The Algae Project | Automated Detection of Hazards
Awards & Nominations
The Algae Project has received the following awards and nominations. Way to go!
Automated Detection of Hazards
The Algae Project
Summary
Globally, some algal blooms are regarded as harmful because of associated physical ailments, damages to marine life, and impacts on fishing and shipping activities. Locally, reliance on desalination facilities adds another level of hazard as algal blooms can impact freshwater security. In an effort to maintain both environmental and economic health, we have developed an app which uses satellite, historical, and in-situ data to model algal blooms locally and help monitor and predict blooms of impact. This app will be vital to government operations for maintaining health and safety, as well as informative to local industry, ocean adventurers, and the general public.
How We Addressed This Challenge
The Algae Project is an app that integrates historical, in-situ, and satellite data into a model that can be used to monitor and predict harmful algal blooms. Just like hurricanes, forest fires, blizzards, and other phenomena, algal blooms are a natural part of our planet’s cyclic processes, and can have many benefits for the environment. However, anthropogenic influences like pollution and shipping have bolstered these events to become more extreme; making them larger, more frequent, last longer, and appear in places where they did not occur before. This has increased impact on marine life, human life, fishing, shipping, tourism, and other industries. In the UAE, algal blooms can also affect freshwater security since the blooms can impact desalination plants.
The main function of The Algae Project app is to identify areas of potential algal blooms based on real-time monitoring of sea surface temperature, salinity, chlorophyll A, inorganic carbon, nitrates, phosphates, and ocean currents. The interface of The Algae Project app allows users to view updates about marine conditions, and notifies them of any locally issued warnings or necessary precautions that should be taken. It lets them toggle backwards in time to learn more about algal bloom trends, as well to adjust parameters in the simulation to see how algal blooms are affected by each parameter.
Our goal with The Algae Project is to aid relevant authorities in decreasing response time and mitigating potential hazards caused by algal blooms. Furthermore, with our simulation feature, we wish to provide an educational tool to students, or simply curious users, to better understand algal blooms.
How We Developed This Project
As a team of scientists and software developers based in the UAE, we were focused on solving a local challenge using global tools. Being a coastal nation that prides itself on its rich maritime history, we felt it was important to focus on an issue that lay at the heart of the nation. Algal blooms have affected the people of the UAE across many fronts, including economic, environmental, social, and cultural. Choosing a challenge that modeled scientific evidence to make it more tangible seemed like a perfect combination of our passions and abilities.
Our approach was simple, find the root cause of the issue, explore remote sensing options, and create a tangible platform to aid authorities and boost awareness. Since algal blooms happen annually in certain areas, historical data about the locations, time of year, frequency, longevity, and water conditions allowed us to determine conditional indicators and hotspots. When combined with data about algal blooms caused by anthropomorphic sources we were able to learn about which parameters should be monitored for the early detection of potentially hazardous algal blooms. The selected parameters were sea surface temperature, salinity, chlorophyll A, inorganic carbon, nitrates, phosphates, and ocean currents. This is the backbone of our machine learning model, and the adjustable parameters in the simulation.This can be expanded to include other parameters, like turbidity, once better monitoring techniques become available. From there, we assimilated in-situ UAE data from various local government agencies that monitor local water conditions and NASA satellite information to track our parameters in real time for our prediction model and simulation.
We configured an ocean simulator that can model things like salinity, and output files in the same format as NASA satellite images of the same parameters. We have written code that will open the satellite images.
With the machine learning complete, we set up an ocean simulator to match historical NASA data. This can be advanced with optimisation techniques such as evolutionary algorithms, fine tuning the ocean parameters, and even the topography of the land as well. Once the simulation and historical data were matched and verified to be accurate through cross validation techniques, the simulation could predict algae blooms.
Python was used alongside the VEROS ocean simulator. The code outputs files in NetCDF format, which matches the format of the real world data given by NASA. No specialist hardware was used, though ocean modelling could be sped up significantly with a graphics card.
