Information Technology for Reducing Earthquake Impacts on Phuket Tourism

Transcription

1 Information Technology for Reducing Earthquake Impacts on Phuket Tourism Apichat Heednacram 1, Noppon Lertchuwongsa 2 Department of Computer Engineering, Faculty of Engineering, Prince of Songkla University (Phuket Campus) Kathu, Phuket, 83120, Thailand 1 apichat@coe.phuket.psu.ac.th 2 noppon@coe.phuket.psu.ac.th Abstract This article reviews recent earthquakes in Phuket region and the impacts they have had on the hospitality and tourism industry as well as suggesting how to apply information technology that can reduce the earthquake impacts in the future. This is because we believe the incident like earthquake is one of the major obstacles for sustainable development of tourism industry in Phuket province. We assess how information technology can help in three main steps; before earthquake, during earthquake, and after earthquake. Our reviews and recommendation are given in each of these steps. Keywords: Earthquake, Information Technology, Phuket, Tourism 1. Introduction Statistics of earthquakes in the past and the results measured by seismic stations show that Thailand is the country that is not completely safe from earthquakes. Earthquakes in Thailand often occur in North, West and South. The felt earthquakes often occur from two sources. The first source comes from active faults inside the country and the other source is a result of outside country s seismic activities. The earthquake that occurs from outside Thailand comes from subduction zone along Sumatra, Andaman Sea, Myanmar, south of China, Laos and Vietnam (Wechbunthung, 2008). For example, the major earthquake of this kind which seriously affected Phuket was the 2004 Indian Ocean earthquake. This was an undersea 9.3 Richter scale earthquake that occurred on Sunday, 26 December 2004, with an epicentre off the west coast of Sumatra. The CNN reported 5,395 deaths, 2,993 missing, in Thailand during the boxing-day tsunami (CNN, 2005). For Phuket only, the Department of Disaster Prevention and Mitigation reported 262 deaths, 1,111 injuries, and 620 missing. During the tsunami, the popular tourist resort of Phuket was extensively damaged. The tourism and economic impact on Phuket was considerable. Thousands of Thais dependent on tourism-related industries have lost their jobs. The confidence of overseas tourists in travelling to places such as Phuket also took some time to recover. The earthquake inside the country comes from active fault zones in Thailand. In 2012, there are 29 earthquakes with epicentre in Thalang, Phuket. These events began on 16 April 2012 with a 4.3 magnitude earthquake that occurred at 4.44 PM (local time), following by another 28 earthquakes with a magnitude of during 16 April till 5 May Information technology has played an important role during the earthquake, saving lives and properties. Social network, for example, is a major tool in disaster response in times of calamities as in the Haiti earthquake in 2010 and the tsunami that struck Japan in Should computer scientists take more responsibility to help reduce the loss of life and major impacts from natural disasters such as earthquake? In this paper, we will study the use of information and technology in the preparation, response and recovery phases of earthquakes. Information and technology assessment that we will consider in this paper is outlined below.

2 A: Before Earthquake Information and knowledge for a better understanding of earthquake. Survival procedure and how to react in the midst of chaos as well as evacuation plan and the rehearsal of the plan. Early Warning system. Prediction system. Resource management such as hospital beds, police force, rescue team, food and shelters. News and social networks. Expanding more research in all multidisciplinary such as data mining, algorithms, resource management system, decision support system, relation to animal behaviors, relation to electromagnetic waves, and so on. B: During Earthquake News and social networks. Application of decision support system. Application of disaster management software. Warning system during earthquake. Web tools. C: After Earthquake Damage inspection techniques. Donation management system. Database of patients, victims, damages. News and social networks update. The paper is organized as follows. First, we describe technical background necessary for understanding the concepts of this paper. Then, we review and recommend the information technology that can be used to reduce earthquake impacts in three main steps; before earthquake, during earthquake, and after earthquake. Finally, we summarize and conclude with open research problems. 2. Technical Background The seismotectonic setting of Southeast Asia is based on the interaction between the Indo-Australian, Eurasian, Philippine and West Pacific plates. Thailand is situated within the Eurasian plate and is bounded by the Andaman thrust in the west, Sunda arc in the south and Philippine trench in the east (Fenton et al., 2003) as shown in Figure 1. Figure 1. Tectonic Elements in Andaman Region (Fenton et al., 2003) Different magnitude scales are used to define the earthquake magnitude. For example, the surface-wave magnitude (M s ) and the compressional body wave (P-wave) magnitude (mb) are commonly used in USGS, ISC, while the local magnitude (M L ) or "Richter" is reported by TMD. Other scales that have been used are the moment magnitude (M w ), the energy magnitude (M e ), the body wave magnitude using the Lg wave (mblg). Formulas for all these different magnitude scales are given below. Details of each formula (NEIC, 2012) will not be discussed here. M w = (2/ 3)log Mo Me = (2/ 3)log ES 2. 9 M S = log( A/T ) + 166log. D mb = log( A/T ) + Q(D, h) mblg = log D + log( A/T ) for 0. 5 D 4 mblg = log. D + log( A/T ) for 4 D 30 M L = log A log Ao

3 The earthquake intensity is not the same with magnitude. The intensity measures the effect of an earthquake on the Earth's surface such as people awakening, movement of furniture, total destruction. The currently used intensity scale in the US is the Modified Mercalli (MM), the intensity which refers to the effects actually experienced at that place. This scale is composed of 12 increasing levels of intensity that range from not felt except by a very few people to catastrophic destruction. The seismic hazard map of Thailand is shown in Figure 2. Phuket and most of the west-southern part of Thailand is in Zone 2A. This means that, the intensity is of V VII and the earthquake is felt by nearly everyone with a possible unstable object overturned. From their investigation, there are 15 active faults in Thailand as shown in Figure 3. These active faults are Mae Chan, Mae Ing, Pua, Mae Hong Son, Mae Tha, Phayao, Mae Yom, Thoen, Uttaradit, Tha Khaek, Moei, Si Sawat, Three Pagoda, Ranong and Klong Marui. In the Southern part of Thailand there are two active faults which could affect Phuket area; these are Ranong and Klong Marui fauls. 1) Ranong: The fault is one of the northeast to north-northeast-trending faults that traverse the Peninsular Thailand. The total fault length is about 220 km. The fault follows the channel of the Kraburi River and has its subsidiary faults cutting from 135 million to 63 million years ago (Charusiri, 1989). Figure 2. Seismic Hazard Map of Thailand by DMR as of January 2005 Department of Mineral Resource (DMR) is carrying out researches of inland earthquake source and tectonic movement. Figure 3. A map of 15 active faults in Thailand by DMR as of October 2006

4 A few hot springs was found near and along the southern end of the fault, implying that the fault significantly provides conduits for the geothermal field. Shrestha (1990) noted that an earthquake of Mb 5.6 happened along this fault during 30 September The most recent earthquake in this zone is on 4 June PM (local time) with an epicenter in Amphur Muang, Ranong having a magnitude of 4.0 (Seismological Bureau, 2012). 2) Khlong Marui: The fault is 130 km-long which cuts across the Phang Nga Bay and Ban Don Bay, follows the Klong Marui channel and the fault may have occurred from 63 million to 2 million years ago (Charusiri, 1989). Figure 4. Centre of 4.3 Earthquake in Phuket produced by DMR as of April 2012 Hot springs are mostly concentrated at the southern portion of the fault while the northern part of Khlong Marui fault is related to opening of the Gulf of Thailand and is therefore a basin-bounding normal fault rather than a major strike-slip fault. The recent major earthquake in this zone is on 16 April PM (local time) with an epicenter in Amphur Thalang, Phuket, having a magnitude of 4.3. The authors of this paper witnessed the building vibration and the sensation like heavy truck striking building. The earthquake originating from Klong Marui fault affected Tumbon Srisuntorn and Tumbon Thepkrasuttri where there were some damages to buildings. The intensity was V VII with the depth of 22 km. After this incident there were another 28 earthquakes with a magnitude of 1.9 to 3.3 during 16 April till 5 May 2012 as shown in Table 1. The Thai Meteorological Department (TMD) reported that all of these earthquakes occurred in Amphur Thalang region, Phuket. Table 1. Earthquakes in Thalang, Phuket since 16 April 2012 recorded by TMD (2012) No Origin Time (UTC) Mag Latitude Longitude 1 16-Apr-12 9: Apr-12 13: Apr-12 14: Apr-12 16: Apr-12 16: Apr-12 16: Apr-12 18: Apr-12 19: Apr-12 1: Apr-12 5: Apr-12 14: Apr-12 17: Apr-12 21: Apr-12 21: Apr-12 12: Apr-12 12: Apr-12 13: Apr-12 1: Apr-12 10: Apr-12 14: Apr-12 19: Apr-12 2: Apr-12 6: Apr-12 8: Apr-12 8: Apr-12 21: Apr-12 1: May-12 21: May-12 23: The earthquakes with the magnitude greater than 3 were felt quite noticeably by persons indoors, especially on upper floors of buildings. Many people do not recognize the earthquakes in Table 1 as the earthquakes. The earthquakes with smaller magnitude were felt only by a few persons at rest.

