October 19, 2022

Disaster Assessment Using Synthetic Aperture Radar

SAR sensors are ideal for monitoring certain disasters or areas that are vulnerable to disasters especially because the signal can “see” the surface of the Earth during day or night conditions and under nearly all weather conditions. In addition, the signal can penetrate through vegetation and is sensitive to surface roughness and small displacements of the land surface. This intermediate, three-part webinar series will focus on the use of SAR to 1) assess areas at risk from disasters due to landslides through the use of interferometric SAR (INSAR). This is accomplished by measuring small movements (on the order of centimeters) of the land surface that are caused by gradual landslide motion, and how these movements vary with time; 2) characterize the extent of oil spills and their impacts. SAR data is sensitive to surface roughness, allowing for identifying areas where there are oil spills; 3) and characterizing inundation extent. The SAR signal can penetrate through the vegetation and detect inundation driven by large precipitation events or by natural events. This training will include theoretical portions for each disaster as related to the SAR signal interaction with surface conditions and demonstrations using Google Earth Engine, Jupyter Notebooks, and the SNAP Toolbox, all freely and openly available tools.

Relevant UN Sustainable Development Goals:
• Goal 11: Make cities and human settlements inclusive, safe, resilient and sustainable
• Target 11.5: By 2030, significantly reduce the number of deaths and the number of people affected and substantially decrease the direct economic losses relative to global gross domestic product caused by disasters, including water-related disasters, with a focus on protecting the poor and people in vulnerable situations
• Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries

Course Dates: October 19, 20, and 27, 2022

Times and Registration Information:

English Session: 11:00-13:00 EDT (UTC-4): https://go.nasa.gov/3BkK4S2
Spanish Session: 14:00-16:00 EDT (UTC-4): https://go.nasa.gov/3KQBoWm

Course Format: Three, 2-hour parts

Retweet option: https://twitter.com/NASAARSET/status/1571861920491048960

Location: Online Course
Host: NASA Applied Remote Sensing Training Program (ARSET)
Type: Online Course
Contact: brock.blevins@nasa.gov
Language: en