Description

This introductory webinar series will cover the fundamentals of solar induced fluorescence (SIF) and light detection and ranging (lidar), their applications, and an overview of different satellite data sources that are openly available. In addition, it will also include a step-by-step guide on how to access, open, and interpret SIF and lidar data.

SIF is a relatively new emerging satellite product, which provides information on photosynthetic activity versus Normalized Difference Vegetation Index (NDVI), which is a greenness index. It serves as a strong proxy to gross primary production (GPP), capturing dynamic responses of vegetation to stressors such as drought and temperature.

Lidar is a sensor system that illuminates a target and measures distance through the time taken for a pulse to reflect back to the sensor. Lidar can be used to generate topography and vegetation height maps and retrieve digital elevation data necessary for flood modeling and vulnerability, along with risk analysis. They are valuable datasets for disaster assessment of debris deposition, vegetation loss, and flooding.

Prerequisites

• Fundamentals of Remote Sensing

Objectives

By the end of this training, attendees will be able to understand the basic concepts of SIF and lidar sensors, how to interpret the measurements, and how they can be used to address different applications. In addition, attendees will also be able to access, open, and analyze SIF and lidar data.

Audience

Academia as well as local, regional, state, federal, and international organizations interested in using satellite imagery to support applications related to vegetation studies and disasters.

Course Format

Four 2-hour sessions

Sessions

Part 1: Lidar and its Applications

This session will cover the fundamentals of lidar measurements, the characteristics of different spaceborne lidar systems, and examples of application areas related to vegetation studies. It will be followed by a question and answer period.

Materials

• Part 1 Presentation Slides:
  • Podest (PDF, 4.82MB)
  • Neuenschwander (PDF, 7.42MB)
  • Kotlinski (PDF, 8.16MB)
• Part 1 Q&A Transcript (PDF, 0.20MB)

Part 2: Accessing and Analyzing Lidar Data for Vegetation Studies

This session will summarize where different spaceborne lidar measurements can be accessed. This will be followed by a demo showing participants how to open, interpret, and analyze lidar data for assessments of vegetation structure. The session will end with a question and answer period. 

Materials

• Part 2 Presentation Slides (PDF, 2.6MB)
• Part 2 Q&A Transcript (PDF, 0.15MB)

Optional For Part 2: Although not a prerequisite, in Part 2 there is a demonstration of 3D mapping of Global Ecosystem Dynamics Investigation (GEDI) data using QGIS and the Qgis2threejs plugin, and a demonstration of a data prep script for subsetting GEDI data using Python.

• In the demonstration, we show how to install the Qgis2threejs plugin.
• Download QGIS.
• Access Qgis2threejs plugin information.
• To install Python, see the instructions in this readme link. This provides instructions for installing a compatible Python environment for those users interested in executing the GEDI data prep script. See the section on Python Environment Setup.

Part 3: Solar Induced Fluorescence and Its Applications

This session will cover the fundamentals of SIF, how it is measured from space, and examples of application areas that this measurement can support. It will be followed by a question and answer period.

Materials

• Part 3 Presentation Slides (PDF, 10.15MB)
• Part 3 Q&A Transcript (PDF, 0.18MB)

Part 4: Accessing and Analyzing SIF Data for Vegetation Studies

This session will provide an overview of different satellite SIF datasets, their characteristics, and where they can be accessed. It will be followed by a demo with Orbiting Carbon Observatory-2 (OCO-2) data, showing participants how to open, interpret, and analyze the data to identify vegetation stress. The session will end with a question and answer period.

Materials

• Part 4 Presentation Slides (PDF, 5.32MB)
• Part 4 Q&A Transcript (PDF, 0.11MB)

Homework

• Homework (Due April 15, 2021)

Notes

In Part 4, there is a demonstration of: 

• Tools to read/analyze TROPOMI and OCO-2 data (Python and R)
• Gridding satellite data (Julia)

Part 4 tutorial (Julia):

• Please refer to slides 17 and 18 in the Part 4 slides for all links.
  • We use Pluto, a simple, reactive notebook for Julia (similar to ipython notebooks).
  • 1st Pluto Notebook “Demo_presentation.jl”
• Reading and selecting Tropospheric Monitoring Instrument (TROPOMI) and OCO-2 SIF data for arbitrary spatial shapes, temporal averaging, generating spatial composites (via oversampling), and evaluating uncertainties.
  • 2nd Pluto Notebook “Case_Study_illinois.jl”
  • Case Study: Impact of the 2019 Midwest Flood on SIF over Illinois