This dataset contains results from an eelgrass classification in Shippagan Harbour, New Brunswick. Derived from a Quickbird satellite image collected on July 27, 2007 at as close to low-tide as possible. Classification was objected-oriented using Definiens software. Data used for accuracy and training was collected along transects using a differential GPS positioned towfish holding sidescan sonar, and a video camera that was later transcribed as XY points to describe eel-grass presence.

Towfish (sidescan and video) and echo sounder surveys were utilized to examine bottom type and macrophyte cover within the area of two coastal marine finfish aquaculture sites, one in New Brunswick (Welch Cove) and one in Nova Scotia (Jordan Bay). Both towfish and echo sounder data could be used independently of one another. However, the towfish data were very useful for ground truthing echo sounder based classifications. All survey data were placed into a GIS which could be used to answer management questions such as the placement of cages at sites, benthic impacts and baseline conditions to determine long term changes.Cite this data as: Vandermeulen H. Data of: Exploratory Video-Sidescan and Echosounder Survey of Welch Cove. Published: June 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/0083e317-8bb5-492a-8348-c021e183f307

Towfish (sidescan and video) and echo sounder surveys were utilized to examine bottom type and macrophyte cover within the area of two coastal marine finfish aquaculture sites, one in New Brunswick (Welch Cove) and one in Nova Scotia (Jordan Bay). Both towfish and echo sounder data could be used independently of one another. However, the towfish data were very useful for ground truthing echo sounder based classifications. All survey data were placed into a GIS which could be used to answer management questions such as the placement of cages at sites, benthic impacts and baseline conditions to determine long term changes.Cite this data as: Vandermeulen H. Data of: Exploratory Video-Sidescan and Echosounder Survey of Jordan Bay. Published: March 2019. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/752d277f-8b3e-40c7-b99d-cfa67e69d975

A novel towfish incorporating sidescan and video hardware was used to ground truth echosounder data for the nearshore of Halifax Harbour. The resulting sampling grid extended from the shoreline to a depth of 10 m, including Bedford Basin through the Inner Harbour to the Outer Harbour. Each of these three zones could be distinguished from the others based upon combinations of substrate type, benthic invertebrates, and macrophyte canopy. Bedford Basin had a relative lack of macrophytes and evidence of intense herbivory. The Inner Harbour was characterized by shoreline hardening due to anthropogenic activities. The Outer Harbour was the most “natural” nearshore area with a mix of bottom types and a relatively abundant and diverse macrophyte canopy. All survey data were placed into a GIS, which could be used to answer management questions such as the placement and character of habitat compensation projects in the harbour. Future surveys utilizing similar techniques could be used to determine long term changes in the nearshore of the harbour.Cite this data as: Vandermeulen H. Data of: A Video, Sidescan and Echosounder Survey of Nearshore Halifax Harbour. Published: September 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/9122c3e2-3cfc-45d0-ac36-aecb306130f6

