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Updated: Jun 26, 2025

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
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Multi-vehicle adaptive 3D mapping for targeted ocean sampling.

Tore Mo-Bjørkelund1, Sanna Majaneva2, Glaucia Moreira Fragoso2

  • 1Department of Marine Technology, Norwegian University of Science and Technology, Trondheim, Norway.

Plos One
|May 8, 2024
PubMed
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Autonomous underwater vehicles provide real-time chlorophyll a measurements for mapping phytoplankton biomass. This adaptive, collaborative approach enhances understanding of ocean processes and plankton patchiness.

Area of Science:

  • Marine Biology
  • Oceanography
  • Autonomous Systems

Background:

  • Phytoplankton distribution is patchy, making 3D ocean mapping challenging.
  • Traditional sampling methods miss fine-scale horizontal and temporal variability.
  • Accurate identification of phytoplankton patches requires advanced spatial and temporal data.

Purpose of the Study:

  • To demonstrate the use of autonomous underwater vehicles (AUVs) for real-time phytoplankton biomass mapping.
  • To investigate adaptive sampling strategies for maximizing information gain in oceanographic surveys.
  • To assess the effectiveness of collaborative AUV operations for understanding ocean processes.

Main Methods:

  • Two AUVs equipped with chlorophyll a sensors collected real-time data.

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  • AUVs employed adaptive navigation, prioritizing areas of high concentration, uncertainty, and safety.
  • Vehicles collaborated, sharing data via satellite to optimize information exchange under bandwidth limitations.

    • Main Results:

    • AUVs successfully mapped spatiotemporal phytoplankton distribution and patchiness.
    • Adaptive movement strategies improved data acquisition efficiency.
    • Collaborative AUV operations facilitated comprehensive data collection for oceanographic studies.

    Conclusions:

    • Real-time data from multiple AUVs combined with targeted sampling improves the understanding of plankton patchiness.
    • Adaptive and collaborative AUV strategies are effective for 3D ocean mapping and studying ocean processes.
    • This approach offers a significant advancement over traditional sampling methods for phytoplankton research.