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All Abstracts of Session SE19

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Oral Presentations

SE19 - Accelerating Citizen Geoscience: Intersection Of Social Media, Innovative Technology, Scientific Research, And Outreach
Thursday, August 04, 2016 | 306A (L3N) | 11:00-12:30
1.
SE19-D4-AM2-306A(L3N)-001 (SE19-A004)
 
Lastquake: From Real Time Public Information to Risk Awareness and Risk Reduction
Remy BOSSU#+
European Mediterranean Seismological Centre, France
#Corresponding author: bossu_remy@yahoo.fr +Presenter

Although it is a key element for their efficiency, many citizen science projects as well as risk awareness and risk reduction initiatives fail to engage with the appropriate audience. We will show in this presentation how an engagement strategy initially developed by the Euro-Med Seismological Centre (EMSC) for its rapid public information tools named LastQuake and targeting eyewitnesses of global earthquakes is being extended to contribute to improved risk awareness and reduced seismic risk.

LastQuake (a smartphone app and a quakebot automatically publishing earthquake information on Twitter) aims at optimizing the collection of observations on earthquake effects (felt reports, geo-located pics, comments) for improved situational awareness. Its engagement strategy is based on 3 key elements: LastQuake focuses on felt earthquakes, the only ones that really matter for the public, it provides very rapid information (typically within the first couple of minutes) and a presence on the main social networks ensure it is easily identifiable.

LastQuake proved efficient during the devastating April 2015 Nepal earthquake with 7 000 testimonies collected in 3 weeks for the mainshock and its numerous felt aftershocks as well as 100 geo-located pics. This efficiency was confirmed on many subsequent earthquakes, like the Manipur (India) of January 2016 where for a total 2 000 collected testimonies, more than 800 were shared within 30 minutes of the earthquake occurrence.

Following requests from our users, a new version of the app is being developed where there will be pop-up visual items providing safety advice on actions that should or should not be performed by users who have just been through violent shaking, limiting potential fatal mistakes. A reflexion is being performed to bridge LastQuake with Quake Catcher Network and other awareness initiatives.

2.
SE19-D4-AM2-306A(L3N)-002 (SE19-A001)
 
Toward Constructing Disaster Mitigation Community Sensor Network in Yokohama, Japan
Ahyi KIM1#+, Tatsuya TAKEUCHI2, Hiroki UEMATSU3, Zhe SUN1, Kazuyuki KOIZUMI1, Kahoko TAKAHASHI1, Yuya MATSUMOTO1
1 Yokohama City University, Japan, 2 Yokohama National University, Japan, 3 Senshu University, Japan
#Corresponding author: ahyik@yokohama-cu.ac.jp +Presenter

Since Japan is one of the most seismically active countries in the world, a nationwide dense seismic network has been developed for seismic monitoring. However, the current distribution is not enough to issue the effective earthquake early warning (EEW) within ~30 km of the epicentral area. In addition, although the strong ground motion and the response of a building to shaking is important information for the disaster mitigation, to get the information, even more seismometers is required and the cost will be unrealistic amount of money for the national government disbursements.

To address this issue, we developed a community based MEMS sensor network in the metropolitan area Yokohama, Japan. The project aims to distribute the sensors every several hundreds meters in the area to provide information more closely linked to community’s life. As a first step, we developed a sensor unit which detects strong motion and process the data. The unit is composed of 12 bit MEMS sensor and Raspberry pi. The sensor unit is linked to Twitter and shares the information with the users. The initial installment costs about $100 US dollars, which is much less expensive than the conventional seismometer. However, for the long-term maintenance of the network, support of community is mandatory. From this point of view, it is still too expensive if the immediate benefit is only getting on-site EEW.

To develop more practical and beneficial sensor unit for the community, we hold workshop with them regular basis and share the idea through a discussion. The practical idea is then implemented to the sensor units. Sometimes the idea is not related to seismic monitoring, but is based on the function of accelerometer, such as taking care of elderly person lives alone. In this presentation, we will introduce some from those ideas, implementations, and the operation examples.

