Mapping 3D structure of a<i>Sargassum</i>forest with high-resolution sounding data obtained by multibeam echosounder

Hamana, Masahiro; Komatsu, Toshimitsu

doi:10.1093/icesjms/fsab044

Cited by 3 publications

(3 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To our knowledge, no studies have used multi-detect data for actual habitat mapping, although Schneider von Deimling et al (2007) used it for gas flaring detection. Hamana and Komatsu (2021) and Held and Schneider von Deimling (2019) used misclassifications of the bottom detection algorithm to identify benthic habitats in point cloud data (brown algae and seagrass, respectively). The target habitat of this study, the black coral forests formed by Anthipatella wollastoni (Gray, 1857) off the coast of Lanzarote, Spain, appears geometrically similar to a vegetated seabed, with corals protruding from the seabed a few decimetres into the water column (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

Can black coral forests be detected using multibeam echosounder “multi-detect” data?

Feldens

Held²,

Otero‐Ferrer³

et al. 2023

Front. Remote Sens.

View full text Add to dashboard Cite

The black coral Anthipatella wollastoni forms marine animal forests in the mesophotic zone. The spatial extent of black coral forests is not well known in many regions. Due to its protein and chitin skeleton, the coral is difficult to image using acoustic remote sensing techniques compared to corals with carbonate skeletons. Several manufacturers have recently introduced an additional data type to their multibeam echosounders, called “multi-detection,” which provides additional target detections per beam in addition to the primary bottom detection. In this study, we used a Norbit chirp multibeam echosounder in multi-detect mode to acquire up to three targets in each beam in an area of black coral below 45 m depth off the coast of Lanzarote (Canary Islands, Spain). Multi-detect allows features above and below the primary bottom detection to be identified without the need to store and process water-column data. Black coral can be detected by comparing “multi-detection” data with ground truthing by technical divers and underwater cameras. However, the repeatability of the detections is limited and further sensitivity studies are required.

show abstract

Section: Introductionmentioning

confidence: 99%

Can black coral forests be detected using multibeam echosounder “multi-detect” data?

Feldens

Held²,

Otero‐Ferrer³

et al. 2023

Front. Remote Sens.

View full text Add to dashboard Cite

show abstract

“…Controversially, the Acoustic method hardly to be affected by water turbidity, and it is possible to detect the target from a faraway area. There are previous studies that suggest a method to survey Sargassum distribution by Quantitative Echo Sounder (QES) (Minami et al 2012) and Multi Beam Echo Sounder (MBES) (Hamana and Komatsu, 2021). QES transmits the pulse downward and detects the target just below the sonar and cannot survey areas outside of the ship track.…”

Section: Introductionmentioning

confidence: 99%

Mapping of Sargassum meadow for estimation biomass by side scan sonar

Okawa

Hayashizaki

2023

Preprint

View full text Add to dashboard Cite

Sargassum meadows play important roles in coastal ecosystems, CO2 fixing, and others. Estimation of their biomass helps conservation of meadows and estimation of the amount of fixed CO2 for blue carbon projects. Most sonars are inefficient in shallow waters because their swaths are limited by water depth. Side scan sonar (SSS) creates a detailed image of the bottom efficiently, even in shallow waters transmitting wide beams. We towed SSS from the ship’s side and scanned the meadow of Sargassum horneri at a small beach in Otsuchi Bay on the Sanriku Coast of Japan during the growing season of 2022. For the truthing, we surveyed with the underwater camera and Single beam echo sounder (SBES) to compare with SSS data. SSS scanned the sea floor of the beach to detect seaweed echoes. The beach consists of a sandy area and a rocky shore. The seaweeds were discriminated from the sand and rocks by their acoustic shadows, and we pinpointed their locations, although the background reflectance strength and pattern were different between the two areas. To estimate the canopy heights, we measured the acoustic shadow lengths of the seaweeds. However, the shadows of the seaweeds, which are located very near to the sonar, are too short to measure. Therefore, we developed a new method to measure their heights from acoustic reflections instead. Our study demonstrated the effectiveness of side scan sonar for mapping Sargassum meadows in shallow waters and estimating their canopy heights with a novel method, which leads to precise biomass estimation.

show abstract

“…The validation experiment of their system for plant growth monitoring will be performed in the future. Hamana et al [17] demonstrated that a multibeam echosounder can be used to map the 3D structure of a seaweed forest (both canopy height and inter-individual distances of the plants were measured).…”

Section: Introductionmentioning

confidence: 99%

Seaweed Growth Monitoring with a Low-Cost Vision-Based System

Gerlo,

Kooijman,

Wieling

et al. 2023

Sensors

View full text Add to dashboard Cite

In this paper, we introduce a method for automated seaweed growth monitoring by combining a low-cost RGB and stereo vision camera. While current vision-based seaweed growth monitoring techniques focus on laboratory measurements or above-ground seaweed, we investigate the feasibility of the underwater imaging of a vertical seaweed farm. We use deep learning-based image segmentation (DeeplabV3+) to determine the size of the seaweed in pixels from recorded RGB images. We convert this pixel size to meters squared by using the distance information from the stereo camera. We demonstrate the performance of our monitoring system using measurements in a seaweed farm in the River Scheldt estuary (in The Netherlands). Notwithstanding the poor visibility of the seaweed in the images, we are able to segment the seaweed with an intersection of the union (IoU) of 0.9, and we reach a repeatability of 6% and a precision of the seaweed size of 18%.

show abstract

Mapping 3D structure of aSargassumforest with high-resolution sounding data obtained by multibeam echosounder

Cited by 3 publications

References 30 publications

Can black coral forests be detected using multibeam echosounder “multi-detect” data?

Can black coral forests be detected using multibeam echosounder “multi-detect” data?

Mapping of Sargassum meadow for estimation biomass by side scan sonar

Seaweed Growth Monitoring with a Low-Cost Vision-Based System

Contact Info

Product

Resources

About