Scientists mimicked the
neural networks of the brain to map phytoplankton types in
the Mediterranean Sea. A new study published in
the Journal of Geophysical
Research: Oceans presented a new method of classifying
phytoplankton that relies on artificial intelligence clustering.
Phytoplankton blanket surface waters of the world’s oceans and
pigments in their cells absorb certain wavelengths of light, like the
chlorophyll that gives plants their green color. Viewed from space, the color
of the ocean’s surface changes depending on the phytoplankton growing there. In
the Mediterranean Sea,
where the latest study focused its efforts, an array of phytoplankton species
bloom throughout the year.
Past research
has mined satellite
images of ocean color in the Mediterranean for common
pigments found in phytoplankton. A combination of pigments can reveal a certain
type of dominant phytoplankton in the area, like certain species of diatoms
that can be spotted because of their unique orange pigment, fucoxanthin. But
connecting the complex relationships between satellite image pixels, pigments,
and phytoplankton types can make for a tricky analysis.
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