Coastal Topo-Bathymetry from a Single-Pass Satellite Video: Insights in Space-Videos for Coastal Monitoring at Duck Beach (NC, USA)
Abstract
:1. Introduction
2. The Satellite Video Acquisition, Pre-Processing and Ground Truth
3. Methods to Compute Topography and Bathymetry
4. Results
4.1. Coastal Topo-Bathymetry Continuum from Satellite Videos
4.2. Temporal Versus Spatial Approaches in Retrieving Wave Kinematics to Inverse Bathymetry from Satellite Videos
5. Recommendations for Future Missions: Designing a Coastal-Oriented Mission
- Swath: In general, the need for high-accuracy DEM is local—a few tens to hundreds of square kilometers, localized at the shoreline in shallow water where the bed evolves rapidly under the action of varying hydrodynamics;
- Resolution: typically, there is no big constraint for the bathymetry retrieval where meters are sufficient but rather for the topography estimation, which directly depends on the pixel resolution;
- Revisit: not necessarily daily to capture the event scale but typically monthly and seasonal evolution, which represents a reasonable target for coastal studies and management;
- Video duration and frame rate: to capture wave kinematics, tens of seconds covering 2–3 waves (with periods ranging from 5 to 25 s typically) are a minimum to reduce the stochastic influence of the wave field in order to accurately inverse bathymetry. A long duration is also important to allow stereo photogrammetry on land (large base-over-height ratio typically −0.1, 0.2 give good results for flat areas, while small base-over-height ratio are better for steep areas), as in coastal zones dunes and beach generally present slopes of 0.01 to 0.1 [67]. The frame rate is important and should remain higher than 1 Hz, staying a small fraction of wave period.
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Laporte, J.; Dolou, H.; Avis, J.; Arino, O. Thirty years of Satellite Derived Bathymetry: The charting tool that Hydrographers can no longer ignore. Int. Hydrogr. Rev. 2020, 25, 129–154. [Google Scholar]
- Wölfl, A.C.; Snaith, H.; Amirebrahimi, S.; Devey, C.W.; Dorschel, B.; Ferrini, V.; Huvenne, V.A.I.; Jakobsson, M.; Jencks, J.; Johnston, G.; et al. Seafloor Mapping—The Challenge of a Truly Global Ocean Bathymetry. Front. Mar. Sci. 2019, 6, 283. [Google Scholar] [CrossRef]
- Cesbron, G.; Melet, A.; Almar, R.; Lifermann, A.; Tullot, D.; Crosnier, L. Pan-European Satellite-Derived Coastal Bathymetry—Review, User Needs and Future Services. Front. Mar. Sci. 2021, 8, 1591. [Google Scholar] [CrossRef]
- Melet, A.; Teatini, P.; Le Cozannet, G.; Jamet, C.; Conversi, A.; Benveniste, J.; Almar, R. Earth observations for monitoring marine coastal hazards and their drivers. Sur. Geophys. 2020, 46, 1489–1534. [Google Scholar] [CrossRef]
- Benveniste, J.; Cazenave, A.; Vignudelli, S.; Fenoglio-Marc, L.; Shah, R.; Almar, R.; Andersen, O.; Birol, F.; Bonnefond, P.; Bouffard, J.; et al. Requirements for a Coastal Hazards Observing System. Front. Mar. Sci. 2019, 6, 348. [Google Scholar] [CrossRef] [Green Version]
