skip to main content
10.1145/3607834.3616570acmconferencesArticle/Chapter ViewAbstractPublication PagesmmConference Proceedingsconference-collections
short-paper

SkySea: Connecting Satellite, UAV and Underwater Imagery for Benthic Habitat Mapping

Authors Info & Claims
Published:29 October 2023Publication History

ABSTRACT

Satellite imagery, UAV imagery, and geo-referenced underwater photo transects (from the surface) are different methods used in marine monitoring and benthic habitat mapping applications to collect observations at different spatial scales. There are however challenges in linking them all together to provide fine-grained mapping and analysis for underwater, benthic habitats with complex geometric and ecological properties. We propose a novel framework called SkySea that offers users access to aligned observational data at multiple spatial scales. SkySea can integrate satellite images (e.g., from SENTINEL-2 at 10m resolution), UAV images (<5cm ground sampling distance), detailed underwater images, 3D reconstruction of the seafloor/benthos from underwater images, and make the data available through a commonly used user interface, such as QGIS. Initial evaluation indicates that the spatial overlay achieves sub-meter-level accuracy, while the underwater 3D reconstruction reaches an average relative error of less than 10% for size estimation with reference objects. We believe that this is a novel and innovative framework to achieve a seamless connection across an enormous gap of scales from satellite images, regional UAV images, local underwater images and local 3D reconstruction of the underwater environment, for benthic habitat mapping. It enables marine biologists to perform survey planning, species mapping, and model validation tasks in an integrated pipeline.

References

  1. Matthias Adorjan. 2016. OpenSfM: A Collaborative Structure-From-Motion System. Ph.,D. Dissertation. Wien.Google ScholarGoogle Scholar
  2. V. Brandou, A. G. Allais, M. Perrier, E. Malis, P. Rives, J. Sarrazin, and P. M. Sarradin. 2007. 3D Reconstruction of Natural Underwater Scenes Using the Stereovision System IRIS. In OCEANS 2007 - Europe. 1--6. https://doi.org/10.1109/OCEANSE.2007.4302315Google ScholarGoogle ScholarCross RefCross Ref
  3. Elisa Casella, Pia Lewin, Mattia Ghilardi, Alessio Rovere, and Sonia Bejarano. 2022. Assessing the relative accuracy of coral heights reconstructed from drones and structure from motion photogrammetry on coral reefs. Coral Reefs, Vol. 41, 4 (2022), 869--875.Google ScholarGoogle ScholarCross RefCross Ref
  4. Noel Gorelick, Matt Hancher, Mike Dixon, Simon Ilyushchenko, David Thau, and Rebecca Moore. 2017. Google Earth Engine: Planetary-Scale Geospatial Analysis for Everyone. Remote Sensing of Environment , Vol. 202 (2017), 18--27. https://www.sciencedirect.com/science/article/pii/S0034425717302900Google ScholarGoogle ScholarCross RefCross Ref
  5. L. Hellequin, J.-M. Boucher, and X. Lurton. 2003. Processing of high-frequency multibeam echo sounder data for seafloor characterization. IEEE Journal of Oceanic Engineering , Vol. 28, 1 (2003), 78--89. https://doi.org/10.1109/JOE.2002.808205Google ScholarGoogle ScholarCross RefCross Ref
  6. Byeongjin Kim, Hangil Joe, and Son-Cheol Yu. 2021. High-precision underwater 3d mapping using imaging sonar for navigation of autonomous underwater vehicle. International Journal of Control, Automation and Systems, Vol. 19, 9 (2021), 3199--3208.Google ScholarGoogle ScholarCross RefCross Ref
  7. Yang Li, Jiajun Liu, Brano Kusy, Ross Marchant, Brendan Do, Torsten Merz, Joey Crosswell, Andy Steven, Lachlan Tychsen-Smith, David Ahmedt-Aristizabal, Jeremy Oorloff, Peyman Moghadam, Russ Babcock, Megha Malpani, and Ard Oerlemans. 2022. A Real-Time Edge-AI System for Reef Surveys. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking (Sydney, NSW, Australia) (MobiCom '22). Association for Computing Machinery, New York, NY, USA, 903--906. https://doi.org/10.1145/3495243.3558278Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Miquel Massot-Campos and Gabriel Oliver-Codina. 2015. Optical Sensors and Methods for Underwater 3D Reconstruction. Sensors, Vol. 15, 12 (2015), 31525--31557. https://doi.org/10.3390/s151229864Google ScholarGoogle ScholarCross RefCross Ref
  9. Arnadi Murtiyoso and Pierre Grussenmeyer. 2017. Documentation of heritage buildings using close-range UAV images: dense matching issues, comparison and case studies. The Photogrammetric Record , Vol. 32, 159 (2017), 206--229.Google ScholarGoogle ScholarCross RefCross Ref
  10. Oscar Pizarro, Ryan Michael Eustice, and Hanumant Singh. 2009. Large Area 3-D Reconstructions From Underwater Optical Surveys. IEEE Journal of Oceanic Engineering , Vol. 34, 2 (2009), 150--169. https://doi.org/10.1109/JOE.2009.2016071Google ScholarGoogle ScholarCross RefCross Ref
  11. Anne Sedlazeck, Kevin Koser, and Reinhard Koch. 2009. 3D reconstruction based on underwater video from ROV Kiel 6000 considering underwater imaging conditions. In OCEANS 2009-EUROPE. 1--10. https://doi.org/10.1109/OCEANSE.2009.5278305Google ScholarGoogle ScholarCross RefCross Ref
  12. Shimon Ullman. 1979. The interpretation of structure from motion. Proceedings of the Royal Society of London. Series B. Biological Sciences, Vol. 203, 1153 (1979), 405--426. ioGoogle ScholarGoogle Scholar

Index Terms

  1. SkySea: Connecting Satellite, UAV and Underwater Imagery for Benthic Habitat Mapping

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          UAVM '23: Proceedings of the 2023 Workshop on UAVs in Multimedia: Capturing the World from a New Perspective
          November 2023
          86 pages
          ISBN:9798400702860
          DOI:10.1145/3607834

          Copyright © 2023 ACM

          Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 29 October 2023

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • short-paper

          Upcoming Conference

          MM '24
          MM '24: The 32nd ACM International Conference on Multimedia
          October 28 - November 1, 2024
          Melbourne , VIC , Australia
        • Article Metrics

          • Downloads (Last 12 months)67
          • Downloads (Last 6 weeks)15

          Other Metrics

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader