Remote sensing of epibenthic shellfish using synthetic aperture radar satellite imagery

22Citations
Citations of this article
32Readers
Mendeley users who have this article in their library.

Abstract

On intertidal mudflats, reef-building shellfish, like the Pacific oyster and the blue mussel, provide a myriad of ecosystem services. Monitoring intertidal shellfish with high spatiotemporal resolution is important for fisheries, coastal management and ecosystem studies. Here, we explore the potential of X- (TerraSAR-X) and C-band (Radarsat-2) dual-polarized SAR data to map shellfish densities, species and coverage. We investigated two backscatter models (the integral equation model (IEM) and Oh's model) for inversion possibilities. Surface roughness (vertical roughness RMSz and correlation length L) was measured of bare sediments and shellfish beds, which was then linked to shellfish density, presence and species. Oysters, mussels and bare sediments differed in RMSz, but because the backscatter saturates at relatively low RMSz values, it was not possible to retrieve shellfish density or species composition from X- and C-band SAR. Using a classification based on univariate and multivariate logistic regression of the field and SAR image data, we constructed maps of shellfish presence (Kappa statistics for calibration 0.56-0.74 for dual-polarized SAR), which were compared with independent field surveys of the contours of the beds (Kappa statistics of agreement 0.29-0.53 when using dual-polarized SAR). We conclude that spaceborne SAR allows one to monitor the contours of shellfish-beds (thus, distinguishing shellfish substrates from bare sediment and dispersed single shellfish), but not densities and species. Although spaceborne SAR cannot replace ground surveys entirely, it could very well offer a significant improvement in efficiency.

Cite

CITATION STYLE

APA

Nieuwhof, S., Herman, P. M. J., Dankers, N., Troost, K., & Van Der Wal, D. (2015). Remote sensing of epibenthic shellfish using synthetic aperture radar satellite imagery. Remote Sensing, 7(4), 3710–3734. https://doi.org/10.3390/rs70403710

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free