Remote Sensing of Epibenthic Shellfish Using Synthetic Aperture Radar Satellite Imagery

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 potenti...

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Published in:Remote Sensing
Main Authors: Sil Nieuwhof, Peter Herman, Norbert Dankers, Karin Troost, Daphne Van der Wal
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2015
Subjects:
SAR
Online Access:https://doi.org/10.3390/rs70403710
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spelling ftmdpi:oai:mdpi.com:/2072-4292/7/4/3710/ 2023-08-20T04:09:07+02:00 Remote Sensing of Epibenthic Shellfish Using Synthetic Aperture Radar Satellite Imagery Sil Nieuwhof Peter Herman Norbert Dankers Karin Troost Daphne Van der Wal agris 2015-03-27 application/pdf https://doi.org/10.3390/rs70403710 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs70403710 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 7; Issue 4; Pages: 3710-3734 SAR epibenthic shellfish oyster mussel mapping surface roughness Text 2015 ftmdpi https://doi.org/10.3390/rs70403710 2023-07-31T20:42:37Z 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. Text Pacific oyster MDPI Open Access Publishing Pacific Remote Sensing 7 4 3710 3734
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic SAR
epibenthic shellfish
oyster
mussel
mapping
surface roughness
spellingShingle SAR
epibenthic shellfish
oyster
mussel
mapping
surface roughness
Sil Nieuwhof
Peter Herman
Norbert Dankers
Karin Troost
Daphne Van der Wal
Remote Sensing of Epibenthic Shellfish Using Synthetic Aperture Radar Satellite Imagery
topic_facet SAR
epibenthic shellfish
oyster
mussel
mapping
surface roughness
description 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.
format Text
author Sil Nieuwhof
Peter Herman
Norbert Dankers
Karin Troost
Daphne Van der Wal
author_facet Sil Nieuwhof
Peter Herman
Norbert Dankers
Karin Troost
Daphne Van der Wal
author_sort Sil Nieuwhof
title Remote Sensing of Epibenthic Shellfish Using Synthetic Aperture Radar Satellite Imagery
title_short Remote Sensing of Epibenthic Shellfish Using Synthetic Aperture Radar Satellite Imagery
title_full Remote Sensing of Epibenthic Shellfish Using Synthetic Aperture Radar Satellite Imagery
title_fullStr Remote Sensing of Epibenthic Shellfish Using Synthetic Aperture Radar Satellite Imagery
title_full_unstemmed Remote Sensing of Epibenthic Shellfish Using Synthetic Aperture Radar Satellite Imagery
title_sort remote sensing of epibenthic shellfish using synthetic aperture radar satellite imagery
publisher Multidisciplinary Digital Publishing Institute
publishDate 2015
url https://doi.org/10.3390/rs70403710
op_coverage agris
geographic Pacific
geographic_facet Pacific
genre Pacific oyster
genre_facet Pacific oyster
op_source Remote Sensing; Volume 7; Issue 4; Pages: 3710-3734
op_relation https://dx.doi.org/10.3390/rs70403710
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs70403710
container_title Remote Sensing
container_volume 7
container_issue 4
container_start_page 3710
op_container_end_page 3734
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