5 3. Information Technology Assessment In this section, we review how the information technology can be used to reduce the earthquake impacts in three main steps. In each step, we also provide recommendations on what more could be done to widen the information technology usage. 3.1 Before Earthquake Some of the useful tools involved in the above step are given in Table 2. Table 2. Information Technology Assessment Before Earthquake Topics 1. Information & Knowledge of Earthquake 2. Survival and Evacuation Plan 3. Early Warning System 4. Prediction System 5. Resources Management 6. News and Social Networks 7. Expanding Research Example Tools JMA (2007) Yamasaki (2012) TMD, DMR, USGS, EMSC, Geofon JMA (2007) TMD JMA (2007) Yamasaki (2012) Lee et al. (2003) Allen et al. (2009) TMD Alvan and Azad (2011) Zhi-Ma et al. (2010) Karatay et al. (2009) Preethi and Santhi (2011) USGS Yao et al. (2006) Yao et al. (2006) TMD Facebook Alvan and Azad (2011) Zhi-Ma et al. (2010) Karatay et al. (2009) Preethi and Santhi (2011) USGS The Japan Meteorological Agency (JMA, 2007) published the bulletin for their people to understand the warning system and how to protect themselves when strong tremors arrive. Japan s Earthquake Early Warning System (EEWS) is split into two phases: earthquake detection and warning system. For earthquake detection, the ground movement data is collected using Japan s dense seismic network to analyze when and where an earthquake has occurred to effectively issue an earthquake warning. Two types of seismic waves emitted by earthquakes are P-waves and S-waves. P- waves are less hazard and move faster than S- waves (Yamasaki, 2012), thus it can be used to detect the onset of an earthquake before the arrival of the more destructive S-waves, hence an idea for EEWS. The Japan EEWS is useful for regions that are located at least 100km from the earthquake s epicenter. This distance translates into an approximately second warning (Yamasaki, 2012). This information leads to the development of survival guidelines (JMA, 2007) because even a 30 second warning prior to an earthquake can allow a driver to pull over to the side of the road or a student to huddle under a desk before the earthquake s ground-shaking rupture, the bullet trains automatically halt in the seconds before the ground began to shake. Similar guidelines are made available in Thailand by TMD (Wechbunthung, 2008). For example, if a person is in the building, the suggestion is, do not rush outside and protect the head and shelter under a table. If a person is in the elevator, stop elevator and get off immediately. If a person is outside the building, be careful of falling signs and broken glass. Moreover, TMD has made the earthquake information available for the public awareness via SMS messages, crawling text on TV. Additional sources for information and news that are commonly known in the field both local and overseas are: 1. USGS qsww/quakes/quakes_all.php 2. EMSC 3. Geofon

6 4. TMD (Thailand) 5. DMR (Thailand) 6. Other sources: NEIC, ISC, IRIS, GSN, CEA, ASL, MMS, REDPUMA, PTWC, JMA. Lee et al. (2003) and Allen et al. (2009) emphasized on the global network warning system, for Mexico, Japan, and Taiwan s earthquake early warning systems. Earthquake signal of seismic sensors are conveyed to the central station and analyzed results is obtained in real-time (within 1-10 seconds). They also mentioned that the effective use of the system requires activation of automated systems, slowing down rapid transit vehicle, and shutting down hazard pipe lines. For Thailand, the warning system begins with the seismic monitoring system which consists of Seismic Station Phase I of 15 stations, Seismic Station Phase II of 25 stations, Accelerograph Station of 22 stations, Tide Gauge of 9 stations and GPS of 5 stations (Seismological Bureau, 2012). In the region around Phuket, three seismic stations were installed (see Figure 5, Figure 6 and Figure 7). Bangwad Dam is the seismic station located near Prince of Songkla University, Phuket. Figure 6. Seismic Station at Ranong (Seismological Bureau, 2012) Figure 7. Seismic Station at Bangwaad Dam, Phuket (Seismological Bureau, 2012) In case of the undersea earthquake, several tsunami warning towers were installed, for example, the warning tower on Patong beach in Figure 8. Figure 5. Seismic Station at Bang-Kamprud Reservoir, Krabi (Seismological Bureau, 2012) Figure 8. Warning Tower on Patong Beach, Phuket (Seismological Bureau, 2012) Yao et al. (2006) suggested the technology to manage news, warning system and resources called WebGIS in which the distribution nature of earthquake information can be effectively shared for coordinated works. GIS technology is integrated with web technology to form the WebGIS for organizing, utilizing and sharing earthquake information, which overcomes the limitation of the traditional GIS system that is built in a single computer environment. The pre-earthquake deformation is also the