- Matheen, N.; Harley, M.D.; Turner, I.L.; Splinter, K.D.; Simmons, J.A.; Thran, M.C. Bathymetric Data Requirements for Operational Coastal Erosion Forecasting Using XBeach. J. Mar. Sci. Eng. 2021, 9, 1053. [Google Scholar] [CrossRef]
- Lange, A.M.; Fiedler, J.W.; Becker, J.M.; Merrifield, M.A.; Guza, R. Estimating runup with limited bathymetry. Coast. Eng. 2022, 172, 104055. [Google Scholar] [CrossRef]
- Cohn, N.; Brodie, K.L.; Johnson, B.; Palmsten, M.L. Hotspot dune erosion on an intermediate beach. Coast. Eng. 2021, 170, 103998. [Google Scholar] [CrossRef]
- Almar, R.; Ranasinghe, R.; Bergsma, E.W.J.; Diaz, H.; Melet, A.; Papa, F.; Vousdoukas, M.; Athanasiou, P.; Dada, O.; Almeida, L.P.; et al. A global analysis of extreme coastal water levels with implications for potential coastal overtopping. Nat. Commun. 2021, 12, 3775. [Google Scholar] [CrossRef]
- Hooijer, A.; Vernimmen, R. Global LiDAR land elevation data reveal greatest sea-level rise vulnerability in the tropics. Nat. Commun. 2021, 12, 3592. [Google Scholar] [CrossRef]
- Bergsma, E.W.; Almar, R.; de Almeida, L.P.M.; Sall, M. On the operational use of UAVs for video-derived bathymetry. Coast. Eng. 2019, 152, 103527. [Google Scholar] [CrossRef]
- Angnuureng, D.B.; Jayson-Quashigah, P.N.; Almar, R.; Stieglitz, T.; Anthony, E.J.; Worlanyo Aheto, D.; Addo, K.A. Remote sensing application of shore-based video and unmanned aerial vehicles (Drones): Complementary tools for beach studies. Remote Sens. 2020, 12, 394. [Google Scholar] [CrossRef] [Green Version]
- Brodie, K.L.; Bruder, B.L.; Slocum, R.K.; Spore, N.J. Simultaneous Mapping of Coastal Topography and Bathymetry From a Lightweight Multicamera UAS. IEEE Trans. Geosci. Remote Sens. 2019, 57, 6844–6864. [Google Scholar] [CrossRef]
- Holman, R.A.; Plant, N.; Holland, T. cBathy: A Robust Algorithm For Estimating Nearshore Bathymetry. J. Geophys. Res. Oceans 2013, 118, 2595–2609. [Google Scholar] [CrossRef]
- Abessolo Ondoa, G.; Bonou, F.; Tomety, F.S.; Du Penhoat, Y.; Perret, C.; Degbe, C.G.E.; Almar, R. Beach Response to Wave Forcing from Event to Inter-Annual Time Scales at Grand Popo, Benin (Gulf of Guinea). Water 2017, 9, 447. [Google Scholar] [CrossRef] [Green Version]
- Holman, R.; Bergsma, E.W.J. Updates to and Performance of the cBathy Algorithm for Estimating Nearshore Bathymetry from Remote Sensing Imagery. Remote Sens. 2021, 13, 3996. [Google Scholar] [CrossRef]
- Le Mauff, B.; Juigner, M.; Ba, A.; Robin, M.; Launeau, P.; FATTAL, P. Coastal monitoring solutions of the geomorphological response of beach dune systemes using multio-temporal LiDAR datasets (Vendée coast, France). Geomorphology 2018, 304, 121–140. [Google Scholar] [CrossRef]
- Louvart, L.; Grateau, C. The Litto3D project. In Proceedings of the Europe Oceans 2005, Brest, France, 20–23 June 2005; Volume 2, pp. 1244–1251. [Google Scholar] [CrossRef]
- Tuell, G.; Barbor, K.; Wozencraft, J. Overview of the coastal zone mapping and imaging lidar (CZMIL): A new multisensor airborne mapping system for the US Army Corps of Engineers. In Proceedings of the Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, SPIE, Orlando, FL, USA, 5–8 April 2010; Volume 7695, pp. 226–233. [Google Scholar]
