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​Satellite Radar for Rapid Disaster Response

Published on: 28-Oct-2020

Event Type: Seminar
Event Date: 28 October  2020 - 10:00am to 11:00am
Venue: Online (via Zoom)
Speaker: Dr Sang-Ho Yun

About the speaker:

Sang-Ho Yun is a Geophysicist and Radar Scientist at the NASA Jet Propulsion Laboratory (JPL). He received his PhD in Geophysics and Master’s in Electrical Engineering from Stanford University, and prior to joining JPL, he was a Postdoc at the U.S. Geological Survey (USGS). As the Disaster Response Lead of the Advanced Rapid Imaging and Analysis (ARIA) project at JPL and California Institute of Technology, he and his team have supported over 90 major disaster events globally. He received the 2018 NASA Exceptional Public Achievement Medal and the 2014 NASA Exceptional Early Career Medal for innovative use of SAR data in support of rapid post-disaster response. He is currently the Principal Investigator for three NASA projects to develop algorithms and systems for global rapid damage and flood mapping as well as human activity monitoring for the COVID-19 Global Pandemic response. His profile is featured on the NASA People website at https://appliedsciences.nasa.gov/our-impact/people/sang-ho-yun-improving-disaster-response-satellites-see-through-clouds


About the event:

Annually, natural disaster events claim about 60,000 people’s lives and cause ~232 billion U.S. dollars of global economic loss. My team uses radar remote sensing data to produce maps that show the locations of floods or damage caused by earthquakes, tsunamis, volcanic eruptions, wildfires, landslides, tropical cyclones, and tornadoes. Our products are being used by responding agencies globally, including the World Food Programme, the AHA (ASEAN Humanitarian Assistance) Centre, Sentinel Asia, World Bank, FEMA, CAL FIRE, USGS, etc. The primary tool of our analysis is satellite Synthetic Aperture Radar (SAR) observations. We have developed various techniques to use SAR for mapping flood extents and structure damage, including using novel Bayesian and machine-learning techniques. In this presentation, I will share a brief history of our development efforts for the past decade and stories of recent disaster response support, including the ongoing California fires, the Beirut explosion, and the COVID-19 global pandemic.

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