7 interesting topic for researchers whose aim is to forecast before the real shake is happened. Several phenomenons are considered, for example, ionospheric perturbations; formation of clouds; electromagnetic fluctuations; changing water levels in deep wells; surfacetemperature changes due to the heat, water vapor, and gas. Alvan and Azad (2011) noted various electromagnetic signals being detected prior to large earthquakes. They also observed several interesting precursor data such as the surface temperature changes due to the heat, water vapor, gas prior to earthquakes; the formation of clouds, attributed to the heat generated under the earth s before releasing the main energy; the changing water levels in deep wells due to seismic waves induced large water level fluctuations in wells and the movement of the rock near the surface. Zhi-Ma et al. (2010) mainly studied on Ne (electron density), and Te (electron temperature), their results concerned the variations of electron density and electron temperature associated with strong earthquakes. The DEMETER satellite is also used to study ionospheric perturbations in relation with the seismic activity, volcanoes and human activity, to detect the electromagnetic environment of global scale. Karatay et al. (2009) argued that the ionosphere can be characterized with Total Electron Content (TEC), electron density distribution in a complex function of spatial and temporal variations, geomagnetic, solar and seismic activity. The promising results are obtained from the analysis of Kullback-Leibler divergence between the an average quiet day TEC estimate (AQDT) and the TEC estimates for the before a strong earthquake (BE). The seismic activity before the strong earthquakes has a diurnal disturbance structure which can be distinguished from the ionospheric disturbances due to geomagnetic storms or solar flares. Preethi and Santhi (2011) used the historical sequences of data along with signal analyzing tool to predict the earth quake events in the future similar to the techniques used in financial forecast. The historical data are collected, and then preprocessed using the data mining and finally the fuzzy logic rules are applied to predict the impact of earthquake. In addition, USGS uses the GPS technology to monitor the deformation of Earth's surface by assuming that over the time period, the accumulate strain and slip or slowly creep in earth s faults caused the deformation of earth s surface. The GPS is used to measure precisely these positions of stations near active faults relative to each other. Months or years later, they calculate ground deformation by determining how the stations have moved. We recommend expanding some of the above research and adapt to Phuket case especially the more study on electromagnetic relation to the earthquake, ionospheric perturbations, and an analysis of AQDT and BE cases as the precursors. This is because all of this research is relatively new in Thailand. Using GPS technology is also an interesting tool to tract down the movement of fault plate, since there is a fault line passing by Phuket s island according to the active fault map by TMD. Also, the TMD should make a national database of the earthquake available for research and update it frequently and accurately. For this reason, more seismic stations should be installed in the South and also across the country. A local action plan for responding to the crisis on the earthquake should be published on the internet, web site and social network. At present, people are not aware of any evacuation plan. In past earthquakes, the evacuate routes were jammed. We recommend to separate the evacuate route and the route for rescue teams or the route that help needs to go into the disaster zone. The rehearsal exercise of the people in the earthquake situation is crucial. It should be done at least once a year. All information given to the public cannot be just in Thai because Phuket is a city with many nationalities. 3.2 During Earthquake Some of the useful tools involved in the above step are given in Table 3. During earthquake, news and information network are vital for the connection of the public with-in the disaster area and from/to outside.