- Anthony, E.J.; Aagaard, T. The lower shoreface: Morphodynamics and sediment connectivity with the upper shoreface and beach. Earth-Sci. Rev. 2020, 210, 103334. [Google Scholar] [CrossRef]
- Turner, I.L.; Harley, M.D.; Almar, R.; Bergsma, E.W.J. Satellite optical imagery in coastal engineering. Coast. Eng. 2021, 167, 103919. [Google Scholar] [CrossRef]
- Anne, V.; Jan, J.; Antoine, M.; Thomas, J.; François-Régis, M.L. New Perspectives in the Monitoring of Marine Sedimentary Transport by Satellites—Advantage and Research Directions. In Estuaries and Coastal Zones in Times of Global Change; Springer: Berlin, Germany, 2020; pp. 789–808. [Google Scholar]
- Vos, K.; Harley, M.D.; Splinter, K.D.; Simmons, J.A.; Turner, I.L. Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery. Coast. Eng. 2019, 150, 160–174. [Google Scholar] [CrossRef]
- Collin, A.; Hench, J.; Pastol, Y.; Planes, S.; Thiault, L.; Schmitt, R.; Holbrook, S.; Davies, N.; Troyer, M. High resolution topobathymetry using a Pleiades-1 triplet: Moorea Island in 3D. Remote Sens. Environ. 2018, 11, 109–119. [Google Scholar] [CrossRef]
- Almar, R.; Kestenare, E.; Boucharel, J. On the key influence of remote climate variability from Tropical Cyclones, North and South Atlantic mid-latitude storms on the Senegalese coast (West Africa). Environ. Res. Commun. 2019, 1, 071001. [Google Scholar] [CrossRef] [Green Version]
- Almeida, L.P.; Almar, R.; Bergsma, E.W.J.; Berthier, E.; Baptista, P.; Garel, E.; Dada, O.A.; Alves, B. Deriving High Spatial-Resolution Coastal Topography from Sub-meter Satellite Stereo Imagery. Remote Sens. 2019, 11, 590. [Google Scholar] [CrossRef] [Green Version]
- Bergsma, E.W.J.; Almar, R.; Rolland, A.; Binet, R.; Brodie, K.L.; Bak, A.S. Coastal morphology from space: A showcase of monitoring the topography-bathymetry continuum. Remote Sens. Environ. 2021, 261, 112469. [Google Scholar] [CrossRef]
- Tateishi, R.; Akutsu, A. Relative DEM production from SPOT data without GCP. Int. J. Remote Sens. 1992, 13, 2517–2530. [Google Scholar] [CrossRef]
- Taveneau, A.; Almar, R.; Bergsma, E.W.; Sy, B.A.; Ndour, A.; Sadio, M.; Garlan, T. Satellite-Based Beach Topography Evolution: An Application to Monitor Coastal Erosion at Saint Louis on the Langue de Barbarie sand spit (Senegal, West Africa). Remote Sens. 2022, in press. [Google Scholar]
- Salameh, E.; Frappart, F.; Almar, R.; Baptista, P.; Heygster, G.; Lubac, B.; Raucoules, D.; Almeida, L.P.; Bergsma, E.W.J.; Capo, S.; et al. Monitoring Beach Topography and Nearshore Bathymetry Using Spaceborne Remote Sensing: A Review. Remote Sens. 2019, 11, 2212. [Google Scholar] [CrossRef] [Green Version]
- Abileah, R. Mapping shallow water depth from satellite. In Proceedings of the ASPRS Annual Conference, Reno, NV, USA, 1–5 May 2006; pp. 1–7. [Google Scholar]