We faced a lot of challenges in trying to model a cube of the ocean with all the parameters and simulate the variables. We overcame this by allowing for low resolution outputs instead. We also had an immense challenge in figuring out how to make this more interactive and engaging to be used as an educational tool. This made us move from being a prediction model platform to a multi-purpose simulation platform that will drive engagement.
How We Used Space Agency Data in This Project
We built our model thanks to the rich NASA satellite datasets available online via web api. The Algae Project uses EOSDIS Worldview data sets as the core tool in its parameter monitoring and modeling for sea surface temperature, salinity, chlorophyll A, and ocean currents. The data sets and visuals are integrated into the app and is a large part of the user interface.
Project Demo
https://youtu.be/Mjb4ln2i8Vc
Data & Resources
Derek Baldwin, C., 2020. Red Tide Blooms Along UAE Coastline. [online] Gulfnews.com. Available at: <https://gulfnews.com/uae/environment/red-tide-blooms-along-uae-coastline-1.2162673> [Accessed 4 October 2020].
Worldview. 2020. Worldview: Explore Your Dynamic Planet. [online] Available at: <https://worldview.earthdata.nasa.gov/> [Accessed 4 October 2020].
Soe.ae. 2020. [online] Available at: <https://www.soe.ae/wp-content/uploads/2017/10/environmental-report-water-quality.pdf> [Accessed 4 October 2020].
Veros.readthedocs.io. 2020. Publications — Veros 0.2.2+79.Gc7485d5.Dirty Documentation. [online] Available at: <https://veros.readthedocs.io/en/latest/more/publications.html> [Accessed 4 October 2020].
Veros.readthedocs.io. 2020. Versatile Ocean Simulation In Pure Python — Veros 0.2.2+79.Gc7485d5.Dirty Documentation. [online] Available at: <https://veros.readthedocs.io/en/latest/index.html#> [Accessed 4 October 2020].
Cmr.earthdata.nasa.gov. 2020. JPL SMAP Level 3 CAP Sea Surface Salinity Standard Mapped Image 8-Day Running Mean V4.3 Validated Dataset. [online] Available at: <https://cmr.earthdata.nasa.gov/search/concepts/C1702143760-PODAAC.html> [Accessed 4 October 2020].
NASA. 2020. Algae Bloom In Lake St. Clair. [online] Available at: <https://www.nasa.gov/image-feature/algae-bloom-in-lake-st-clair> [Accessed 4 October 2020].
Usgs.gov. 2020. Causes Of Toxic Golden Algal Blooms Determined. [online] Available at: <https://www.usgs.gov/news/causes-toxic-golden-algal-blooms-determined> [Accessed 4 October 2020].
LKT Labs. 2020. Brevetoxin 1 - LKT Labs. [online] Available at: <https://lktlabs.com/product/brevetoxin-1/> [Accessed 4 October 2020].
Arxiv.org. 2020. [online] Available at: <https://arxiv.org/ftp/arxiv/papers/2003/2003.05694.pdf> [Accessed 4 October 2020].
Gulfnews.com. 2020. Ministry Of Environment Monitors Algal Bloom In UAE’S Waters. [online] Available at: <https://gulfnews.com/uae/environment/ministry-of-environment-monitors-algal-bloom-in-uaes-waters-1.1271712> [Accessed 4 October 2020].
The National. 2020. 'Algal Bloom Threat Will Rise With Heavy Increase Of Ship Traffic'. [online] Available at: <https://www.thenational.ae/uae/environment/algal-bloom-threat-will-rise-with-heavy-increase-of-ship-traffic-1.531776> [Accessed 4 October 2020].
The National. 2020. Red Alert: Ministry Monitors Algal Bloom In UAE's Regional Waters. [online] Available at: <https://www.thenational.ae/uae/environment/red-alert-ministry-monitors-algal-bloom-in-uae-s-regional-waters-1.698322> [Accessed 4 October 2020].