8 Table 3. Information Technology Assessment During Earthquake Topics 1. News and Social Networks 2. Decision Support System 3. Disaster Management Software 4. Warning System Example Tools Shibata et al. (2012) SNS, Blog Tang and Zhao (2012) Hosokawa et al. (2009) Chen et al. (2009) Mardiyono et al. (2012) Mardiyono et al. (2012) Yamasaki (2012) Lee et al. (2003) Allen et al. (2009) 5. Web Tools Shibata et al. (2012) Yao et al. (2006) Google Public Alert, Google Person Finder, Google Map Shibata et al. (2012) studied the reliable of information network systems in Japan earthquake, and discussed their robustness and throughput. They claimed that the robustness of information network is the most importance factor because available area of cellar phone had been halt during earthquake. Satellite phone system was fully used where each local city government possessed about two phones. Satellite IP system (IPSTAR) quickly helped recovering internet communication in many disaster areas. The routers consisted of 3G and wireless networks (IEEE b/g/n) were used for many city halls and evacuation shelters. The use of social networking sites (SNS) like Facebook, LinkedIn, MySpace, and Twitter become practical for real-time information sharing such as gas station, transportation, foods, and ATM. WebGIS is another tool to manage news, warning system and resources (Yao et al., 2006) where earthquake information can be effectively shared. Decision supporting system is a powerful tool in aided decision-making for earthquake response (Tang and Zhao, 2012). Their tool equips with the following functions; earthquake hazard analysis, sand liquefaction, assessment group building earthquake damage, assessment of lifeline system, seismic economic losses assessment, and assessment of life losses. For supporting rescue operations, Hosokawa et al. (2009) were able to obtain damage detection maps that correspond with the severely damaged area. Their method is based on a combination of earthquake damage estimation using change detection and earthquake information (magnitude, location of source, ground conditions, and distance attenuation equation) by the means of remote sensing data. Chen et al. (2009) claimed that earthquake response spectra, a tool for analyzing the performance of structures and equipment in earthquakes, can be accurately designed by involving artificial neural network model (ANN) in parameters of the seismic environment, rock and site condition. Mardiyono et al. (2012) proposed an intelligent monitoring system utilizing ANN to predict the building damage index. The system also provides an alert and notification to inform the status of the damage, thus it is useful for evacuation of public from hazard area, and planning of the rescue teams. The warning systems of Yamasaki (2012), Lee et al. (2003) and Allen et al. (2009) are also applicable during earthquake. Google crisis response provides an online technology to quickly reach people in need and to efficiently run internal operations during a crisis. Some of the Google tools are Google Public Alert, Google Person Finder, Google Maps and Google Earth. The satellite network has higher robustness than local line network; we recommend its use during the disaster. In Thailand, NECTEC has implemented Emergency and Education Vehicle (EECV) which is fully equipped with satellite communication. Currently, there are two vehicles like this in operation (Charnsripinyo, 2012). Moreover, we recommend the practical use of internet application, such as, Facebook, Twitter, and Blog for sharing information. The social network is increasingly useful for instant reporting of health issues and current situations during the calamities.

9 3.3 After Earthquake Some of the useful tools involved in the above step are given in Table 4. Table 4. Information Technology Assessment After Earthquake Topics Example Tools 1. Damage Hosokawa et al. Inspection (2009) Chen et al. (2009) Mardiyono et al. (2012) 2. Donation System Web Forums Phones 3. Resource Yao et al. (2006) Management PPPHO (2012) 4. News and Social Shibata et al. (2012) Networks Yao et al. (2006) After earthquake, the majority task is to deal with the damage affect, life loss, and the reconstruction. The map and the damage evaluation of Hosokawa et al. (2009), Chen et al. (2009) and Mardiyono et al. (2012) can be served in this step as well. There are several overlapping tools from previous section that can be applied after the earthquake. Similarly, the web sites and popular social networks allow the public to access the up to date information from the data center. We believe there are more items which could be done to widen the information technology usage for finding and rescue operations; even in the preparation of equipment, medical aid, food, water and clothing; or the creation of temporary shelters. In particular, Phuket Provincial Public Health Office (2012) has adopted the use of information technology to develop software system for resource management during disasters in Phuket. 4. Conclusion We reviewed and suggested the information technology for reducing earthquake impacts in three main steps. The need to recognize natural disaster impacts on Phuket tourism can save lives, properties, local business and economy. This requires further extensively study in the research areas mentioned in the paper and the areas not mentioned but are interesting such as Catastrophe modelling, Disaster Informatics and Unified Victim Identification System (UVIS). Specifically, disaster Informatics is the study of the use of information and technology in the preparation, mitigation, response and recovery phases of disasters and other emergencies. It began to emerge as a new field recently. The UVIS is an Internet-enabled database system developed for the medical examiner. We encourage these topics as open research problems. 5. References Allen, R.M., Gasparini, P., Kamigaichi, O. and Böse, M. (2009). The status of earthquake early warning around the world: an introductory overview. Seism. Res. Lett. 80(5), Alvan, H.V. and Azad, F.H. (2011). Satellite remote sensing in earthquake prediction. A review. In National Postgraduate Conference (NPC), 1-5. Charnsripinyo, C. (2012). In Workshop on Internet Architecture 2012, Department of Computer Engineering, Prince of Songkla University, Phuket October, Charusiri, P. (1989). Lithophile Metallogenic Epochs of Thailand: A Geological and Geochronological Investigation. Ph.D. thesis, Queen s University, Kingston, Ontario, Canada. Chen, Y., Liu, T., Liu, W. (2009). Predictive Model of Artificial Neural Network for Earthquake Influence Analysis. In International Forum on Information Technology and Application (IFITA). Chengdu, China. 1: CNN. (2005). Tsunami death toll on Tuesday, February 22, Retrieved from cf/12/28/tsunami.deaths/index.html Department of Mineral Resource, Thailand. (2012). Earthquake Thai. Retrieved from arthquake_thai

