Homework: Monitoring Water Quality of Inland Lakes using Remote Sensing

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This homework includes questions from all three parts of the training series. You might want to record your answers on a sheet of paper or word document before submitting them here. You will not be able to save your answers and return to complete this form at a later time.

To receive a certificate of completion, you must have attended all three parts and have completed this homework by Tuesday, August 8, 2023. Once you submit the homework, you will receive an email with a copy of your responses.

Once you click submit, you can click "View Score" to see how you did.

Email *

Name (First Last) *

This water quality parameter is used as an indicator of lake water clarity. *

1 point

Nutrients

Salinity

Secchi Depth

Temperature

This satellite/sensor has the highest spatial and temporal resolution. *

1 point

Sentinel-2/MSI

Landsat 9/OLI

Aqua MODIS

Sentinel-3/OLCI

This sensor has the largest number of spectral bands in the optical range.
*

1 point

MSI

OLI

MODIS

OLCI

Total Suspended Sediments have maximum water-leaving reflectance in this spectral band.

1 point

Red

Green

Blue

All of the above

Once you have remote sensing data, you do not need in situ water quality measurements in lakes.
*

1 point

True

False

GLORIA data are available globally but in a limited number of lakes.
*

1 point

True

False

The CyAN (Cyanobacteria Assessment Network) Web Application provides:
*

1 point

Cyanobacteria Type

Cyanobacteria Count

Cyanobacteria Size

CyAN has a mobile phone application.
*

1 point

True

False

CyAN uses this currently orbiting sensor to detect Cyanobacteria:

1 point

VIIRS

MSI

OLCI

One of the limitations of using optical satellite data is that…

1 point

they have no hyperspectral information.

orbit swaths are usually narrow.

they cannot see the surface in cloudy conditions.

they cannot be used over oceans.

What type of regression was used in the demonstration for Part 3?

1 point

linearFit()

linearRegression()

randomForestRegression()

polynomialRegression()

Upload a screenshot of the Sentinel-2 RGB image from Lake Erie for 19 July 2020 you saved in Exercise-1A from Part 1 of the training to the following link, using the file name YourLastName_WQ_E1: https://drive.google.com/drive/folders/1BXrBJB2JsqP9psLTl4UvMGQgCCb9i4jJ?usp=sharing

Using the CyAN web Application, select a lake and download (or take a screenshot) of the Cyanobacteria bloom map and get a time series following the Exercise from Part 2 of this training and upload both to the following link, using the file name YourLastName_WQ_E2: https://drive.google.com/drive/folders/1BXrBJB2JsqP9psLTl4UvMGQgCCb9i4jJ?usp=sharing

Uncomment a line of code from the Part 3 demonstration (line 351 or 353) and export the feature collection as a CSV file to your Google Drive. Upload the CSV file to the following link, using the file name YourLastName_WQ_E3: https://drive.google.com/drive/folders/1BXrBJB2JsqP9psLTl4UvMGQgCCb9i4jJ?usp=sharing

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