3.
SE19-D4-AM2-306A(L3N)-003 (SE19-A006)
 
Development of the Gathering and Analyzing System of Seismic Records with Use of Sensors Inside Mobile Terminals and Cloud Technology
Shohei NAITO#+, Hiroki AZUMA, Ken Xiansheng HAO, Hiroyuki FUJIWARA
National Research Institute for Earth Science and Disaster Prevention, Japan
#Corresponding author: naito@bosai.go.jp +Presenter

There are more than 4,000 strong motion seismometer observation stations in Japan as typified by the K-NET, KiK-net. These seismic observation networks have been maintained for approximately 20 years, and these records have been greatly contributed to developments of the seismology and engineering.

Such densely seismometers covering whole country cannot be seen in any other countries, but it is not enough for recording regional and residential earthquake responses. However, it is difficult to increase these strong-motion seismometers exponentially in terms of costs. So, we have been developing the citizen seismometer network by utilizing MEMS acceleration sensors inside mobile terminals. Only by installing apps, soon after the earthquake occurs, these terminals can record waveform at sampling frequencies of 100Hz, then data are automatically transmitted to the cloud server via internet. Soon after that, users can easily access the distribution map of seismic intensities, and analysis data by only use of a web browser.

By this system, citizens who have no experience of analyzing seismic data can install their own seismometers in their houses and they can compare waves recorded in another buildings from the standpoint of amplitude or predominant frequency.

However, in case for owners of each buildings, these data are sometimes not desirable. So, we have developed the hierarchic structure of accounts and the limitation of access by the authentication.

In the future, we are going to develop the archiving system recorded by multi-sensors including the other type of micro-sensors or video pictures, and also we are going to develop analyzing techniques with a large amount of these data.

Finally, it is important to regard not only with a view of developers but also users to develop these systems as the social implementation. So, it is crucial to cooperate with experimental partner including local governments, companies, and citizens.

4.
SE19-D4-AM2-306A(L3N)-004 (SE19-A008)
 
A Citizen Seismic Network in Taiwan and Its Applications
Wen-Tzong LIANG1#+, Simon C. LIN1, Kate Huihsuan CHEN2, Eric YEN1
1 Academia Sinica, Taiwan, 2 National Taiwan Normal University, Taiwan
#Corresponding author: wtl@earth.sinica.edu.tw +Presenter

To promote the citizen seismology in Taiwan, we have collaborated with the Quake Catcher Network (QCN) project to establish a Pacific Asia QCN server at the Academia Sincia, Taiwan. So far, there are more than 210 volunteers have requested low cost MEMS sensors with -2g to +2g dynamic range to build up citizen strong motion stations by themselves. We then have constructed a data server to host event-based QCN-Taiwan waveforms that are extracted from these volunteer sites in a near real-time manner. All the collected waveforms are further processed to obtain the corresponding peak ground acceleration (PGA) for each site. This QCN-Taiwan PGA's may provide complementary dataset to enhance the spatial resolution of observed shake map for any significant earthqaukes occurring in the Taiwan region. In addition, a web service has been designed to offer volunteers a friendly online interface to interact with their recorded waveforms and the intensity distribution in Taiwan. Meanwhile, we are developing workable teaching plans on earthquake science and earthquake preparedness through a practical operation of this citizen seismic network. The related information can be found at http://qcnasia.org, http://qcntw.earth.sinica.edu.tw and http://katepili2003.wix.com/future-eq-school.

5.
SE19-D4-AM2-306A(L3N)-005 (SE19-A003)
 
Development and Validation of Citizen Seismological Literacy (CSL) in Taiwan
Leon Yufeng WU1#+, Hao CHANG2, Wen-Tzong LIANG3, Kate Huihsuan CHEN1, Chun-Yen CHANG1
1 National Taiwan Normal University, Taiwan, 2 National Taiwan Normal Univeristy, Taiwan, 3 Academia Sinica, Taiwan
#Corresponding author: leonyifengwu@gmail.com +Presenter