- Danilo, C.; Binet, R. Bathymetry estimation from wave motion with optical imagery: Influence of acquisition parameters. In Proceedings of the IEEE Transactions on Geoscience and Remote Sensing, Bergen, Norway, 10–14 June 2013; pp. 1–5. [Google Scholar]
- Danilo, C.; Farid, M. Wave period and coastal bathymetry using wave propagation on optical images. IEEE Trans. Geosci. Remote Sens. 2016, 54, 6307–6319. [Google Scholar] [CrossRef]
- Poupardin, A.; Idier, D.; de Michele, M.; Raucoules, D. Water Depth Inversion from a Single SPOT-5 Dataset. IEEE Trans. Geosci. Remote Sens. 2016, 119, 2329–2342. [Google Scholar] [CrossRef] [Green Version]
- Bergsma, E.W.J.; Almar, R.; Maisongrande, P. Radon-Augmented Sentinel-2 Satellite Imagery to Derive Wave-Patterns and Regional Bathymetry. Remote Sens. 2019, 11, 1918. [Google Scholar] [CrossRef] [Green Version]
- Almar, R.; Bergsma, E.W.J.; Maisongrande, P.; de Almeida, L.P.M. Wave-derived coastal bathymetry from satellite video imagery: A showcase with Pleiades persistent mode. Remote Sens. Environ. 2019, 231, 111263. [Google Scholar] [CrossRef]
- Almar, R.; Bergsma, E.W.J.; Thoumyre, G.; Baba, M.W.; Cesbron, G.; Daly, C.; Garlan, T.; Lifermann, A. Global Satellite-Based Coastal Bathymetry from Waves. Remote Sens. 2021, 13, 4628. [Google Scholar] [CrossRef]
- Muis, S.; Apecechea, M.I.; Dullaart, J.; de Lima Rego, J.; Madsen, K.S.; Su, J.; Yan, K.; Verlaan, M. A High-Resolution Global Dataset of Extreme Sea Levels, Tides, and Storm Surges, Including Future Projections. Front. Mar. Sci. 2020, 7, 263. [Google Scholar] [CrossRef]
- Forte, M.F.; Birkemeier, W.A.; Mitchell, J.R. Nearshore Survey System Evaluation; Technical Report; U.S. Army Engineer Research and Development Center ERDC-CHL Vicksburg United States: Vicksburg, MI, USA, 2017. [Google Scholar]
- Shean, D.; Alexandrov, O.; Moratto, Z.; Smith, B.; Joughin, I.; Porter, C.; Morin, P. An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolutioncommercial stereo satellite imagery. ISPRS J. Photogramm. Remote Sens. 2016, 116, 101–117. [Google Scholar] [CrossRef] [Green Version]
- Nuth, C.; Kääb, A. Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change. Cryosphere 2011, 5, 271–290. [Google Scholar] [CrossRef] [Green Version]
- McNabb, R. PyBob: A Python Package of Geospatial Tools; Version 0.25; Github: San Francisco, CA, USA, 2019. [Google Scholar]
- Larson, M.; Kraus, N.C. Temporal and spatial scales of beach profile change, Duck, North Carolina. Mar. Geol. 1994, 117, 75–94. [Google Scholar] [CrossRef]
- Beyer, R.A.; Alexandrov, O.; McMichael, S. The Ames Stereo Pipeline: NASA’s Open Source Software for Deriving and Processing Terrain Data. Earth Space Sci. 2018, 5, 537–548. [Google Scholar] [CrossRef]
- Youssefi, D.; Michel, J.; Sarrazin, E.; Buffe, F.; Cournet, M.; Delvit, J.; L’Helguen, C.; Melet, O.; Emilien, A.; Bosman, O. CARS: A photogrammetry pipeline using Dask graphs to construct a global 3D model. In Proceedings of the IGARSS 2020—2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 26 September–2 October 2020; pp. 453–456. [Google Scholar]
