@mastersthesis {7287, title = {Acoustic Methods for Mapping and Characterizing Submerged Aquatic Vegetation Using a Multibeam Echosounder}, volume = {Earth and Environmental Science}, year = {2019}, month = {December}, pages = {253}, school = {University of New Hampshire}, address = {Durham, NH}, abstract = {

Submerged aquatic vegetation (SAV) is an important component of many temperate global coastal ecosystems. SAV monitoring programs using optical remote sensing are limited by water clarity and attenuation with depth. Here underwater acoustics is used to analyze the water volume above the bottom to detect, map and characterize SAV. In particular, this dissertation developed and applied new methods for analyzing the full time series of acoustic intensity data (e.g., water column data) collected by a multibeam echosounder. This dissertation is composed of three separate but related studies. In the first study, novel methods for detecting and measuring the canopy height of eelgrass beds are developed and used to map eelgrass in a range of different environments throughout the Great Bay Estuary, New Hampshire, and Cape Cod Bay, Massachusetts. The results of this study validated these methods by showing agreement between boundaries of eelgrass beds in acoustic and aerial datasets more in shallow water than at the deeper edges, where the acoustics were able to detect eelgrass more easily and at lower densities. In the second study, the methods developed for measuring canopy height in the first study are used to delineate between kelp-dominated and non-kelp-dominated habitat at several shallow rocky subtidal sites on the Maine and New Hampshire coast. The kelp detection abilities of these methods are first tested and confirmed at a pilot site with detailed diver quadrat macroalgae data, and then these methods are used to successfully extrapolate kelp- and non-kelp-dominated percent coverages derived from video photomosaic data. The third study examines the variability of the acoustic signature and acoustically-derived canopy height under different tidal currents. Submerged aquatic canopies are known to bend to accommodate the drag they generate in response to hydrodynamic forcing, and, in turn, the canopy height measured by acoustics will not be a perfect representation of canopy height as defined by common seagrass monitoring protocols, which is usually measured as the length of the blade of seagrass. Additionally, the bending of the canopy affects how the blades of seagrass are distributed within the footprint of the sonar, changing the acoustic signature of the seagrass canopy. For this study, a multibeam echosounder, a current profiler and an HD video camera were deployed on a stationary frame in a single eelgrass bed over 2 tidal cycles. Acoustic canopy heights varied by as much as 30 cm over the experiment, and although acoustic canopy height was correlated to current magnitude, the relationship did not follow the predictive flexible vegetation reconfiguration model of Luhar and Nepf (2011). Results indicate that there are significant differences in the shape of the return from a deflected (i.e., bent-over) canopy and an upright canopy, and that these differences in shape have implications for the accuracy of bottom detection using the maximum amplitude of a beam time series. These three studies clearly show the potential for using multibeam water column backscatter data for mapping coastal submerged aquatic vegetation while also testing the natural variability in acoustic canopy height measurements in the field.

}, url = {https://scholars.unh.edu/dissertation/2494}, author = {Ashley R Norton} } @article {6192, title = {Comparing Acoustic- and Aerial Imagery-based Methods of Eelgrass Mapping at Two New England Sites}, year = {2017}, month = {November 5-9}, pages = {Providence, RI}, abstract = {

Eelgrass is an important part of many temperate coastal ecosystems and is often used as a bio-indicator for environmental issues such as water quality. Many eelgrass monitoring programs rely on the analysis of optical remote sensing data, including aerial or satellite imagery. However, these methods are often inhibited by natural attenuation of light with water depth and clarity. Acoustic methods have the potential to complement these optical remote sensing-based datasets. The method described here uses water column data from a multi-beam echo-sounder. It can provide geo-referenced acoustic imagery and depth information needed to document the location, structure, and spatial heterogeneity of eelgrass beds, with more spatial coverage than existing acoustic tools that mostly utilize single-beam echo-sounders. Presented here are two acousticallyderived datasets from Wellfleet, Massachusetts, and Kittery, Maine, classified to characterize the presence/absence, percent cover and canopy height of eelgrass. These data are compared to optical-remote-sensing-derived datasets and sidescan sonar imagery using standard accuracy assessment techniques i.e., error matrices. Analysis also includes correlations of classification accuracies with parameters such as water depth, slope and rugosity. Preliminary results indicate that boundaries of eelgrass beds in acoustic and aerial datasets agree more in shallower water than at the deeper edges, and that eelgrass is detected at lower densities in the acoustic data than in the aerial imagery. These differences are due to the differences in horizontal positioning accuracy and resolution and inherent differences in data collection methods (i.e., continuous transects vs. pixel-based imagery).

