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.
- Matthias Adorjan. 2016. OpenSfM: A Collaborative Structure-From-Motion System. Ph.,D. Dissertation. Wien.Google Scholar
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 ScholarDigital Library
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 Scholar
Index Terms
- SkySea: Connecting Satellite, UAV and Underwater Imagery for Benthic Habitat Mapping
Recommendations
Optical delineation of benthic habitat using an autonomous underwater vehicle: Field Reports
Special Issue on Underwater RoboticsTo better characterize and improve our understanding of coastal waters, there has been an increasing emphasis on autonomous systems that can sample the ocean on relevant scales. Autonomous underwater vehicles (AUVs) with active propulsion are especially ...
Quantitative mapping of pasture biomass using satellite imagery
A knowledge of the amount of pasture biomass available in farm paddocks is crucial for improving utilization and productivity in the Australian grazing industry. A method to quantitatively map the biomass of annual pastures under grazing has been ...
Whale shark habitat assessments in the northeastern Arabian Sea using satellite remote sensing
One of the major requirements for the growing whale shark tourism industry is to identify potential areas of their aggregation for sighting. This would require baseline information on the occurrence of whale shark and the associated environment. In this ...
Comments