10 EMSC. (2012). Worldwide Earthquake with M4.0+. Retrieved from Fenton, C., Charusiri, P. and Wood, S. (2003). Recent Paleoseismic Investigations in Northern and Western Thailand. Annuals of Geophysics. 46, 5: Geofon. (2012). Recent Earthquake. Retrieved from Hosokawa, M., Jeong, B., Takizawa, O. (2009). Earthquake Intensity Estimation and Damage Detection using Remote Sensing Data for Global Rescue Operations. IGARSS (2) Japan Meteorological Agency Ministry of Land, Infrastructure and Transport. (2007). Earthquake Early Warning. Retrieved from Karatay, S., Arıkan, F., Arıkan, O. (2009). Investigation of Hourly and Daily Patterns for Lithosphere-Ionosphere Coupling Before Strong Earthquakes. In Proceedings of RAST, Recent Advances in Space Research, İstanbul, Türkiye, Lee, W.H.K., and Espinosa-Aranda, J.M. (2003). Earthquake early warning systems: Current status and perspectives. In Early Warning Systems for Natural Disaster Reduction, Springer, Berlin. Mardiyono, Suryanita, R., Adnan, A. (2012). Intelligent Monitoring System on Prediction of Building Damage Index using Neural-Network. TELKOMNIKA, 10(1), NEIC. (2012). Earthquake Center: Magnitude and Intensity. Retrieved from ormulas.html Phuket Provincial Public Health Office. (2012). Personal Communication. Poolcharuansin, K. (2009). Updating Framework for Site-Specific Attenuation Relation of Seismic Ground Motion in Thailand. Master s thesis. National Graduate Institute for Policy Studies & Building Research Institute. Japan. Preethi, G., Santhi, B. (2011). Study on Techniques of Earthquake Prediction. International Journal of Computer Applications, 29(4), Seismological Bureau, Thai Meteorological Department. (2012). Local Earthquake and Seismic Monitoring System. Retrieved from hp Shibata, Y., Uchida, N., Ohhashi, Y. (2012). Problem Analysis and Solutions of Information Network Systems on East Japan Great Earthquake. AINA Workshops, Shrestha, P.M. (1987). Investigation of Active Faults in Kanchanaburi Province, Thailand. Master s thesis, Asian Institute of Technology, Bangkok, Thailand Tang, A., Zhao, D.A. (2012). A Decision Supporting System for Earthquake Disaster Mitigation, In the 2nd International Conference on Intelligent System Design and Engineering Application, United States Geological Survey. (2012). Latest Earthquakes in the World. Retrieved from nteqsww/quakes/quakes_all.php Wechbunthung, B. (2008). Fundamental Seismology, Seismological Bureau. Thai Meteorological Department. Yamasaki, E. (2012). What We Can Learn From Japan's Early Earthquake Warning System. Momentum. 1(1), Yao, B., Shi W. and Tong, X. (2006). A WebGIS Based General Framework of Information Management and Aided Decision Making System for Earthquake Disaster Reduction. IGARSS Zhi-Ma, Z.R., Zhang, X.M., Shen, X.H., Jing, L., Pan, X., Kang, C.L. (2010). Ionospheric disturbances associated with Tonga Mw7.9 earthquake - Results from Langmuir Probe Instrument onboard DEMETER satellite. IGARSS