SAR for Disasters and Hydrological Applications [Advanced]

Key Info
Description - a brief synopsis, abstract or summary of what the learning resource is about: 

This training builds on the skills taught from previous ARSET SAR training in terms of the use of Google Earth Engine for flood mapping of radar data. This training presents two new topics; the use of InSAR for characterizing landslides and the generation of a digital elevation model (DEM).
Learning Objectives: By the end of this training, attendees will be able to:

  • Create a flood map using Google Earth Engine
  • Generate a map characterizing areas where landslides have occurred
  • Generate a digital elevation model (DEM)


Course Format: 

  • This webinar series will consist of three, two-hour parts
  • Each part will include a presentation on the theory of the topic followed by a demonstration and exercise for attendees. 
  • This training is also available in Spanish. Please visit the Spanish page for more information.
  • A certificate of completion will also be available to participants who attend all sessions and complete the homework assignment, which will be based on the webinar sessions. Note: certificates of completion only indicate the attendee participated in all aspects of the training, they do not imply proficiency on the subject matter, nor should they be seen as a professional certification.



Prerequisites: 
Prerequisites are not required for this training, but attendees that do not complete them may not be adequately prepared for the pace of the training. 



Part One: SAR for Flood Mapping Using Google Earth Engine
This session will focus on the use of the Google Earth Engine (GEE) to generate a flood map utilizing SAR images from Sentinel-1. The first part of this session will cover the basic principles of radar remote sensing related to flooding. The remaining time in the session will be dedicated to a demonstration on how to use GEE to generate flood extent products with Sentinel-1 and how to integrate socioeconomic data into the flood map to identify areas at risk.
Part Two: Interferometric SAR for Landslide Observations
Featuring guest speaker Dr. Eric Fielding from JPL, this session is focused on landslide observations utilizing and building on InSAR skills from the previous three SAR webinar series. The first part of the session will cover the physics of InSAR as related to landslides. The remainder will be focused on how to generate and interpret the derived landslide product.
 Part Three: Generating a Digital Elevation Model (DEM)
Featuring guest speaker Nicolás Grunfeld Brook, from Argentina’s CONAE, participants will learn how to generate a digital elevation model (DEM) through InSAR techniques. The first part of the session will cover the physics behind using two SAR phase images to generate a DEM. The remainder of the time will focus on how to generate a DEM.

Each part of 3 includes links to the recordings, presentation slides, exercises, and Question & Answer Transcripts.
 

Authoring Person(s) Name: 
Erika Podes
Sean McCartney
Eric Jameson Fielding
Alexander Louis Handwerger
Nicolás A. Grunfeld Brook
Authoring Organization(s) Name: 
NASA Applied Remote Sensing Training Program (ARSET)
License - link to legal statement specifying the copyright status of the learning resource: 
Creative Commons Attribution 2.0 Generic - CC BY 2.0
Access Cost: 
No fee
Primary language(s) in which the learning resource was originally published or made available: 
English
Also available in - other languages in which the learning resource has been translated or made available other than the primary: 
Spanish
More info about
Keywords - short phrases describing what the learning resource is about: 
Agriculture data
Disaster applications
Elevation data
Environmental management
Flood mapping applications
Hydrologic data
Land management
Landcover applications
Remote sensing
Satellite imagery
Sustainable Development Goals (SDGs)
Synthetic aperture radar data (SAR)
Subject Discipline - subject domain(s) toward which the learning resource is targeted: 
Education: Science and Mathematics Education
Physical Sciences and Mathematics: Earth Sciences
Physical Sciences and Mathematics: Environmental Sciences
Published / Broadcast: 
Tuesday, December 3, 2019
Publisher - organization credited with publishing or broadcasting the learning resource: 
NASA Applied Remote Sensing Training Program (ARSET)
Media Type - designation of the form in which the content of the learning resource is represented, e.g., moving image: 
Interactive Resource - requires a user to take action or make a request in order for the content to be understood, executed or experienced.
Contact Person(s): 
Brock Blevins
Contact Organization(s): 
NASA Applied Remote Sensing Training Program (ARSET)
Educational Info
Purpose - primary educational reason for which the learning resource was created: 
Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.
Learning Resource Type - category of the learning resource from the point of view of a professional educator: 
Learning Activity - guided or unguided activity engaged in by a learner to acquire skills, concepts, or knowledge that may or may not be defined by a lesson. Examples: data exercises, data recipes.
Target Audience - intended audience for which the learning resource was created: 
Citizen scientist
Data manager
Data policymaker
Early-career research scientist
Mid-career research scientist
Research scientist
Technology expert group
Intended time to complete - approximate amount of time the average student will take to complete the learning resource: 
More than 1 hour (but less than 1 day)