- Michel, J.; Sarrazin, E.; Youssefi, D.; Cournet, M.; Buffe, F.; Delvit, J.; Emilien, A.; Bosman, J.; Melet, O.; L’Helguen, C. A new satellite imagery stereo pipeline designed for scalability, robustness and performance. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2020, 2, 171–178. [Google Scholar] [CrossRef]
- Almar, R.; Michallet, H.; Cienfuegos, R.; Bonneton, P.; Tissier, M.; Ruessing, G. On the use of the Radon Transform in studying nearshore wave dynamics. Coast. Eng. 2014, 92, 24–30. [Google Scholar] [CrossRef]
- Almar, R.; Bergsma, E.W.J.; Gawehn, M.A.; Aarninkhof, S.G.J.; Benshila, R. High-frequency temporal wave-pattern reconstruction from a few satellite images: A new method towards estimating regional bathymetry. J. Coast. Res. 2020, 95, 996–1000. [Google Scholar] [CrossRef]
- Yamazaki, D.; Ikeshima, D.; Tawatari, R.; Yamaguchi, T.; O’Loughlin, F.; Neal, J.C.; Sampson, C.C.; Kanae, S.; Bates, P.D. A high-accuracy map of global terrain elevations. Geophys. Res. Lett. 2017, 44, 5844–5853. [Google Scholar] [CrossRef] [Green Version]
- Magruder, L.; Neuenschwander, A.; Klotz, B. Digital terrain model elevation corrections using space-based imagery and ICESat-2 laser altimetry. Remote Sens. Environ. 2021, 264, 112621. [Google Scholar] [CrossRef]
- Holman, R.A.; Brodie, K.L.; Spore, N.J. Surf Zone Characterization Using a Small Quadcopter: Technical Issues and Procedures. IEEE Trans. Geosci. Remote Sens. 2017, 55, 2017–2027. [Google Scholar] [CrossRef]
- Bergsma, E.W.J.; Conley, D.C.; Davidson, M.A.; O’Hare, T.J.; Almar, R. Storm Event to Seasonal Evolution of Nearshore Bathymetry Derived from Shore-Based Video Imagery. Remote Sens. 2019, 11, 519. [Google Scholar] [CrossRef] [Green Version]
- Almar, R.; Cienfuegos, R.; Catalán, P.A.; Birrien, F.; Castelle, B.; Michallet, H. Nearshore bathymetric inversion from video using a fully non-linear Boussinesq wave model. In Proceedings of the 11th International Coastal Symposium, Szczecin, Poland, 9–14 May 2011. [Google Scholar]
- Bergsma, E.W.J.; Almar, R. Video-based depth inversion techniques, a method comparison with synthetic cases. Coast. Eng. 2018, 138, 199–209. [Google Scholar] [CrossRef]
- Gawehn, M.; de Vries, S.; Aarninkhof, S. A Self-Adaptive Method for Mapping Coastal Bathymetry On-The-Fly from Wave Field Video. Remote Sens. 2021, 13, 4742. [Google Scholar] [CrossRef]
- Almar, R.; Bonneton, P.; Senechal, N.; Roelvink, D. Wave Celerity From Video Imaging: A new method. In Proceedings of the 31st International Conference Coastal Engineering, Hamburg, Germany, 31 August–5 September 2008; pp. 1–14. [Google Scholar]
- Stumpf, R.P.; Holderied, K.; Sinclair, M. Determination of water depth with high-resolution satellite imagery over variable bottom types. Limnol. Oceanogr. 2003, 48, 547–556. [Google Scholar] [CrossRef]
- Lyzenga, D.R.; Malinas, N.P.; Tanis, F.J. Multispectral bathymetry using a simple physically based algorithm. IEEE Trans. Geosci. Remote Sens. 2006, 44, 2251–2259. [Google Scholar] [CrossRef]
- Lee, Z.; Hu, C.; Casey, B.; Shang, S.; Dierssen, H.; Arnone, R. Global Shallow-Water from Satellite Ocean Color Data. Eos 2010, 91, 429–430. [Google Scholar] [CrossRef] [Green Version]