}, keywords = {eelgrass, habitat mapping, multi-beam sonar, seagrass, water column}, author = {Ashley R Norton and Semme J Dijkstra} } @article {6103, title = {Development of a New Acoustic Mapping Method for Eelgrass Using a Multi-Beam Echo-Sounder}, year = {2017}, month = {May 1-5}, pages = {Halifax, Nova Scotia, Canada}, abstract = {

Eelgrass plays important roles in temperate coastal ecosystems, including as primary producers and as habitat for many species. The distribution and health of eelgrass beds are also sometimes used as a bio-indicator for water quality. The deepest edges of eelgrass beds are especially vulnerable to water quality issues because of the pre-existing light limitation with increasing depth due to natural light attenuation. However, the deep edges of beds are also often the most difficult to delineate with satellite and aerial imagery often used for large-scale seagrass mapping programs; the use of aerial imagery for mapping eelgrass beds is also sometimes hindered by turbidity issues common in estuarine environments. We are in particular developing methods to determine and map the maximum depth limit (\‘deep edge\’), percent cover, functional type (i.e., macroalgae or eelgrass) and canopy height of the beds using water column backscatter data from a multi-beam echo-sounder because these characteristics are difficult to obtain using existing optical and acoustic methods. Water column data was collected using an Odom MB1 sonar in 2014 and 2015 over a variety of vegetated sites in New Hampshire and Massachusetts, selected to represent a range of conditions: dense/sparse eelgrass, long/short eelgrass, mixed macroalgae and eelgrass, eelgrass on muddy or hard substrates, etc. The data processing workflow will look at both echo and terrain characteristics to determine the presence and characteristics of vegetation. In addition to sonar data, drop camera data was collected, and data from a regional aerial mapping program also exist for comparison. Initial data analysis shows good agreement between drop camera and sonar detections, and patches as small as 1m2 and as short as 20 cm are detectable.

}, keywords = {acoustic mapping, eelgrass, multi-beam, multibeam}, author = {Ashley R Norton}, editor = {Semme J Dijkstra} } @article {6173, title = {Three-Dimensional Assessment of Seaweed Habitats Using Remote Sensing}, year = {2017}, month = {November 5-9}, pages = {Providence, RI}, abstract = {

Seafloor mapping at different scales via multibeam echosounder (MBES) has become a prominent tool for characterizing marine habitats. The presence/absence of macroalgae, for example, have been determined using shipboard MBES systems. However, differentiation of macroalgal assemblages through integration of MBES water column data, diver survey, and in-situ video collection has yet to be established. The purpose of this study is to evaluate an integrative approach to assess the distribution and cover of various macroalgal assemblages across seascapes. High frequency water column multibeam data, along with diver and video surveys were collected at 3 sites around the Isles of Shoals and one site in York, ME. Water column data was used to assess canopy heights and were correlated with diver collected canopy heights and in-situ 3D models of macroalgae collected in different morphological seafloor settings. Integration of multiple datasets may provide insights for the detection, differentiation and characterization of macroalgal assemblages at spatial scales greater than that covered using SCUBA.

}, keywords = {benthic habitats, macroalgae, seaweeds}, url = {https://cerf.confex.com/cerf/2017/meetingapp.cgi/Paper/3762}, author = {Jennifer A. Dijkstra and Ashley R Norton and Semme J Dijkstra} } @article {5838, title = {Developments in Eelgrass Mapping Methodology Using Hydrographic Multi-beam Sonar}, year = {2016}, month = {March 30}, address = {EPA District 1 Offices, Boston, MA}, abstract = {

The goal of this work is to develop a data collection and processing methodology for water column backscatter data collected with a multi-beam echo-sounder (Teledyne Odom MB1) to determine the presence or absence, percent cover, maximum depth limit, and canopy height of eelgrass beds. Acoustic eelgrass mapping is of particular use in deep waters and turbid estuaries, where aerial imagery does not reveal the necessary detail for analysis. Presented here are updates to this project, including fieldwork completed in the summer and fall of 2015. The three main updates to the project are: a more comprehensive delineation of the deep edge of eelgrass beds in Portsmouth Harbor; trials of a remotely-operated survey vehicle with the same sensor package used for our boat-based multi-beam surveys over eelgrass beds; and the extension of canopy and bottom picks further out across the swath of the multi-beam.

}, keywords = {eelgrass mapping}, author = {Ashley R Norton and Semme J Dijkstra} } @article {5936, title = {Observations of Acoustic Backscatter and Current Velocity Above an Eelgrass Canopy Over Multiple Tidal Cycles}, year = {2016}, month = {October 20-22}, pages = {Block Island, RI}, abstract = {

Acoustic mapping of eelgrass beds has the potential to document, in three dimensions, the structure of an eelgrass canopy. However, the acoustically-measured height of a submerged canopy can vary by more than 50\% due to plant pronation in response to hydrodynamic forcing. In May of 2016, a multi-beam echosounder, high-resolution current profiler and high-definition video camera were deployed on a custom-built stationary frame above an eelgrass canopy in New Castle, NH. The objectives of the study were (1) to observe how the varying posture of the eelgrass canopy due to currents affects the acoustic backscatter signature and (2) to verify, in the field, a laboratory-tested model by Luhar and Nepf (2011) for deflected canopy height under varying hydrodynamic forcing. Acoustic, current velocity, and video data were collected continuously over several tidal cycles, and plant morphological characteristics (blade length, thickness, width) were sampled periodically during the deployment. Preliminary results indicate that the acoustic signature of a fully-pronated canopy differs significantly from an upright canopy, and that changes in the acoustically-measured canopy heights are correlated to changes in horizontal current velocity. Continuing work will also try to examine the changes in acoustic backscatter intensity from the canopy with changing light levels and time of day. These data offer an interesting snapshot of the daily and weekly variability of parameters that may affect the acoustic signature of an eelgrass canopy.

