Engaging citizen seismologists worldwide

Most of what we know about Earth's structure, dynamics, hazards, resources and exploration for raw materials comes from seismology. But it is only recently, thanks to cheap computers and the internet, that it has become possible to introduce the subject in schools and include live displays in museums and geoparks for the general public. As the educational value of the subject is becoming more widely appreciated, the need for this international discussion workshop for Educational and Citizen Seismology became apparent (see box “Details of the meeting – and the next ones”). The meeting was a forum for experts in educational and citizen seismology to meet, discuss areas of mutual interest and discover potential synergies and future collaborations (figure 1). It aimed for a balance between talks and discussion or demonstration sessions. There were keynote addresses from those most experienced in developing equipment and running school and citizen seismology programmes, in order to facilitate future collaboration and encourage the growing number of institutions around the globe interested in developing such programmes. There were breakout discussion groups on motivating leaders and maintaining engagement, hardware and software development, data sharing standards and archiving

Landslide Detection in Real-Time Social Media Image Streams

Lack of global data inventories obstructs scientific modeling of and response to landslide hazards which are oftentimes deadly and costly. To remedy this limitation, new approaches suggest solutions based on citizen science that requires active participation. However, as a non-traditional data source, social media has been increasingly used in many disaster response and management studies in recent years. Inspired by this trend, we propose to capitalize on social media data to mine landslide-related information automatically with the help of artificial intelligence (AI) techniques. Specifically, we develop a state-of-the-art computer vision model to detect landslides in social media image streams in real time. To that end, we create a large landslide image dataset labeled by experts and conduct extensive model training experiments. The experimental results indicate that the proposed model can be deployed in an online fashion to support global landslide susceptibility maps and emergency response

Landslide detection in real-time social media image streams

Lack of global data inventories obstructs scientific modeling of and response to landslide hazards which are oftentimes deadly and costly. To remedy this limitation, new approaches suggest solutions based on citizen science that requires active participation. In contrast, as a non-traditional data source, social media has been increasingly used in many disaster response and management studies in recent years. Inspired by this trend, we propose to capitalize on social media data to mine landslide-related information automatically with the help of artificial intelligence techniques. Specifically, we develop a state-of-the-art computer vision model to detect landslides in social media image streams in real-time. To that end, we first create a large landslide image dataset labeled by experts with a data-centric perspective, and then, conduct extensive model training experiments. The experimental results indicate that the proposed model can be deployed in an online fashion to support global landslide susceptibility maps and emergency response

A Real-Time System for Detecting Landslide Reports on Social Media Using Artificial Intelligence

This paper presents an online system that leverages social media data in real time to identify landslide-related information automatically using state-of-the-art artificial intelligence techniques. The designed system can (i) reduce the information overload by eliminating duplicate and irrelevant content, (ii) identify landslide images, (iii) infer geolocation of the images, and (iv) categorize the user type (organization or person) of the account sharing the information. The system was deployed in February 2020 online at https://landslide-aidr.qcri.org/landslide_system.php to monitor live Twitter data stream and has been running continuously since then to provide time-critical information to partners such as British Geological Survey and European Mediterranean Seismological Centre. We trust this system can both contribute to harvesting of global landslide data for further research and support global landslide maps to facilitate emergency response and decision making

Toward a unified near-field intensity map of the 2015 Mw 7.8 Gorkha, Nepal, Earthquake

We develop a unified near-field shaking intensity map for the 25 April 2015 Mw 7.8 Gorkha, Nepal, earthquake by synthesizing intensities derived from macroseismic effects that were determined by independent groups using a variety of approaches. Independent assessments by different groups are generally consistent, with minor differences that are likely due in large part to differences in spatial sampling. Throughout most of the near-field region, European Macroseismic Scale (EMS-98) intensities were generally close to 7 EMS. In the Kathmandu Valley, intensities were somewhat higher (6.5–7.5) along the periphery of the valley and in the adjacent foothills than in the central valley, where they were ≈6. The results are consistent with instrumental intensity values estimated from available data using a published relationship between peak ground acceleration (PGA) and intensity. Using this relationship to convert intensities to PGA, we estimate strong-motion PGA de-amplification factors of ≈0.7 in the central Kathmandu Valley, with amplification of ≈1.6 in adjacent foothills. The results support the conclusion that the Kathmandu Valley experienced a pervasively nonlinear response during the Gorkha main shock

