NH23A:
Model, Tools, Techniques, and New Data Streams for Natural Hazards and Emergencies II Posters

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You can still search the program to see your colleague�s abstract submissions as well as the sessions submitted for the 2016 Fall Meeting. The final program will be released in early October.


Session ID#: 14783

Session Description:
In recent years, advances in science have enabled new capabilities to acquire near-real time Earth data from space-borne, air-borne and ground based measurements.  Easy access to novel information streams, including social media,  is redefining situation awareness. These streams are diverse, complex and overwhelming in volume, velocity and in the variety of viewpoints they offer.  These multi-sourced data can support assessment, humanitarian assistance and disaster relief operations in ways not previously possible.

Negotiating these overwhelming streams is beyond the capacity of human analysts.Novel research and approaches are necessary to explore new capabilities and challenges to utilize these streams in new, groundbreaking ways, and to leverage, fuse and filter these new data.  This session is organized to explore the opportunities, challenges, solutions and applications of leveraging and synthesizing the multi-sourced data, computing technologies and tools to support the analysis, and to assist in response during various disaster phases (mitigation, preparedness, response, and recovery).
Primary Convener:  Guido Cervone, Pennsylvania State University Main Campus, Department of Geography and Institute for Computational and Data Sciences, University Park, PA, United States
Conveners:  Phu Nguyen, University of California Irvine, Irvine, CA, United States, Qunying Huang, Department of Geography, University of Wisconsin Madison, Geography, Madison, United States and Andrea R Thorstensen, NOAA Boulder, Boulder, CO, United States
Chairs:  Guido Cervone, Pennsylvania State University Main Campus, Department of Geography and Institute for Computational and Data Sciences, University Park, PA, United States, Phu Nguyen, University of California Irvine, Irvine, CA, United States, Andrea R Thorstensen, NOAA Boulder, Boulder, CO, United States and Qunying Huang, Department of Geography, University of Wisconsin Madison, Geography, Madison, United States
OSPA Liaison:  Phu Nguyen, University of California Irvine, Irvine, CA, United States
Index Terms:

4301 Atmospheric [NATURAL HAZARDS]
4302 Geological [NATURAL HAZARDS]
4303 Hydrological [NATURAL HAZARDS]
4333 Disaster risk analysis and assessment [NATURAL HAZARDS]

Abstracts Submitted to this Session:

Introduction of the Mobile Platform for the Meteorological Observations in Seoul Metropolitan City of Korea (155473)
Ki-tae Baek1, Sanghee Lee2, Minsoo Kang1 and Gangwoong Lee1, (1)Hankuk University of Foreign Studies, Yongin, Korea, Republic of (South), (2)Yonsei University, Seoul, Korea, Republic of (South)
Ecological Methods Reveal New Microfossil Signals of Cyclone Activity in a Tropical Reef Setting (149819)
Luke C Strotz, University of Kansas, Lawrence, KS, United States, Briony L Mamo, Macquarie University, Sydney, Australia and Dale Dominey-Howes, The University of Sydney, School of Geosciences, Sydney, Australia
Study on Earthquake Emergency Evacuation Drill Trainer Development (155583)
Lu ChangJiang, Organization Not Listed, Washington, DC, United States
An Enhanced Text-Mining Framework for Extracting Disaster Relevant Data through Social Media and Remote Sensing Data Fusion (141334)
Christopher Jeffrey Scheele, University of Wisconsin, Madison, Department of Geography, Madison, WI, United States and Qunying Huang, University of Wisconsin, Madison, Department of Geography, Madison, United States
Study of flash floods over some parts of Brazil using precipitation index (190311)
Diego Souza, Rafael Le Masson de Souza and Rayana Araujo, National Center for Monitoring and Early Warning of Natural Disasters - CEMADEN, São José dos Campos, Brazil
Detection of Flood Inundation Information of the Kinu River Flooding in 2015 by Social Media (170355)
Yongxue Shi1, Takahiro Sayama1 and Kaoru Treasure Takara2, (1)Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan, (2)Kyoto University, Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto, Japan
Machine Learning Predictions of Flash Floods (188402)
Robert Allan Clark III1,2, Zac Flamig1,3, Jonathan J Gourley4 and Yang Hong5, (1)University of Oklahoma Norman Campus, Cooperative Institute for Mesoscale Meteorological Studies, Norman, OK, United States, (2)NOAA Norman, Storm Prediction Center, Norman, OK, United States, (3)University of Chicago, Center for Data Intensive Science, Chicago, IL, United States, (4)National Severe Storms Lab, Oklahoma City, United States, (5)University of Oklahoma Norman Campus, Norman, OK, United States
Hybrid approach using TOPLATS and regression model for forecasting flash flood in mountainous area (169825)
Byong Ju Lee and Seongsim Yoon, Hankuk University of Foreign Studies, WISE Institute, Yongin, Korea, Republic of (South)
From Rainfall Nowcasting to Flash Flood Early Warning Systems: recent and ongoing advancements in Europe  (179144)
Daniel Sempere-Torres, Marc Berenguer and Shinju Park, Universitat Politecnica de Catalunya, Centre de Recerca Aplicada en Hidrometeorologia, Barcelona, Spain
Fleeing to Fault Zones: Incorporating Syrian Refugees into Earthquake Risk Analysis along the East Anatolian and Dead Sea Rift Fault Zones (131476)
Bradley Wilson and Thomas R Paradise, University of Arkansas, Fayetteville, AR, United States
Reconstruction of the 2015 Atacama Floods: Influence of Legacy Mining Deposits in the Salado River Mouth (166914)
María José Fuenzalida Callejas, Pontifical Catholic University of Chile, Santiago, Chile, Mari­a Teresa Contreras Vargas, University of Notre Dame, Department of Civil & Environmental Engineering & Earth Sciences, Notre Dame, IN, United States and Cristian R Escauriaza, Pontifical Catholic University of Chile, Hydraulic and Environmental Engineering, Santiago, Chile
Assessment of “TIMELINE” for river floods in Japan based on geographical and societal backgrounds: Case studies in Japan and the United States (198295)
Seiya Maruyama1,2 and Shinjiro Kanae2, (1)Tokyo Institute of Technology, Tokyo, Japan, (2)Tokyo Institute of Technology, Department of Civil and Environmental Engineering, Tokyo, Japan
Building the ensemble flood prediction system by using numerical weather prediction data: Case study in Kinu river basin, Japan (194921)
Yuta Ishitsuka, University of Massachusetts Amherst, Civil & Environmental Engineering, Amherst, MA, United States and Kei Yoshimura, The University of Tokyo, Institute of Industrial Science, Tokyo, Japan
Building Inventory Database on the Urban Scale Using GIS for Earthquake Risk Assessment (188571)
Onur Kaplan1, Ugur Avdan2, Yucel Guney1,2 and Cuneyd Helvaci3, (1)Anadolu University, Eskisehir, Turkey, (2)Anadolu University, Earth and Space sciences institute, Eskisehir, Turkey, (3)Geobilgi Company, Istanbul, Turkey
Application of Radar-Based Accumulated Rainfall Products for Early Detection of Heavy Rainfall Occurrence (173192)
Koji Nishiyama1, Kenji Wakimizu2, Izumi Yokota3, Kenichi Tsukahara3 and Toshiyuki Moriyama4, (1)Kyushu University, Faculty of Engineering, Fukuoka, Japan, (2)Kyushu university, Faculty of Agriculture, Fukuoka, Japan, (3)Kyushu University, Fuculty of Engineering, Fukuoka, Japan, (4)Fukuoka institute of Technology, Fukuoka, Japan, Fukuoka, Japan
Multi-iteration approach to studying tracer spreading using drifter data (182012)
Alison M Macdonald1, Irina Rypina1, David Alan Fertitta2, Sachiko Yoshida1 and Steven R Jayne1, (1)Woods Hole Oceanographic Institution, Physical Oceanography, Woods Hole, MA, United States, (2)Louisiana State University, Baton Rouge, LA, United States
EFFECTS OF OIL SPILLAGE ON VEGETATION, LAND AND WATER (ODU-GBORO, SAGAMU, OGUN STATE, SOUTH-WESTERN, NIGERIA) USING REMOTE SENSING AND GIS TECHNIQUES. (177893)
Olayinka Oseni, Federal University of Technology Akure, Akure, Nigeria

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