- Hodúl, M.; Bird, S.; Knudby, A.; Chénier, R. Satellite derived photogrammetric bathymetry. ISPRS J. Photogramm. Remote Sens. 2018, 142, 268–277. [Google Scholar] [CrossRef]
- Caballero, I.; Stumpf, R.P. Retrieval of nearshore bathymetry from Sentinel-2A and 2B satellites in South Florida coastal waters. Estuarine Coast. Shelf Sci. 2019, 226, 106277. [Google Scholar] [CrossRef]
- Li, J.; Knapp, D.E.; Lyons, M.; Roelfsema, C.; Phinn, S.; Schill, S.R.; Asner, G.P. Automated Global Shallow Water Bathymetry Mapping Using Google Earth Engine. Remote Sens. 2021, 13, 1469. [Google Scholar] [CrossRef]
- Bergsma, E.W.J.; Almar, R. Coastal coverage of ESA’ Sentinel 2 mission. Adv. Space Res. 2020, 65, 2636–2644. [Google Scholar] [CrossRef]
- Karunarathna, H.; Horrillo-Caraballo, J.; Kuriyama, Y.; Mase, H.; Ranasinghe, R.; Reeve, D.E. Linkages between sediment composition, wave climate and beach profile variability at multiple timescales. Mar. Geol. 2016, 381, 194–208. [Google Scholar] [CrossRef] [Green Version]
- Thuan, D.H.; Almar, R.; Marchesiello, P.; Viet, N.T. Video sensing of nearshore bathymetry evolution with error estimate. J. Mar. Sci. Eng. 2019, 7, 233. [Google Scholar] [CrossRef] [Green Version]
- Mayer, L.; Jakobsson, M.; Allen, G.; Dorschel, B.; Falconer, R.; Ferrini, V.; Lamarche, G.; Snaith, H.; Weatherall, P. The Nippon Foundation—GEBCO Seabed 2030 Project: The Quest to See the World’s Oceans Completely Mapped by 2030. Geosciences 2018, 8, 63. [Google Scholar] [CrossRef] [Green Version]
- Komar, P. Beach Processes and Sedimentation, 2nd ed.; Prentice-Hall: Upper Saddle River, NJ, USA, 1998. [Google Scholar]
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Almar, R.; Bergsma, E.W.J.; Brodie, K.L.; Bak, A.S.; Artigues, S.; Lemai-Chenevier, S.; Cesbron, G.; Delvit, J.-M. Coastal Topo-Bathymetry from a Single-Pass Satellite Video: Insights in Space-Videos for Coastal Monitoring at Duck Beach (NC, USA). Remote Sens. 2022, 14, 1529. https://doi.org/10.3390/rs14071529
Almar R, Bergsma EWJ, Brodie KL, Bak AS, Artigues S, Lemai-Chenevier S, Cesbron G, Delvit J-M. Coastal Topo-Bathymetry from a Single-Pass Satellite Video: Insights in Space-Videos for Coastal Monitoring at Duck Beach (NC, USA). Remote Sensing. 2022; 14(7):1529. https://doi.org/10.3390/rs14071529
Chicago/Turabian StyleAlmar, Rafael, Erwin W. J. Bergsma, Katherine L. Brodie, Andrew Spicer Bak, Stephanie Artigues, Solange Lemai-Chenevier, Guillaume Cesbron, and Jean-Marc Delvit. 2022. "Coastal Topo-Bathymetry from a Single-Pass Satellite Video: Insights in Space-Videos for Coastal Monitoring at Duck Beach (NC, USA)" Remote Sensing 14, no. 7: 1529. https://doi.org/10.3390/rs14071529
APA StyleAlmar, R., Bergsma, E. W. J., Brodie, K. L., Bak, A. S., Artigues, S., Lemai-Chenevier, S., Cesbron, G., & Delvit, J. -M. (2022). Coastal Topo-Bathymetry from a Single-Pass Satellite Video: Insights in Space-Videos for Coastal Monitoring at Duck Beach (NC, USA). Remote Sensing, 14(7), 1529. https://doi.org/10.3390/rs14071529