“Earthquake School in the Cloud: Citizen Seismologists in Taiwan (CSTaiwan),” which aims to improve citizens’ seismology literacy, is a teaching resources platform that combines disaster prevention education, earthquake science, and volunteer-based statistics. The Department of Earth Science from National Taiwan Normal University initiated such project and hold workshops and studies on the topic of disaster prevention and the science of earthquake. Through these activities, one realized that improving seismology literacy is not limited to passing on the knowledge itself, but should also seeks to understand the factors affecting citizens’ seismology literacy, especially when it concerns the citizens’ general safety. This research proposes “Citizen Seismological Literacy, CSL” and develops literacy questionnaires in order to effectively promote seismology and facilitate the project of volunteer training in the future. The questionnaire was developed base on general earthquake-related knowledge, attitude, and skill by seismology education experts in the first phase, and then was reduced into four dimensions – citizen’s prior knowledge to earthquake science (Prior-Knowledge), citizen’s attitude towards earthquake science (Attitude), earthquake technology techniques (Technology Skills), and willingness of learning (Willingness). These four dimensions were the result drew from the first phase results of the questionnaire, with a sample size of 225 participants (134 elementary teachers, and 91 students), through exploratory and confirmatory factor analyses. The research went on to discover the factors affecting these four dimensions. The second phase studied further on the relationships among the four dimensions of citizen seismological literacy (CSL). The result showed differences in two categories: the level of education (teachers with graduate degree showed better CSL than those with bachelor degree), and the academic major (both teachers and students majored in earth science showed better CSL than those did not). While concerning personality portraits (mini-IPIP), Agreeableness, Conscientiousness, Intellect/Imagination were effective predictors for CSL dimensions (Attitude, Technology Skills, and Willingness) among students, and Agreeableness and Conscientiousness among teachers. By measuring the seismology literacy and the factors affecting it, this study contributes in developing practical educational model for CSTaiwan, and serves as a preliminary study on the topic of seismology literacy for future research.

6.
SE19-D4-AM2-306A(L3N)-006 (SE19-A005)
 
Near-Real Time Earthquake Game Competition in Taiwan
Kate Huihsuan CHEN1#+, Wen-Tzong LIANG2, Leon Yufeng WU1
1 National Taiwan Normal University, Taiwan, 2 Academia Sinica, Taiwan
#Corresponding author: katepili@gmail.com +Presenter

While elevating the quality of earthquake science education by incorporating earthquake/tsunami stories and educational earthquake games into traditional school curricula, the citizen-based earthquake science project in Taiwan is also designed to encourage the citizen to contribute to data collection, analysis, and reporting. We have created a near-real time earthquake games competition to facilitate continuous learning while making earthquake science fun. After 10 minutes of an earthquake event, this competition platform allows citizen seismologists to report earthquake information by processing P- and S-wave arrivals (Finding Earthquakes game), peak ground motion (Measuring Earthquake Shaking and Sizing Up Earthquakes games), and first motion of P-waves (Measuring How a Fault Moves game). Since September in 2014 when the near-real time competition was announced through outreach activities, the QCN volunteers increased by 45 and student volunteers increased by 163. To encourage more users to get familiar with this platform, we open guest accounts upon request. The impact assessment on QCN practice/maintenance, change in knowledge, attitude, and skill in earthquake sciences is investigated in this study.

Poster Presentations

  SE19-D4-PM2-P-007 (SE19-A007)
 
Development of a Real-Time Information System for Earthquake in Japan
Shohei NAITO#+, Hiromitsu NAKAMURA, Ikuo TAKAHASHI, Hiroyuki FUJIWARA
National Research Institute for Earth Science and Disaster Prevention, Japan
#Corresponding author: naito@bosai.go.jp +Presenter

NIED have been developing an advanced seismic information system named J-RISQ (Japan Real-time Information System for earthquake) and which is available for public since October 2013 (http://www.j-risq.bosai.go.jp/report/en/). Once a big earthquake occurs, by use of over 4,000 strong motion seismometers in Japan, J-RISQ immediately estimates the detail distribution of seismic intensities, soon after that, calculates population exposures and building damages of each municipality within several minutes. By utilizing these information effectively, it would be possible for us to mitigate seismic damages.