PURPOSE:To gather localized high-quality data for mapping eelgrass distribution in bays and estuaries in the Gulf Region of Atlantic Canada.DESCRIPTION:Between 2018 and 2023, a total of 48 coastal sites in New Brunswick (NB), Prince Edward Island (PE), and Nova Scotia (NS) have been fully processed for eelgrass presence/absence and depth information.An additional 18 sites from the same region and time period (2018–2023) have data collected but not yet fully processed for depth and eelgrass classification. These sites will be incorporated into the dataset as processing is completed. PARAMETERS COLLECTED:Geographic coordinates, timestamp, submerged aquatic vegetation presence.NOTES ON QUALITY CONTROL:BioSonics Visual Aquatic was used to process raw dt4 files by delineating the bottom and submerged aquatic vegetation (SAV) heights. Initial delineation of the estuary bottom was performed using an automated algorithm within the software, followed by manual adjustments to refine the delineation as needed. An algorithm was then used to delineate vegetation, which was edited visually by referring to written ground-truthing notes and underwater photos taken with a GoPro underwater camera with GPS capacity. Expert advice within DFO was used to advise the analysts on best practices and subtleties in the echograms. All efforts were made to ensure vegetation mapped was eelgrass, but in some cases, such as where the acoustic response was not clear or ground-truthing notes were lacking, it is possible that other types of SAV were included.The processed data were exported from BioSonics Visual Aquatic aggregating sets of 10 pings that were in very close proximity. Grouped pings with a vegetation canopy height >= 0.1 m were assigned an eelgrass presence (i.e., "EG_Presence") value of "Y", while grouped pings with a height < 0.1 m were assigned a presence value of "N".SAMPLING METHODS:Acoustic data were collected during the summer or early fall season (varies depending on the site) by the Southern Gulf of St. Lawrence Coalition on Sustainability (Coalition-SGSL) in partnership with Fisheries and Oceans Canada (DFO) Gulf Region. At some sites, the Province of New Brunswick's Department of Agriculture, Aquaculture and Fisheries (NBDAAF) also collected data using their boat. BioSonics MX Aquatic Habitat Echosounder units with a single beam (8.7°) 204.8kHz transducer (mounting height varied depending on the boat used) was used for data collection by all parties. Positioning was achieved using the BioSonics internal GPS through 2020, then subsequently an external GPS unit (Hemisphere S631 RTK GPS) was used to improve positioning from 1-2m accuracy to ~20cm when differential was obtained. BioSonics Visual Acquisition software was used to collect the data.USE LIMITATION:This product is provided as-is and has not been accuracy-assessed against other data. Since there were no transect-independent ground-truthing points surveyed, the accuracy of any interpolated surfaces created from this data cannot be known.Not for use without inclusion of full metadata. The data products are supplied "as they stand" and DFO does not guarantee the integrity, the completeness, or the accuracy.There were issues with the internal GPS of the BioSonics unit, and their impact on positional accuracy has yet to be determined. Beginning in 2021, an external, higher precision GPS unit was used to increase accuracy.Use of various boats and surveyors, as well as analysts, can introduce some inconsistencies in the data collection and analysis between sites and years. Site-specific characteristics such as mixed submerged aquatic vegetation can complicate mapping efforts. Shallow areas can also be challenging to delineate accurately since the bottom and/or the vegetation can extend higher than the mounted transducer. In these cases, a best estimate was used by the analyst.Weather conditions such as wind can affect the accuracy of the results, as the transponder may pitch and roll with the boat, while increased sediment in the water can interfere with the signal. Single-beam acoustic data has a very small focus footprint, which varies with depth, so it should not be considered a comprehensive bottom mapping tool. However, it does provide valuable point data that can indicate presence of vegetation, canopy height, relative depth, and ground-truthing for other mapping techniques (e.g. aerial or satellite imagery). For example, at 1 m depth, the 8.6 degree single-beam used for this work has a footprint of approximately 0.0177 square metres, and at 2 m depth that footprint becomes 0.0711 square metres.

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 bay-scale assessment of eelgrass beds to sub-meter precision in real time.Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video -Tabusintac 2008. Published: March 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/d1c58bc6-69d4-47b2-bb19-988f88233900

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 bay-scale assessment of eelgrass beds to sub-meter precision in real time.Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Using Sidescan and Video - Cocagne 2008. Published: November 2019. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/431c815e-65f0-477b-9389-060fa41ec955

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 bay-scale assessment of eelgrass beds to sub-meter precision in real time.Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video - Bouctouche. Published: November 2017. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/b4c83cd2-20f2-47d8-8614-08c1c44c9d8c

An eelgrass distribution map was classified from remotely sensed imagery in Richibucto Harbour, New Brunswick. Derived from a Quickbird satellite image collected on August 28th, 2007 at as close to low-tide as possible. Quickbird's ground resolution is 2.4 m. Classification was objected-oriented using Definiens software. Accuracy was 81.5%. Data used for accuracy and training was collected along transects using a differential GPS positioned towfish holding sidescan sonar, and a video camera that was later transcribed as XY points to describe eel-grass presence.

A towfish containing sidescan and video hardware was used to map eelgrass in two shallow northern New Brunswick estuaries. The sidescan and video data were useful in documenting suspected impacts of oyster aquaculture gear and eutrophication on eelgrass. With one boat and a crew of three, the mapping was accomplished at a rate of almost 10 km2 per day. That rate far exceeds what could be accomplished by a SCUBA based survey with the same crew. Moreover, the towfish survey applied with a complementary echosounder survey is potentially a more cost effective mapping method than satellite based remote sensing.Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video - Shippagan 2007. Published: November 2019. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/6454594e-c8f9-41c4-801a-db125b8a8875