Catch Me If You Can: Near-Real-Time Monitoring of Water Hyacinth

Category: Managing Water Quality and Precipitation Anomalies
Project Team: Lake Victoria Water Resources II
Team Location: NASA Marshall Space Flight Center at NSSTC – Huntsville, Alabama

A wetness index highlighting areas with high chlorophyll activity in the focus study area. Image Credit: Lake Victoria Water Resources II Team

A wetness index highlighting areas with high chlorophyll activity in the focus study area. Image Credit: Lake Victoria Water Resources II Team

Jeanné le Roux
Daryl Ann Winstead
Christina Fischer
Sara Amirazodi
Dwight Tigner

Dr. Jeffrey Luvall (NASA at the National Space Science and Technology Center)
Dr. Robert Griffin (The University of Alabama in Huntsville)
Africa Flores (NASA SERVIR Coordination Office at MSFC)
Dr. Joe Ortiz (Kent State University)
Dulci Avouris (Kent State University)

Past/Other Contributors:
Nick Rousseau (Center Lead)
Austin Vacek


Lake Victoria has a surface area of 68,800 square kilometers, making it the largest lake in Africa. The lake is surrounded by Kenya, Tanzania, and Uganda and is home to more than 30 million people. These people rely on the lake for all aspects of their lives including fishing, agriculture, and industrial applications. However, the increasing population has negatively impacted water quality due to sewage, as well as agricultural and industrial runoff. Furthermore, the introduction of Eichhornia crassipes, or water hyacinth, has been detrimental to local communities by blocking fishing access and providing breeding grounds for diseases carried by mosquitoes and snails. Ongoing efforts between the NASA SERVIR Coordination Office at Marshall Space Flight Center, the SERVIR-Eastern and Southern Africa Hub, the Regional Centre for Mapping of Resources for Development (RCMRD), and the Makerere University Department of Geomatics and Land Management have been assessing and monitoring water quality parameters, such as chlorophyll concentration, temperature, and turbidity, for Lake Victoria using the Moderate Resolution Imaging Spectrometer (MODIS) sensor on the Aqua satellite. This project sought to include the use of Sentinel-2 Multispectral Imager (MSI), as well as the Operational Land Imager (OLI) sensor on Landsat 8, to assess water hyacinth presence in addition to current monitoring activities. This study focused on the Winam Gulf region of Lake Victoria in Kenya since this area experiences abundant water hyacinth activity and has been identified by RCMRD as an area of focus. As a continuation of the Lake Victoria Water Resources project from fall 2015, this project used data previously collected to create an automated model to detect water hyacinth. This model employed Python scripting to continuously download and process new Landsat 8 images and automate the methodology for Sentinel-2 images. These end products will be utilized by partner organizations in their water hyacinth monitoring efforts.

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Michael Brooke 15-04-2016, 16:37

Great job on the video! I’ve seen firsthand what the water hyacinth can do; there was an outbreak in a lake near my hometown when I was young. What sort of measures are taken to control the plants once they have infested an area?

Daryl Ann Winstead (Lake Victoria Water Resources II) 18-04-2016, 11:41

Hi Michael!

Thank you! There have been past removal efforts such as introducing a species of weevils into the lake that feed on the water hyacinth or mechanical extraction which is costly and time consuming. Both of which work for a while but then the water hyacinth comes back. This is what our end products are important to our project partners so they can further research the water hyacinth in hopes to pinpoint the source of what makes the water hyacinth grow. The locals have found ways to use the water hyacinth, such as making bags, purses, and furniture from the water hyacinth roots. Please let me know if you have any other questions!!

Michael Brooke 18-04-2016, 15:12

Thanks Daryl Ann!

Leigh Sinclair 12-04-2016, 13:42

Awesome! Why is the water hyacinth such a problem in the Winam Gulf?

Daryl Ann Winstead (Lake Victoria Water Resources II) 13-04-2016, 14:00

Hi Leigh! Great question! The Winam Gulf is ideal for water hyacinth outbreaks due to its shallower depth, isolated waters, and increased runoff from agriculture crops and waste from factories. Please let me know if you have any other questions that I can answer! Thanks!

Leigh Sinclair 13-04-2016, 14:52


Teresa Fenn 11-04-2016, 10:16

Awesome project! My team had to create a python tool as well, but we were unable to incorporate near real-time satellite imagery. Where did you get your imagery from?

Daryl Ann Winstead (Lake Victoria Water Resources II) 11-04-2016, 14:13

Hi Teresa! Great question! The team implemented the DEVELOP National Program Python Package (dnppy) which is available of the DEVELOP National Program’s GitHub page. The dnppy has a “Download” module with a “fetch_lansdsat8” function that downloads data from the Landsat Amazon Web Server. The team created a code that pulled the operating system’s date using the “datetime” function. Then, we used the “timedelta” function to create a change in time, such as 15 days prior. These two dates were used to create a date range that the “fetch_landsat8” function used to search for available Landsat 8 images of the Amazon Web Server. Unfortunately, the Amazon Web Server did not update tiles for our study area as often as the USGS web servers, so the date range had to be adjusted accordingly. Since this was an issue, we also created another python script and implemented it into a toolbox in ArcMap10.x and the user can enter it the Green and SWIR bands in order to achieve the same result. This is difficult to portray this process so if you have any other questions, please let me know!!! Thanks!

Alec Courtright (NCEI Node) 08-04-2016, 12:19

Really great video! Did you guys run into any issues comparing Landsat-8 and Sentinel-2 with the difference in temporal resolutions?

Daryl Ann Winstead (Lake Victoria Water Resources II) 10-04-2016, 08:37

Hi Alec! Great question! One of the biggest issues when using the Sentinel-2 MSI data along with the Landsat 8 OLI data was the size of the Sentinel-2 MSI data. Due to it’s file size, it took a really long time to download it and sometimes it didn’t even download properly. Also, we used WorldView-1 imagery to do our accuracy assessment and since the Sentinel-2 satellite is new, there were not any images that lined up with the WorldView-1 dates. So, we were unable to conduct the accuracy assessment on the Sentinel-2 MSI outputs at this time. Let me know if you have anymore questions! Thanks!


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