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 - Richibucto 2007. Published: October 2017. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ca7af8ba-8810-4de5-aa91-473613b0b38d

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 -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 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

This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2014 (USGS Field Activity Number D-01-14-PS). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. Positioning of the survey vessel was determined at 0.5 Hz intervals using a Garmin 76c GNSS receiver. The positioning data from the GNSS were encoded onto the audio track of the digital video recording using Red Hen Systems (RHS) VMS200 hardware. Underwater video data were recorded as the vessel navigated along a series of shore-perpendicular transects at speeds between 1 and 2 knots. The underwater video recording was later reviewed and the presence or absence of eelgrass was determined for each 2-s segment of video tape. These data were used to evaluate the classification of single-beam sonar data acquired during the same time period.

This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2014 (USGS Field Activity Number D-01-14-PS). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. Positioning of the survey vessel was determined at 0.5 Hz intervals using a Garmin 76c GNSS receiver. The positioning data from the GNSS were encoded onto the audio track of the digital video recording using Red Hen Systems (RHS) VMS200 hardware. Underwater video data were recorded as the vessel navigated along a series of shore-perpendicular transects at speeds between 1 and 2 knots. The underwater video recording was later reviewed and the presence or absence of eelgrass was determined for each 2-s segment of video tape. These data were used to evaluate the classification of single-beam sonar data acquired during the same time period.

This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2017 (USGS Field Activity Number 2017-614-FA). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. Positioning of the survey vessel was determined at 1 Hz intervals using a Trimble R7 GNSS receiver and Trimble Zephyr Model 2 antenna. The positioning data from the GNSS were encoded onto the audio track of the digital video recording using Red Hen Systems (RHS) VMS200 hardware. Underwater video data were recorded as the vessel navigated along a series of shore-perpendicular transects at speeds between 1 and 2 knots. The underwater video recording was later reviewed and the presence or absence of eelgrass was determined for each 1-s segment of video tape. These data were used to evaluate the classification of single-beam sonar data acquired during the same time period.

This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2012 (USGS Field Activity Number D-01-12-PS). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. Positioning of the survey vessel was determined at 1 Hz intervals using a Trimble R7 GNSS receiver and Trimble Zephyr Model 2 antenna. The positioning data from the GNSS were encoded onto the audio track of the digital video recording using Red Hen Systems (RHS) VMS200 hardware. Underwater video data were recorded as the vessel navigated along a series of shore-perpendicular transects at speeds between 1 and 2 knots. The underwater video recording was later reviewed and the presence or absence of eelgrass was determined for each 1-s segment of video tape. These data were used to evaluate the classification of single-beam sonar data acquired during the same time period.

This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2017 (USGS Field Activity Number 2017-614-FA). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. Positioning of the survey vessel was determined at 1 Hz intervals using a Trimble R7 GNSS receiver and Trimble Zephyr Model 2 antenna. The positioning data from the GNSS were encoded onto the audio track of the digital video recording using Red Hen Systems (RHS) VMS200 hardware. Underwater video data were recorded as the vessel navigated along a series of shore-perpendicular transects at speeds between 1 and 2 knots. The underwater video recording was later reviewed and the presence or absence of eelgrass was determined for each 1-s segment of video tape. These data were used to evaluate the classification of single-beam sonar data acquired during the same time period.