to work on two complementary systems. The offline local SDI is hosted on a laptop computer which is carried during mission times. It is used to upload all the data that are collected during the mission, so that "no data is left behind" and that perishable information about the data are collated into a centralised place at the time of collection. Once uploaded the data are analysed by ad-hoc scripts so that key metadata can be extracted automatically. For the uploaded photos, the typical metadata include the time of capture, the resolution, information about the collecting device, and geolocation. The metadata and the data volunteered by the data collector at the time of upload are used to build a database of information linked to the collected data and to map the data that have geolocation. The local SDI is supported and augmented by a cloud-based SDI, which enriches the information available in the local SDI by adding a further layer of data richness. This is achieved by integrating the data collected with the EEFIT app and other apps that EEFIT may use to collect data. The EEFIT app de facto replaces the need for paper forms, which were used in the past. The integration of the SDI and the EEFIT app allows the user to collect disaster data at ease and to be guided in this process by the workflows that have been designed in the EEFIT app forms so that the data collected are standardised and can be easily compared. Once uploaded, the "data to maps" process is performed automatically by the SDI. The SDI has 3 components: an Uploader - which consists of a set of easy forms that can be accessed both offline and online to upload data to either the local SDI or the Cloud-based SDI, a Metadata Extractor which analysed the data and populates a database, and a Mapper that uses the data in the database to produce daily maps of what has been observed in the field. When there is no internet connectivity, the users will be able to see the locations that have been visited during daily deployments in the form of a trail of dots. Each of the dots represents the place where the geolocated data have been collected (e.g. geolocated picture of damaged building). If internet connectivity is present, the user will be able to download the data collected with the EEFIT app by accessing the app dashboard online. Once these data are also uploaded, new data attributes will be linked to the collected data. 
Type Of Technology Webtool/Application 
Year Produced 2019 
Impact The EEFIT SDI aims to: - Build institutional memory via collected data - Support multi-disciplinary data analysis and research - making the data more easily accessible to all - Prove the impact of EEFIT Missions in research - Streamline the data management process by using automatic and ad-hoc script that convert the uploaded data into web map 
URL https://research.ncl.ac.uk/learningfromearthquakes/outputs/SDI.jpg
 
Description APP/SDI training 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact 8 people trained in the use of EEFIT app and their connection with the SDI to undertake the building damage survey after the earthquakes in Zagreb and the Aegean region in 2020.
Year(s) Of Engagement Activity 2020
URL https://research.ncl.ac.uk/learningfromearthquakes/outputs/theeefitmobileapp.html
 
Description EEFIT - SECED UK evening talk: Remote earthquake reconnaissance feasibility study: Zagreb earthquake of March 2020 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The evening presentation was a joint EEFIT and SECED lecture which was delivered on 27 January 2021 with the aim of presenting the data collection and repository tools being developed in LfE and the findings of our remote reconnaissance exercise on the Zagreb earthquake in March 2020. A total of 150 people attended the event, and the presentation was followed by a discussion on the current situation in Croatia following the Zagreb and the December 2020 Petrinja earthquake, and the feasibility of hybrid reconnaissance activities in the future. The lecture can be viewed at https://www.ice.org.uk/eventarchive/the-zagreb-earthquake-of-march-2020-webinar.
Year(s) Of Engagement Activity 2021
URL https://www.ice.org.uk/eventarchive/the-zagreb-earthquake-of-march-2020-webinar
 
Description EEFIT Mission Training session 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact The half day workshop was organised jointly by EEFIT and the LFE project team to provide basic training for Team Leaders and Team Members to operate in post disaster field environments; to provide guidance on considerations for organising missions including roles and responsibilities; to provide guidance on Health and Safety procedures and related requirements before, during and after missions; to provide guidance on data collection in the field (where this particular grant fit in); and to provide guidance on expected EEFIT outputs including reporting formats and timelines for output delivery.
Year(s) Of Engagement Activity 2020
URL https://research.ncl.ac.uk/learningfromearthquakes/newsevents/eefitmissiontrainingsession.html
 
Description Zagreb remote mission 2020 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The 2020 Zagreb earthquake occurred on Sunday 22 March 2020. This earthquake was the first that happened during the lockdown imposed by governments to stop spreading the COVID-19. This fact makes the event interesting as a multi-hazard phenomenon. The lockdown made it not possible to deploy an earthquake reconnaissance mission. Therefore, it was necessary to undertake a remote mission supported by the monitoring and analysing social media (SM) platforms, such as Twitter and Instagram. In our work, we first identified the hashtags related to the event. Through the LastQuake app, we obtained the intensity reports from affected people and comments and pictures useful for damage assessment. The team obtained 59,246 tweets posted between the 20th March and the 30th April 2020 and 31,911 comments from LastQuake app users written on the day of the earthquake. Images from posts and comments were used for remote assessment of damage in buildings. Sentiment analysis (SA) was applied to tweets and comments related to the event to assess emergency management during the relief phase after the earthquake. Our work shows that only a limited number of pictures collected through social media were suitable for damage assessment of individual buildings. However, they were still useful as a proxy estimation of damages in some areas of Zagreb and surroundings. We also found SA supported by machine learning a valuable method to assess and identify critical aspects of the emergency and early recovery post-disaster phases. Applying SA we identified the most affected areas, the damages in the non-structural elements in hospitals, the support of collaborative networks for the evacuation of patients and the role of Ministers in the early recovery.
Year(s) Of Engagement Activity 2020
URL https://research.ncl.ac.uk/learningfromearthquakes/newsevents/remotemissionforearthquakeincroatia.ht...