Airborne Drones for Water Quality Mapping in Inland, Transitional and Coastal Waters—MapEO Water Data Processing and Validation
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Published:2023-02-28
Issue:5
Volume:15
Page:1345
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ISSN:2072-4292
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Container-title:Remote Sensing
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language:en
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Short-container-title:Remote Sensing
Author:
De Keukelaere Liesbeth1ORCID, Moelans Robrecht1ORCID, Knaeps Els1ORCID, Sterckx Sindy1ORCID, Reusen Ils1ORCID, De Munck Dominique1, Simis Stefan G.H.2ORCID, Constantinescu Adriana Maria3, Scrieciu Albert3ORCID, Katsouras Georgios4ORCID, Mertens Wim5, Hunter Peter D.6, Spyrakos Evangelos6ORCID, Tyler Andrew6
Affiliation:
1. Vlaamse Instelling Voor Technologisch Onderzoek (VITO), Boeretang 200, 2400 Mol, Belgium 2. Plymouth Marine Laboratory (PML), Plymouth PL1 3DH, UK 3. Institutul National De Cercetare—Dezvoltare Pentru Geologie Si Geoecologie Marina (GeoEcoMar), 23–25 Dimitrie Onciul St., RO-024053 Bucharest, Romania 4. Athens Water Suppy and Sewerage Company (EYDAP S.a.), Oropou 156, 11146 Athens, Greece 5. Instituut Natuur-En Bosonderzoek (INBO) Havenlaan 88 Bus 73, 1000 Brussel, Belgium 6. Earth and Planetary Observation Sciences (EPOS), Biological and Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling FK9 4LA, UK
Abstract
Using airborne drones to monitor water quality in inland, transitional or coastal surface waters is an emerging research field. Airborne drones can fly under clouds at preferred times, capturing data at cm resolution, filling a significant gap between existing in situ, airborne and satellite remote sensing capabilities. Suitable drones and lightweight cameras are readily available on the market, whereas deriving water quality products from the captured image is not straightforward; vignetting effects, georeferencing, the dynamic nature and high light absorption efficiency of water, sun glint and sky glint effects require careful data processing. This paper presents the data processing workflow behind MapEO water, an end-to-end cloud-based solution that deals with the complexities of observing water surfaces and retrieves water-leaving reflectance and water quality products like turbidity and chlorophyll-a (Chl-a) concentration. MapEO water supports common camera types and performs a geometric and radiometric correction and subsequent conversion to reflectance and water quality products. This study shows validation results of water-leaving reflectance, turbidity and Chl-a maps derived using DJI Phantom 4 pro and MicaSense cameras for several lakes across Europe. Coefficients of determination values of 0.71 and 0.93 are obtained for turbidity and Chl-a, respectively. We conclude that airborne drone data has major potential to be embedded in operational monitoring programmes and can form useful links between satellite and in situ observations.
Funder
European Union’s Horizon 2020 research and innovation programme Belgian Science Policy
Subject
General Earth and Planetary Sciences
Reference41 articles.
1. Koparan, C., Koc, A.B., Privette, C.V., and Sawyer, C.B. (2018). In Situ Water Quality Measurements Using an Unmanned Aerial Vehicle (UAV) System. Water, 10. 2. Rodrigues, P., Marques, F., Pinto, E., Pombeiro, R., Lourenço, A., Mendonça, R., Santana, P., and Barata, J. (2015, January 19–22). An open-source watertight unmanned aerial vehicle for water quality monitoring. Proceedings of the Conference OCEANS 2015—MTS/IEEE, Washington, DC, USA. 3. UAS-based real-time water quality monitoring, sampling, and visualization platform (UASWQP);Ryu;HardwareX,2022 4. El Serafy, G., Schaeffer, B., Neely, M.-B., Spinosa, A., Odermatt, D., Weathers, K., Baracchini, T., Bouffard, D., Carvalho, L., and Conmy, R. (2021). Integrating Inland and Coastal Water Quality Data for Actionable Knowledge. Remote. Sens., 13. 5. Sibanda, M., Mutanga, O., Chimonyo, V.G.P., Clulow, A.D., Shoko, C., Mazvimavi, D., Dube, T., and Mabhaudhi, T. (2021). Application of Drone Technologies in Surface Water Resources Monitoring and Assessment: A Systematic Review of Progress, Challenges, and Opportunities in the Global South. Drones, 5.
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