J-RISQ estimates seismic damages from the basic data such as subsurface amplification factors, population, and building information. A part of these data had accumulated in the public portal for seismic hazard information of Japan named J-SHIS (Japan Seismic Information Station) which have been developed by NIED for over 10 years (http://www.j-shis.bosai.go.jp/en/). The series of the estimation is performed for each 250m square mesh and finally the estimated data is converted into information for each municipality.

Since June 2015, we have made new functional additions to J-RISQ, as stated below.

・It has become possible to focus on the specific areas

・The estimated information can be downloaded as KML

・The estimated information can be updated automatically

・The newest information can be listed by using RSS readers

・Platform for smartphones have been prepared.

In the future, we are planning to develop estimation methods utilizing the continuous strong ground motion data observed by K-NET strong motion seismometers. In addition, we are going to develop high accuracy underground structure model for calculating site amplification factors. Furthermore, we are intend to update the nationwide building model and population model, and then, develop an identification method for seismic damages.

Acknowledgement: This research was partially supported by SIP (Cross-ministerial Strategic Innovation Promotion Program) under the leadership of Cabinet Office, Government of Japan.

  SE19-D4-PM2-P-008 (SE19-A009)
 
Development of the Seismic Signal Detection Method Under Low SNR Condition Using an Artificial Neural Network
Kahoko TAKAHASHI1#+, Yuya MATSUMOTO1, Zhe SUN1, Kazuyuki KOIZUMI1, Tatsuya TAKEUCHI2, Hiroki UEMATSU3, Ahyi KIM1
1 Yokohama City University, Japan, 2 Yokohama National University, Japan, 3 Senshu University, Japan
#Corresponding author: i130385d@yokohama-cu.ac.jp +Presenter

We have developed a community based MEMS sensor network, Citizen Seismic Network (CSN) to obtain the detailed strong motion data which closely linked to community’s life. In this project, we developed a sensor unit which detects strong motion and process the data. The unit is composed of 12 bit MEMS sensor and Raspberry pi. Since we expect the unit is set under the high noise environment (e.g. inside of house), it is important to discriminate between the earthquake signal and the others. However, under the such environment, the conventional method, ratio of short time average and long time average (STA/LTA) which depends on the amplitude of the signal often mislead to pick noise as the signal. To overcome this problem, we developed a method to detect and identify a seismic signal using an artificial neural network (ANN) which utilize a pattern recognition. In the initial test, we used waveform data recorded at our sensor network as the training data to detect the other observed data. The results show successful discrimination. However, at the moment, since we only have five earthquakes detected in our network, the amount of training data is not enough. So as the next step, we use the seismic data obtained at the Yokohama strong motion network and loaded noise obtained by our sensor to the seismic waves. Using the waveforms as training data we will show our synthetic test to check the ability of our ANN detection algorithm under the low SNR condition. 

  SE19-D4-PM2-P-009 (SE19-A011)
 
Exhibition of Disaster Reduction Technology in Museum: Ma-Tsu Temple for Disaster Reduction in National Science and Technology Museum, Kaohsiung, Taiwan
Huang-Kai HUNG#+
National Science and Technology Museum, Taiwan
#Corresponding author: bradhung@mail.nstm.gov.tw +Presenter

Natural hazards, such as earthquakes and floods induced by typhoons, frequently occurred and lost many lives in Taiwan. In order to mitigate these hazards, the technology of the disaster reduction is persistent investigated by the associate government agencies in around three decades. For the purpose of popularizing these studies to the general public, National Science and Technology Museum cooperates with several national research institutes, such as Ministry of Science and Technology, National Science and Technology Center for Disaster Reduction, and National Center for Research on Earthquake Engineering, trying to introduce the technology for disaster reduction using the exhibition in museum. We use the feature of the traditional religion building, Ma-Tsu Temple, to establish the main imagery for this exhibition. Specific gods in Ma-Tsu Temple represent various technology of the disaster reduction, including the satellite image recognition, earthquake warning system, automatic monitoring of urban flooding, landslide warning system, and rapid establishing light-weight bridge. In future, the exhibition will be updated by interactive model and moveable style for the purpose of more attractive and widespread.