MARSite–MARMARA SUPERSITE: Accomplishments and Outlook

MARsite Project, funded under FP7-ENV.2012 6.4-2 (Grant 308417) and successfully implemented to Marmara Region during 2014-2016 indicated that focusing on the monitoring of the region and the integration of data from land, sea and space and the processing of this composed data based on sound earth-science research is an effective tool for mitigating damage from future earthquakes. This was achieved by monitoring the earthquake hazard through the ground-shaking and forecast maps, short- and long-term earthquake rate forecasting and time-dependent seismic hazard maps to make important risk-mitigation decisions regarding building design, insurance rates, land-use planning, and public-policy issues that need to balance safety and economic and social interests. MARSite has demonstrated the power of the use of different sensors in the assessment of the earthquake hazard. In addition to the more than 30 scientific publication within the MARsite Project framework, a multidisciplinary innovative borehole seismic observatory and a dilatometer have been installed within MARSite where its a data can be used for a range of seismic studies. Due to the encouraging results obtained from this experiment, it was determined that in the future likely smaller number of stations will be required reducing the cost of national seismic networks. The technical infrastructure of the continuous GPS stations of MAGNET network has been updated within MARSite. Tsunami hazard studies in MARSite in Marmara Sea showed that the tsunami hazard in the Marmara Region is primarily due to submarine landslides triggered by an earthquake and a conceptual Tsunami Early Warning System in the Marmara region strongly coupled with the strong ground motion and existing Earthquake Early Warning System was developed. The existing Earthquake Early Warning and Rapid Response system in the Marmara Region was improved and the installation and test of a pilot seismic landslide monitoring system was taken place in the Avcilar-Beylikdüzü Peninsula, a large landslide prone area located in westward part of Istanbul and facing the North Anatolian Fault Zone (NAFZ). An integrated approach based on multi-parameter seafloor observatories was implemented to continuously monitor the micro-seismicity along with the fluid expulsion activity within the submerged fault zone. During MARSite, strong integration and links had been established with major European initiatives focused on the collection of multidisciplinary data, their dissemination, interpretation and fusion to produce consistent theoretical and practical models, the implementation of good practices so as to provide the necessary information to end users, and the updating of seismic hazard and risk evaluations in the Marmara region. In this perspective, to continue the understanding of and improvement in the preparedness for geological disasters, the existing monitoring infrastructure of Marsite requires the continuation of a strong a European initiative. This presentation will provide a venue for information exchange towards the establishment of such an initiative

New directions in seismic hazard assessment through focused earth observation in the MARmara SuperSITE - Project Achievements

The MARsite Project, which started in November 2012,funded by the EC/ FP7-ENV.2012 6.4-2 (Grant 308417) identifies the Marmara region as a ‘Supersite’ within European initiatives to aggregate on-shore, off-shore and space-based observations, comprehensive geophysical monitoring, improved hazard and risk assessments encompassed in an integrated set of activities. MARsite aimed to harmonize geological, geophysical, geodetic and geochemical observations to provide a better view of the post-seismic deformation of the 1999 Izmit earthquake (in addition to the post-seismic signature of previous earthquakes), loading of submarine and inland active fault segments and transient pre-earthquake signals, related to stress loading with different tectonic properties in and around Marmara Sea. This presentation provides an overview of the achievements of MARSite which aimed to coordinate research groups ranging from seismology to gas geochemistry in a comprehensive monitoring activity developed in the Marmara Region based on collection of multidisciplinary data to be shared, interpreted and merged in consistent theoretical and practical models suitable for the implementation of good practices to move the necessary information to the end users in charge of seismic risk management of the region. In addition, processes involved in earthquake generation and the physics of short-term seismic transients, 4D deformations to understand earthquake cycle processes, fluid activity monitoring and seismicity under the sea floor using existing autonomous instrumentation, early warning and development of real-time shake and loss information, real- and quasi-real-time earthquake and tsunami hazard monitoring and earthquake-induced landslide hazard topics are also covered within MARSite. In particular, achievements and progress in the design and building of a multi-parameter borehole system consisting of very wide dynamic range and stable borehole (VBB) broad band seismic sensor, with incorporated 3-D strain meter, tilt meter, and temperature and local hydrostatic pressure measuring devices would be reported. Progress has been marked on photogeological analysis of DInSAR temporal series and of space multispectral/hyperspectral image data, an important geophysical field survey of one of the most important landslide that yielded a refined geological engineering model, numerical dynamic modelling of this and installation of a real-time monitoring system the field. We improved the existing earthquake early warning and strong motion networks and they are mostly integrated. The early warning signals extend to the critical infrastructure’s of Marmara Region like as natural gas distribution line IGDAS and transportation line MARMARAY). The project reached the following goals: intensive monitoring infrastructure have been installed, data sharing among the partners and researchers even the out of the Marsite project have been succesfully realized, more than 70 articles ,reports, presentations have been already issued (or published) and presented by 18 partners institutions

Monitoring Haiti’s Quakes with Raspberry Shake

International audienc