Description

This advanced-level training led by NASA's Applied Remote Sensing Training Program (ARSET) focuses on using remote sensing observations from Landsat 8 and 9, Sentinel-2, and Sentinel-3A and -3B for assessing water quality parameters including chlorophyll-a concentration, turbidity, and total suspended solids (TSS) in inland lakes. This training also highlights the importance of in situ measurements of these parameters, coincident with satellite observations, in developing methodologies for operational water quality monitoring. Participants perform hands-on exercises in Google Earth Engine (GEE) to access satellite data and develop methodologies to assess water quality parameters. In addition, we provide an overview of Cyanobacteria Assessment Network (CyAN), an early warning system to assess algal blooms in freshwater lakes.

Prerequisites

• Fundamentals of Remote Sensing
• Integrating Remote Sensing into a Water Quality Monitoring Program
• Participants should create a GEE account prior to the start of the training by visiting the new Earth Engine account sign up page.

Sessions

Part 1: Overview of Remote Sensing Observations to Assess Water Quality

• Describe state-of-the art, high spatial and spectral resolution observations and their access using GEE
• Describe open source, in situ measurements of water quality parameters
• Provide information about upcoming NASA missions useful for water quality monitoring
• Demonstration and Exercise
  • Introduction to GEE
  • Access Landsat 8 and Sentinel-2 surface reflectance data using GEE
  • Access Sentinel-3 top of the atmosphere reflectance data using GEE
  • Explore and download in situ measurements of water quality parameters (chlorophyll-a concentration, turbidity, and TSS) for selected lakes

ARSET Instructors

 Amita Mehta and Sean McCartney

Materials

• Part 1 Presentation Slides (PDF, 13.0 MB)
• Part 1 Q&A Document (PDF, 0.2 MB)
• Exercise Information:
  • Part 1 Exercise Instructions (PDF, 0.1 MB)
  • Part 1 GEE Code Links (PDF, 0.02 MB)
  • Part 1 Sample Data (CSV, 0.01 MB)

Materiales en Español

• Diapositivas de la Presentación de parte 1 (PDF, 8.3 MB)

Part 2: Cyanobacteria Assessment Network (CyAN)

• Overview and Applications of CyAN
• Demonstration and Exercise
  • Explore CyAN website

ARSET Instructor

Amita Mehta

Guest Instructors

Bridget Seegers, Blake Schaeffer

Materials

• Part 2 Presentation Slides (PDF, 4.5 MB)
• Part 2 Q&A Document (PDF, 0.2 MB)
• Part 2 CyAN Exercise (PDF, 1.0 MB)

Materiales en Español

• Diapositivas de la Presentación de parte 2 (PDF, 27.7 MB)

Part 3: Assess Water Quality using Satellite and In Situ Observations

• A brief review of methodologies to assess water quality from remote sensing
• Benefits and limitations of various satellite sensors for water quality monitoring
• Training summary
• Demonstration and Exercise:
  • Calculate spectral indices as indicators of water quality from Landsat, Sentinel-2, and Sentinel-3 observations
  • Develop statistical coefficients to derive water quality parameters based on remote sensing and in situ data
  • Part 3 GEE Code Links

ARSET Instructors

Sean McCartney and Amita Mehta

Materials

• Part 3 Presentation Slides (PDF, 7.7 MB)
• Part 3 Q&A Document (PDF, 0.2 MB)

Homework

• Homework (Due August 8, 2023)

Materiales en Español

• Diapositivas de la Presentación de parte 3 (PDF, 5.9 MB)