NH52A:
Advances in Remote Sensing of Natural Hazards II


Session ID#: 10919

Session Description:
Recent advances in remote sensing technologies, such as optical-infrared imaging, passive/active microwave remote sensing, InSAR, LiDAR, and hyperspectral remote sensing have been a primary impetus to advancing the studies of natural hazards. Fast-growing remote sensing observations have provided large information and data for understanding, detecting, and assessing natural hazards, while improved remote sensing technologies have improved the resolution, accuracy, and precision of remote sensing imagery. This session invites all studies on the advances in theories and applications of remote sensing technologies for observational, theoretical, and numerical modeling studies of natural hazards.
Primary Convener:  Ke Zhang, University of Oklahoma Norman Campus, Norman, OK, United States
Conveners:  Amir AghaKouchak, University of California Irvine, Civil and Environmental Engineering, Irvine, CA, United States, Yang Hong, University of Oklahoma Norman Campus, School of Civil Engineering and Environmental Science (CEES), Norman, OK, United States and Dalia Kirschbaum, NASA Goddard Space Flight Center, Hydrological Sciences Laboratory, Greenbelt, MD, United States
Chairs:  Ke Zhang, The University of Oklahoma, CIMMS, Norman, OK, United States, Amir Aghakouchak, University of California Irvine, The Henry Samueli School of Engineering, Irvine, CA, United States, Dalia Kirschbaum, NASA Goddard Space Flight Center, Hydrological Sciences Laboratory, Greenbelt, MD, United States and Yang Hong, University of Oklahoma Norman Campus, School of Civil Engineering and Environmental Science (CEES), Norman, OK, United States
OSPA Liaison:  Ke Zhang, The University of Oklahoma, CIMMS, Norman, OK, United States

Cross-Listed:
  • G - Geodesy
  • H - Hydrology
  • IN - Earth and Space Science Informatics
  • NS - Near Surface Geophysics
Index Terms:

4314 Mathematical and computer modeling [NATURAL HAZARDS]
4315 Monitoring, forecasting, prediction [NATURAL HAZARDS]
4337 Remote sensing and disasters [NATURAL HAZARDS]
4341 Early warning systems [NATURAL HAZARDS]

Abstracts Submitted to this Session:

Remote sensing of rainfall for flash flood prediction in the United States (Invited) (76621)
Jonathan J Gourley1, Zac Flamig2, Humberto J Vergara, PhD2, Race A Clark3, Pierre Kirstetter4, Galateia Terti2, Yang Hong2 and Kenneth Howard5, (1)NOAA/National Severe Storms Laboratory, Norman, OK, United States, (2)University of Oklahoma Norman Campus, Norman, OK, United States, (3)NOAA/NSSL, Norman, United States, (4)University of Oklahoma Norman Campus, Norman, United States, (5)National Severe Storms Lab, Norman, OK, United States
Advancing Satellite-Based Flood Prediction in Complex Terrain Using High-Resolution Numerical Weather Prediction (Invited) (64777)
Emmanouil N Anagnostou, Professor, Civil and Environmental Engineering, Storrs, United States, Efthymios Ioannis Nikolopoulos, Innovative Technologies Center SA, Athens, Greece, Xinxuan Zhang, University of Connecticut, Department of Civil & Environmental Engineering, Groton, CT, United States and Nikolaos S Bartsotas, National and Kapodistrian University of Athens, Athens, Greece
Supervised classification of aerial imagery and multi-source data fusion for flood assessment (64899)
Elena Sava1, Laura Clemente-Harding1 and Guido Cervone2, (1)Pennsylvania State University Main Campus, University Park, PA, United States, (2)Pennsylvania State University Main Campus, Department of Geography and Institute for Computational and Data Sciences, University Park, PA, United States
Combining UAV and high-resolution image-based particle image velocimetry to monitor flow in lakes and rivers (85690)
Gianluca Blois1, Jim Best2, Kenneth T Christensen3, Andrew B Kennedy1, Aaron Sheffield Donahue4, Naira Hovakimyan5, Venanzio Cichella5 and Ishaan Pakrasi5, (1)University of Notre Dame, Notre Dame, IN, United States, (2)University of Illinois at Urbana Champaign, Departments of Mechanical Science and Engineering and Ven Te Chow Hydrosystems Laboratory, Champaign, United States, (3)University of Notre Dame, Aerospace and Mechanical Engineering, Notre Dame, IN, United States, (4)University of Notre Dame, Notre Dame, United States, (5)University of Illinois at Urbana Champaign, Mechanical Science and Engineering, Urbana, IL, United States
A methodology to generate high-resolution digital elevation model (DEM) and surface water profile for a physical model using close range photogrammetric (CRP) technique (81379)
Vijay Kisan Mali and Soumendra Nath Kuiry, Indian Institute of Technology Madras, Chennai, India
Lightning activity variation during the evolution of tropical cyclones in the southwest Pacific region (61260)
Ashneel Chandra1, Sushil Kumar2 and Abhikesh Kumar1, (1)University of the South Pacific Laucala, Suva, Fiji, (2)The University of the South Pacific, School of Engineering and Physics, Suva, Fiji
Investigating the Spatial Characteristics of Forest Fire in North Korea using Remote Sensing and GIS (63231)
Jin RI, Sungkyunkwan University, Suwon, Gyeonggi-do, Korea, Republic of (South) and Kyoo-seock Lee, Sungkynkwan University, daejeon, Korea, Republic of (South)

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