}, keywords = {Acoustic backscatter, eelgrass, tidal cycles}, author = {Ashley R Norton and Semme J Dijkstra} } @article {5676, title = {Detecting and Characterizing the Deep Edge and Canopy Height of Eelgrass Beds Using a Multi-beam Echosounder}, year = {2015}, month = {November 8-13}, address = {Portland, OR}, abstract = {

Eelgrass plays many important roles in temperate coastal ecosystems, including as habitat for many species, and as a bio-indicator for water quality in many areas. The deepest edges of eelgrass beds are considered more vulnerable to water quality issues because of the pre-existing light limitation with increasing depth due to natural light attenuation. However, the deep edges of beds are also often the most difficult to delineate with satellite and aerial imagery often used for large-scale seagrass mapping programs. We are developing a methodology to characterize the depth limit (\‘deep edge\’), percent cover and canopy height of eelgrass beds at high resolution (~1 m) using water column acoustic backscatter data from a multi-beam echo-sounder.An automated data processing workflow is being developed that will use a combination of digital signal and image-processing techniques, including techniques originally developed for medical ultrasound imagery. These data can provide georeferenced acoustic imagery and depth information needed to document the location, structure, and spatial heterogeneity of eelgrass beds, with more spatial coverage than existing acoustic tools that mostly utilize single-beam echosounders. Water column data were collected over beds at 3 locations in the estuary in the summer of 2014, and preliminary data analysis shows that eelgrass patches as small as 1m2 and as short as 20 cm are detectable. Data was also collected concurrently in the summer of 2015, and they include 1) ground-truth data from drop camera imagery and field surveys; 2) aerial surveys; and 3) acoustic backscatter data.

The ability to process multi-beam water column data for eelgrass characterization may provide a new data source and tool for ecologists and managers interested in eelgrass distribution and characterization, as well as bathymetric information used for charting depths.

}, keywords = {canopy height, eelgrass}, author = {Ashley R Norton and Semme J Dijkstra} } @article {5675, title = {Mapping and Measuring Eelgrass Beds With an MB1 Sonar}, year = {2015}, month = {October 4-7}, address = {San Diego, CA}, abstract = {

Eelgrass plays many important roles in temperate coastal ecosystems, including as habitat for many species, and as a bio-indicator for water quality in many areas. The deepest edges of eelgrass beds are considered more vulnerable to water quality issues because of the pre-existing light limitation with increasing depth due to natural light attenuation. However, the deep edges of beds are also often the most difficult to delineate with satellite and aerial imagery often used for large-scale seagrass mapping programs. We are developing a methodology to characterize eelgrass beds using water column acoustic backscatter data from an MB1 multi-beam echo-sounder. An automated data processing workflow is being developed that will use a combination of digital signal and image-processing techniques, including techniques originally developed for medical ultrasound imagery. These data can provide georeferenced acoustic imagery and depth information needed to document the location, structure, and spatial heterogeneity of eelgrass beds, with more spatial coverage than existing acoustic tools that mostly utilize single-beam echosounders. Water column data were collected over beds at 3 locations in the estuary in the summer of 2014, and preliminary data analysis shows that eelgrass patches as small as 1m2 and as short as 20 cm are detectable. Data was also collected concurrently in the summer of 2015, and they include 1) ground-truth data from drop camera imagery and field surveys; 2) aerial surveys; and 3) acoustic backscatter data. The ability to process multi-beam water column data, including the raw transducer element data, for eelgrass characterization may provide a new data source and tool for ecologists and managers interested in eelgrass distribution and characterization, as well as bathymetric information used for charting depths.

}, author = {Ashley R Norton and Semme J Dijkstra} } @article {5677, title = {Mapping and Measuring Eelgrass with a Multi-beam Sonar in the Great Bay Estuary, New Hampshire}, year = {2015}, month = {March 25}, publisher = {EPA District 1}, address = {Boston, MA}, keywords = {eelgrass, Great Bay}, author = {Ashley R Norton and Semme J Dijkstra} } @mastersthesis {4938, title = {Submerged aquatic vegetation and bedforms in eastern Cape Cod Bay: Spatial distributions, attributes and associations}, year = {2012}, pages = {186}, school = {University of Delaware}, address = {Newark, DE}, author = {Ashley R Norton} } @article {4937, title = {Mapping and quantifying morphological parameters of eelgrass (Zostera marina) beds in eastern Cape Cod Bay, MA using an interferometric sonar system}, year = {2011}, month = {November 6-10}, keywords = {cape cod bay, eelgrass, interferometric sonar}, author = {Ashley R Norton and Brown, M and Arthur Trembanis and Borrelli, M.} }