Training Information

  • Type: Synchronous online
  • Training Dates: 2-5 Nov 2021
  • Audience Location: Colombia
  • Partner: IDEAM, Colombia
  • Audience: 25 attendees from IDEAM and partners in South America
  • Prerequisites:
    • Intermediate familiarity with remote sensing
    • Basic familiarity with computer programming language (i.e. Python, JavaScript, etc.)

Training Description

Many nations in South America are subject to frequent impacts from geophysical and weather-related hazards. With Colombia being frequently obstructed by clouds, this training is introducing concepts and workflows for efficient and weather-independent flood monitoring. The training covers three main components: (1) streamflow forecasting techniques; (2) SAR-based surface water mapping workflows; and (3) approaches to combine runoff forecasting, SAR, and machine learning to enable water extent forecasting with high (daily) temporal resolution.

For this training, we teamed up with partners at the BYU Hydroinformatics Lab, IDEAM, and SERVIR Amazonia, who added their expertise on river runoff forecasting and machine learning to the training. The workshop included lectures and hands-on data processing labs using Jupyter notebooks.


Training Agenda

Day 1: Inauguration & Introduction to SAR / Mapping of Surface Water Extent with SAR [recording]

  • Inauguration:
    • Hector Gonzales, Introduction to IDEAM – [15 min]
    • Angelica Gutierrez, NOAA & AmeriGEO – [15 min]
  • Existing Technical Services:
    • Fabio Bernal Quiroga, IDEAM Dept. of Hydrology – [15 min]
    • Brian Zutta, SERVIR-Amazonia services & projects – [15 min]
  • Lecture 1: Introduction to Synthetic Aperture Radar – [60 min]

Day 2: Introduction to SAR Concepts and Theories [recording]

  • Lecture 2: Surface Water Mapping from SAR – The HydroSAR HYDRO30 Approach – [60 min]
  • Lab 1: SAR-based Surface Water Mapping Exercise – [30 min]
  • Lecture 3: Analysis-ready surface water maps from the NASA OPERA Project – [30 min]

Day 3: Introduction to GEOGLoWs Global Streamflow Processing / Streamflow Forecasting & Synthetic Images [recording]

  • Lab 2: GEOGLoWs Streamflow Processing Case Study – [60 min]
  • Lecture 4: Creating a synthetic SAR image – [90 min]

Day 4: The NISAR mission and Training Summary [recording]

  • Lecture 5: An Introduction to the NASA-ISRO SAR (NISAR) Mission – [30 min]
  • Discussion: IDEAM workflows & needs; next steps — 0.5 hr
  • Synthesis + closeout – [30 min]


Team photo of Franz Meyer

Franz Meyer

University of Alaska Fairbanks, Fairbanks, Alaska, U.S.A.

Team photo of Vanesa Martin

Vanesa Martin

University of Alabama in Huntsville, Huntsville, Alabama, U.S.A.

Team photo of Eric Anderson

Eric Anderson

SERVIR Science Coordination Office, Huntsville, Alabama, U.S.A.

Africa Flores-Anderson

SERVIR Science Coordination Office, Huntsville, Alabama, U.S.A.

Emil Cherrington

SERVIR Science Coordination Office, Huntsville, Alabama, U.S.A.

Jim Nelson

Brigham Young University, Provo, Utah, U.S.A.

Kel Markert

Brigham Young University, Provo, Utah, U.S.A.

Jorge Luis Sánchez-Lozano

SERVIR-Amazonia/CIAT, Cali, Colombia

Alex Lewandowski

Alaska Satellite Facility, University of Alaska Fairbanks, Fairbanks, Alaska, U.S.A.