NASA scientists have developed an artificial intelligence tool that could help coastal communities find harmful algal blooms earlier and more efficiently.
The agency says the tool brings together data from multiple Earth-observing satellites and compares it with field measurements. In recent tests, researchers reported that the system could detect harmful blooms in western Florida and Southern California, including specific species in complicated coastal waters.
A better map for water testing
Harmful algal blooms can close beaches, disrupt aquaculture and tourism, affect wildlife, and create public-health concerns. Today, local agencies often need boats, water samples and lab tests to confirm what is happening. That work is essential, but it can be slow and difficult to aim before a bloom spreads.
NASA's approach is not meant to replace people on the water. Instead, researchers describe it as a force multiplier: a way to show where and when teams may want to collect samples, issue warnings or focus attention. Michelle Gierach of NASA's Jet Propulsion Laboratory said a tool like this can help identify where to sample as a bloom begins.
Satellites working together
The project uses clues from several missions and instruments, including NASA's PACE satellite and TROPOMI. A self-supervised machine-learning system looks for patterns across large streams of satellite data, then connects those patterns to real-world observations.
The next step is more testing with more coastlines and other water bodies, including lakes. It is good news because it turns space data into something practical on Earth: earlier information for communities trying to protect beaches, fisheries and local livelihoods.
Source: NASA, reporting on a JPL-led artificial intelligence tool for detecting harmful algal blooms using satellite and field data.
