Description

Solar-Induced Chlorophyll Fluorescence (SIF) provides a unique remote sensing approach for measuring photosynthetic activity, offering real-time insights into vegetation stress and productivity that surpass traditional indices (e.g. Normalized Difference Vegetation Index (NDVI)) in sensitivity and accuracy. This intermediate training builds on a previous Applied Remote Sensing Training Program (ARSET) training that introduces the SIF measurement and covers several case studies of the impact of floods and droughts on agricultural systems and the impacts of fire on forested ecosystems.

Participants will learn fundamental principles of SIF remote sensing and its practical applications for monitoring vegetation dynamics across cropland and natural systems. The course demonstrates how SIF data can track crop phenological cycles, assess agricultural drought impacts, evaluate wildfire damage and recovery patterns, and quantify relationships between SIF observations and Gross Primary Production (GPP). Participants will gain hands-on experience analyzing SIF datasets from NASA missions including the Orbiting Carbon Observatory-2 (OCO-2) and Orbiting Carbon Observatory-3 (OCO-3), as well as using gap-filled data products derived using machine learning techniques.

Prerequisites

• Fundamentals of Remote Sensing
• Use of Solar Induced Fluorescence and LIDAR to Assess Vegetation Change and Vulnerability
• If you would like to replicate the Jupyter Notebook demonstrations provided in the training:
  • Have a github account
  • Have a NASA Earth Access Account
  • Follow your instructions in the prerequisites section of the notebook
  • Install git or Github Desktop installed on your computer to obtain the course materials
  • Install Python 3: refer to the python.org downloads page and install the latest version of python available for your system

Objectives

By the end of this training attendees will be able to:

• Recognize how the Solar Induced Fluorescence (SIF) is measured and used as a complementary measurement to commonly used indices (NDVI) for land and vegetation applications.
• Identify advantages and limitations of using space-based SIF measurements to monitor and evaluate vegetation health and condition.
• Run a given Jupyter Notebook to generate a Snapshot Area Map (SAM) plot from OCO-3 data for selected regions of interest to analyze and evaluate vegetation and land change due to fire impacts.
• Run a given Jupyter Notebook using GoSIF data for selected regions of interest to produce visualizations to analyze and interpret episodic land change due to droughts and floods.
• Compare how SIF products aggregated in space and time using open source tools are used to study vegetation change across different regions in a variety of science and applied use cases.

Target Audience

• Researchers, analysts, and end users who are interested in learning how to use SIF to study vegetative change for agriculture, land management, pre-fire conditions, and droughts.
• Students and academics who are interested in assessing vegetative change with satellite data and understanding SIF.

Course Format

• Three, 2-hour parts. Each part includes a 30-min Q&A session.
   

Sessions

Part 1 - Solar Induced Chlorophyll Fluorescence (SIF) Measurements from Space

Wednesday, Oct. 15, 2025

ARSET Instructor: Erika Podest (NASA JPL)

Guest Instructors: Nick Parazoo (NASA JPL), Jacqueline Ryan (NASA JPL)

• About ARSET
• Training Overview
• Part 1 introduction
• SIF Overview and SIF from Space
• Setting up your environment to work on SIF data sets
• Retrieving and spatially gridding SIF data
• Part 1 Summary
• Q&A session

Materials: 

• Part 1 Presentation Slides (PDF, 7.9 MB)
• Part 1 Q&A Transcript (PDF, 0.3 MB)

Part 2 - Overview of OCO-2 and OCO-3 Observing Modes and SIF Observations

Wednesday, Oct. 22, 2025

ARSET Instructor: Erika Podest

Guest Instructors: Junjie Liu (NASA JPL), Jacqueline Ryan (NASA JPL)

• Part 2 introduction
• SIF measurements in science and applications
• OCO-3 Snapshot Area Map (SAM) mode
• Comparison with flux tower data
• Case study: fire conditions and SIF in Oregon, 2020
• Part 2 Summary
• Q&A session

Materials:

• Part 2 Presentation Slides (PDF, 11.8MB)
• Part 2 Q&A Transcript

Part 3 - Working with Gap-Filled SIF Products

Wednesday, Oct. 29, 2025

ARSET Instructor: Erika Podest (NASA JPL)

Guest Instructors: Karen Yuen (NASA JPL), Jaqueline Ryan (NASA JPL)

• Part 3 Introduction
• Use of gap-filled SIF data products
• Case study: 2019 Midwestern US floods and impacts to agriculture
• Part 3 & Overall Training Summary
• Q&A session

Materials: 

• Part 3 Presentation Slides (PDF, 11.21 MB)
• Part 3 Q&A Transcript
• Homework (Due Nov. 12, 2025)