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Open AccessArticle

Harmonizing Multi-Source Sonar Backscatter Datasets for Seabed Mapping Using Bulk Shift Approaches

1
School of Ocean Technology, Fisheries and Marine Institute of Memorial University of Newfoundland, St. John’s, NL A1C 5R3, Canada
2
Department of Oceanography, Dalhousie University, Halifax, NS B5H 4R2, Canada
3
Institute for Marine and Antarctic Studies, University of Tasmania, Hobart 7053, Australia
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(4), 601; https://doi.org/10.3390/rs12040601
Received: 20 January 2020 / Revised: 7 February 2020 / Accepted: 8 February 2020 / Published: 11 February 2020
(This article belongs to the Section Ocean Remote Sensing)
The development of multibeam echosounders (MBES) as a seabed mapping tool has resulted in the widespread uptake of backscatter intensity as an indicator of seabed substrate properties. Though increasingly common, the lack of standard calibration and the characteristics of individual sonars generally produce backscatter measurements that are relative to a given survey, presenting major challenges for seabed mapping in areas that comprise multiple MBES surveys. Here, we explore methods for backscatter dataset harmonization that leverage areas of mutual overlap between surveys for relative statistical calibration—referred to as “bulk shift” approaches. We use three multispectral MBES datasets to simulate the harmonization of backscatter collected over multiple years, and using multiple operating frequencies. Results suggest that relatively simple statistical models are adequate for bulk shift harmonization procedures, and that more flexible approaches may produce inconsistent results that risk statistical overfitting. While harmonizing datasets collected using the same operating frequency from separate surveys is generally feasible given reasonable temporal limitations, results suggest that the success at harmonizing datasets of different operating frequencies partly depends on the extent to which the frequencies differ. We recommend approaches and diagnostics for ensuring the quality of harmonized backscatter mosaics, and provide an R function for implementing the methods presented here. View Full-Text
Keywords: backscatter; multispectral; multibeam; echosounder; seabed mapping; benthic; habitat mapping backscatter; multispectral; multibeam; echosounder; seabed mapping; benthic; habitat mapping
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MDPI and ACS Style

Misiuk, B.; Brown, C.J.; Robert, K.; Lacharité, M. Harmonizing Multi-Source Sonar Backscatter Datasets for Seabed Mapping Using Bulk Shift Approaches. Remote Sens. 2020, 12, 601.

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