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

Abstract

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.

New Feature Classes for Acoustic Habitat Mapping—A Multibeam Echosounder Point Cloud Analysis for Mapping Submerged Aquatic Vegetation (SAV)

“…To the best of our knowledge, there is no marine study yet that uses native PCLs for the investigation SAV or for habitat detection and classification, as presented here. The very recent review study regarding SAV mapping by Gumusay et al [22] lists several devices for seagrass detection and mapping, amongst which are single beam echosounders, acoustic doppler current profilers (ADCP), side scan sonars (SSS), MBES, and even low-cost recreational fishfinder-SSS. However, the authors only describe image-based approaches (SSS-and MBES-BS-mosaics, echograms, and WCI data) and features that are derived from DTMs, but do not mention the use of native MBES generated PCLs.…”

“…Detailed lab studies showed the dedicated backscattering response from the seagrass' tissue in the range of 0.5-2.5 kHz for three different seagrass species [21]. A recent review study by Gumusay et al [22] discusses seagrass detection with various acoustic systems between~1 and 1000 kHz.…”

“…With this in mind, we did not expect a 100% detection rate when conducting the RF test runs. There are also other supervised and unsupervised classification methods, such as k-means, support vector machine, neural networks, and naive bayes [22], which we have not tested here, but may achieve better results.…”

Seagrasses and seagrass habitats in Pacific small island developing states: Potential loss of benefits via human disturbance and climate change

“…Effective methods for mapping coastal habitats exist (e.g. Howard et al, 2014;Roelfsema et al, 2014;Gumusay et al, 2019) however mapping seagrass by remote sensing requires ground truthing and can be difficult because seagrasses are often submerged in turbid water and algal epiphytes may confuse spectral signatures. A knowledge of the extent of natural change is also needed (McKenzie, 2003).…”

Contribution of Remote Sensing Technologies to a Holistic Coastal and Marine Environmental Management Framework: A Review

“…They also provide habitat for other organisms, such as juvenile fish and invertebrates. Numerous studies have documented the advantages of RS technologies for seagrass research: SRS [249,250], ARS [251], UAV [252] to USV, and SS [253]. To assess the state change of seagrasses, [229] presented an overview of the RS platforms that can be used to assess state changes, measure biophysical properties, map, monitor, and model the seagrasses ecosystem, as well as specifying the environmental conditions that do not allow the RS and their approaches to work.…”