Using vertical Sidescan Sonar as a tool for seagrass cartography

Sánchez-Carnero, Noela; Rodríguez‐Pérez, Daniel; Couñago, Elena; Aceña, S.; Freire, Juan

doi:10.1016/j.ecss.2012.09.015

Cited by 25 publications

(26 citation statements)

References 41 publications

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“…In deeper waters and/or at large geographic scales, seagrass data may be collected from underwater videos or hyper‐spectral photography (Vandermeulen, ; Schubert et al ., ), side‐scan and multi‐beam sonar data, using scuba divers or boats as working platforms (Sánchez‐Carnero et al , ; Hill et al , ). Autonomous underwater vehicles (AUV) equipped with sonar and hyper‐spectral imagers may be a new and efficient platform for seagrass mapping (Moline et al , ; Wynn et al , ).…”

Section: Discussionmentioning

confidence: 99%

“…Most of the methods mentioned above involve using boats/ships/AUVs entailing relatively high costs and limiting the mapping efforts to open (deeper) waters, possibly avoiding the shallower limits of the meadows being mapped. While mapping seagrasses is non‐trivial, mapping Halophila stipulacea meadows might be particularly challenging, as it is a small‐leaved low‐canopy seagrass species, rendering sonar‐based mapping methods (Komatsu et al , ; Sánchez‐Carnero et al , ) and potentially remote sensing (Uhrin and Townsend, ) impractical. Considerations that were taken into account for mapping of H .…”

Section: Discussionmentioning

confidence: 99%

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A low cost field‐survey method for mapping seagrasses and their potential threats: an example from the northern Gulf of Aqaba, Red Sea

Winters

Edelist

Shem-Tov

et al. 2016

Aquatic Conservation

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1. In the Gulf of Aqaba (GoA), coral reefs are considered the dominating ecosystem, while seagrass meadows, recognized worldwide as important ecosystems, have received little attention. Absence of comprehensive seagrass maps limits awareness, evaluations of associated ecosystem services, and implementation of conservation and management tools.2. Presented here are the first detailed maps of seagrass meadows along the Israeli coast of the northern GoA. Mapping was performed by snorkelling along transects perpendicular to the shore above meadows growing at 15-25 m. Measurements along these transects included position, meadow depth and visual estimations of seagrass cover. Shallow boundaries of meadows, parallel to shore, were recorded by GPS tracking. Supplementary work included drop-camera boat surveys to determine the position of the deeper edge of meadows. In addition, GIS layers were created that indicated shoreline infrastructures, near-shore human activities and potential pollution threats. Ecosystem services of seagrass meadows mapped were valuated using a benefit transfer approach.3. In total, 9.7 km of the 11 km shoreline were surveyed and 2830 data points collected. Seagrasses were growing along 7.5 km of the shoreline, with shallow (15-25 m) meadows found to cover an area of 707 000 m 2 and valued at more than US$ 2 000 000 yr -1 in associated ecosystem services. Pilot drop-camera surveys (additional 283 data points) indicated that meadows can extend down to 50 m in some places. Coastal uses and threats varied in character and location. A municipality runoff point and drainage canal located close to the largest meadow were identified as the main threats to local seagrasses. 4. These low-cost methods enhance our understanding of seagrass distribution in the northern GoA. They demonstrate a GIS-based tool for assessing how environmental changes might affect the cover and state of seagrasses, improving efforts to conserve seagrass, and have particular relevance to seagrass mapping in developing countries and/or island nations.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A low cost field‐survey method for mapping seagrasses and their potential threats: an example from the northern Gulf of Aqaba, Red Sea

Winters

Edelist

Shem-Tov

et al. 2016

Aquatic Conservation

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“…Employment of signal-based methods on SSS data is not investigated widely for seagrass mapping applications (Karpouzli & Malthus, 2007;Sánchez-Carnero et al, 2012). Angular response curves are found to be useful to discriminate different seafloor types (Hughes Clarke, 1994).…”

Section: Data Classification Methodsmentioning

confidence: 99%

A review of seagrass detection, mapping and monitoring applications using acoustic systems

Gümüşay

Bakırman

Kızılkaya

et al. 2018

European Journal of Remote Sensing

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Seagrass meadows are key elements of marine ecosystems as they affect the physical, chemical and biological environment and provide habitats for fish and invertebrates. Human activities have caused a deterioration in seagrass which has led to unstable benthic habitats; therefore, to prevent major decline, seagrass distribution must be mapped and monitored. Acoustic systems allow researchers, scientists and decision makers to collect highresolution datasets such as bathymetry, backscatter and sub-bottom profiles. These systems are able to characterise the properties of the seafloor including plants, sediments and habitats. In this review, we examine seagrass mapping, monitoring and detection applications using acoustic systems in the literature. Although there are various methodologies for data collection, processing, classification and validation, these are limited to certain seagrass species or study areas. Further worldwide research is required to achieve consistent seagrass detection systems with data acquisition, pre-processing, classification and post-processing.

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“…To the author's knowledge, no other researchers have fused video and sidescan hardware into one towfish for shallow water use. In other sidescan surveys of seagrasses, the sidescan portion of the survey was done independently of the ground-truthing portion which was usually more limited in aerial extent (e.g., Mulhearn 2001; Leriche et al 2004Leriche et al , 2006Montefalcone et al 2006;Kiparissis et al 2011;Oakley et al 2012;Sánchez-Carnero et al 2012). Montefalcone et al (2013) particularly stressed the requirement for well-designed and extensive ground truthing for the interpretation of sidescan sonograms from seagrass meadows.…”

Section: Discussionmentioning

confidence: 99%

Bay-scale assessment of eelgrass beds using sidescan and video

Vandermeulen

2014

Helgol Mar Res

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The assessment of the status of eelgrass (Zostera marina) beds at the bay-scale in turbid, shallow estuaries is problematic. The bay-scale assessment (i.e., tens of km) of eelgrass beds usually involves remote sensing methods such as aerial photography or satellite imagery. These methods can fail if the water column is turbid, as is the case for many shallow estuaries on Canada's eastern seaboard. A novel towfish package was developed for the bay-scale assessment of eelgrass beds irrespective of water column turbidity. The towfish consisted of an underwater video camera with scaling lasers, sidescan sonar and a transponder-based positioning system. The towfish was deployed along predetermined transects in three northern New Brunswick estuaries. Maps were created of eelgrass cover and health (epiphyte load) and ancillary bottom features such as benthic algal growth, bacterial mats (Beggiatoa) and oysters. All three estuaries had accumulations of material reminiscent of the oomycete Leptomitus, although it was not positively identified in our study. Tabusintac held the most extensive eelgrass beds of the best health. Cocagne had the lowest scores for eelgrass health, while Bouctouche was slightly better. The towfish method proved to be cost effective and useful for the bayscale assessment of eelgrass beds to sub-meter precision in real time.

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Using vertical Sidescan Sonar as a tool for seagrass cartography

Cited by 25 publications

References 41 publications

A low cost field‐survey method for mapping seagrasses and their potential threats: an example from the northern Gulf of Aqaba, Red Sea

A low cost field‐survey method for mapping seagrasses and their potential threats: an example from the northern Gulf of Aqaba, Red Sea

A review of seagrass detection, mapping and monitoring applications using acoustic systems

Bay-scale assessment of eelgrass beds using sidescan and video

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