Systems, methods, and devices for detecting harmful algal blooms

A method for detecting harmful algae blooms, the method comprising:

• providing a plurality of autonomous watercraft;
• receiving remote imaging data of a body of water;
• inputting the remote imaging data to a trained machine learning model configured to generate a geotagged harmful algal bloom (HAB) probability map;
• deploying the plurality of autonomous watercraft based on a deployment strategy, wherein the deployment strategy is based on the HAB probability map;
• collecting, using the plurality of autonomous watercraft, a plurality of water samples to obtain a plurality of temporally and spatially resolved water sample measurements;
• and
• outputting for display a map overlaying the temporally and spatially resolved water sample measurements and HAB probability map.

A computing system for detecting harmful algae blooms, the system comprising:

• a processor;
• and
• a memory operably coupled to the processor, the memory having computer-executable instructions stored thereon that, when executed by the processor, cause the processor to:
• receive remote imaging data of a body of water;
• input the remote imaging data to a trained machine learning model configured to generate a geotagged harmful algal bloom (HAB) probability map;
• determine a deployment strategy for a plurality of autonomous watercraft based on the geotagged harmful algal bloom (HAB) probability map;
• and
• transmit one or more control signals to the plurality of autonomous watercraft based on the deployment strategy, wherein the plurality of autonomous watercraft are configured to collect and analyze a plurality of water samples to obtain a plurality of temporally and spatially resolved water sample measurements;
• and
• output for display a map overlaying the temporally and spatially resolved water sample measurements and HAB probability map.