Observation data (towed video, BRUVs) collected in Victorian state waters at Pinnacles and Julia Bank.This footage was collected by researchers from Deakin University, Victorian Department of Primary Industries - Marine and Freshwater Resources Institute (MAFRI) and Parks Victoria.The original footage has been converted from various formats including VHS and MiniDV to digital format, with funds supplied by Deakin University Library. Underwater footage gathered from other geographical locations around Victoria from the Victorian Marine Habitat Mapping Program can be accessed via the links featured at the bottom of this record.High quality versions of the videos may be requested via Deakin University Library.

Observation data (towed video, BRUVs) collected in Victorian state waters at Apollo Bay.This footage was collected by researchers from Deakin University, Victorian Department of Primary Industries - Marine and Freshwater Resources Institute (MAFRI) and Parks Victoria.The original footage has been converted from various formats including VHS and MiniDV to digital format, with funds supplied by Deakin University Library. Underwater footage gathered from other geographical locations around Victoria from the Victorian Marine Habitat Mapping Program can be accessed via the links featured at the bottom of this record.High quality versions of the videos may be requested via Deakin University Library.

Observation data (towed video, BRUVs) collected in Victorian state waters at Altona.This footage was collected by researchers from Deakin University, Victorian Department of Primary Industries - Marine and Freshwater Resources Institute (MAFRI) and Parks Victoria.The original footage has been converted from various formats including VHS and MiniDV to digital format, with funds supplied by Deakin University Library. Underwater footage gathered from other geographical locations around Victoria from the Victorian Marine Habitat Mapping Program can be accessed via the links featured at the bottom of this record.High quality versions of the videos may be requested via Deakin University Library.

Observation data (towed video, BRUVs) collected in Victorian state waters at Point Henry, Grand Scenic.This footage was collected by researchers from Deakin University, Victorian Department of Primary Industries - Marine and Freshwater Resources Institute (MAFRI) and Parks Victoria.The original footage has been converted from various formats including VHS and MiniDV to digital format, with funds supplied by Deakin University Library. Underwater footage gathered from other geographical locations around Victoria from the Victorian Marine Habitat Mapping Program can be accessed via the links featured at the bottom of this record.High quality versions of the videos may be requested via Deakin University Library.

Observation data (towed video, BRUVs) collected in Victorian state waters at Port of Melbourne, Vic.This footage was collected by researchers from Deakin University, Victorian Department of Primary Industries - Marine and Freshwater Resources Institute (MAFRI) and Parks Victoria.The original footage has been converted from various formats including VHS and MiniDV to digital format, with funds supplied by Deakin University Library. Underwater footage gathered from other geographical locations around Victoria from the Victorian Marine Habitat Mapping Program can be accessed via the links featured at the bottom of this record.High quality versions of the videos may be requested via Deakin University Library.

This data set contains the raw forward-looking video files obtained by the Ponar Imaging and Sampling System for Assessing Habitat (PISSAH) developed by the Long Island Sound Mapping and Research Collaborative (LISMaRC) to obtain both physical sediment grab samples and ultra-high definition (4K) video using the latest version of GoPro cameras. The videos are in MPEG4 format. A four-day survey using the Ponar Imaging and Sampling System for Assessing Habitat (PISSAH) deployed from the Research Vessel Weicker was conducted from June 12-16, 2023 including mobilization and demobilization. The PISSAH system was used to acquire both physical sediment grab samples as well as the GoPro video from 60 sites in the Phase III area of the Long Island Sound Cable Fund (LISCF) Seafloor Habitat Mapping Initiative. These sites were identified in the Phase IIIA area based upon an analysis of existing acoustic backscatter data obtained from multiple surveys by NOAA that exhibited what appeared to be inconsistent gray scale settings. These two data sources were provided to the team led by Roger Flood from the Stony Brook University to assist with the interpretation of new and existing acoustic backscatter data in the area. Funding was provided by the Long Island Sound Cable Fund Seafloor Habitat Mapping Initiative administered cooperatively by the EPA Long Island Sound Study and the Connecticut Department of Energy and Environmental Protection (DEEP).

This data set provides information on species type, abundance, and distribution, and sediment description for the Phase IIIA survey area of the Long Island Sound Cable Fund (LISCF) Seafloor Habitat Mapping Initiative. This data set contains the results of image analyses of frame captures of video collected by the Ponar Imaging and Sampling System for Assessing Habitat (PISSAH) developed by the Long Island Sound Mapping and Research Collaborative (LISMaRC) to obtain both physical sediment grab samples and ultra-high definition (4K) video using the latest version of GoPro cameras. A four-day survey using the PISSAH deployed from the Research Vessel Weicker was conducted from June 12-16, 2023 including mobilization and demobilization. The PISSAH was used to acquire both physical sediment grab samples as well as the GoPro video from 60 sites in the Phase III area of the Long Island Sound Cable Fund (LISCF) Seafloor Habitat Mapping Initiative. These sites were identified in the Phase IIIA area based upon an analysis of existing acoustic backscatter data obtained from multiple surveys by NOAA that exhibited what appeared to be inconsistent gray scale settings. Multiple GoPro cameras with lights captured both forward-looking and down-looking points of view. The down-looking video files were reviewed and two to five still images (frame grabs) were captured in the .tiff format for image analysis. The images were color corrected using the IrfanView software. Each image was then analyzed using the ImageJ software for point count and percent cover of observed taxa, biogenic features and sediment type. The results of this analysis and attendant maps were provided to the team led by Roger Flood from the Stony Brook University to assist with the interpretation of new and existing acoustic backscatter data in the area. The data file is in ESRI ArcGIS map package (MPK) format. Funding was provided by the Long Island Sound Cable Fund Seafloor Habitat Mapping Initiative administered cooperatively by the EPA Long Island Sound Study and the Connecticut Department of Energy and Environmental Protection (DEEP).

Observation data (towed video, BRUVs) collected in Victorian state waters at Mud Island.This footage was collected by researchers from Deakin University, Victorian Department of Primary Industries - Marine and Freshwater Resources Institute (MAFRI) and Parks Victoria.The original footage has been converted from various formats including VHS and MiniDV to digital format, with funds supplied by Deakin University Library. Underwater footage gathered from other geographical locations around Victoria from the Victorian Marine Habitat Mapping Program can be accessed via the links featured at the bottom of this record.High quality versions of the videos may be requested via Deakin University Library.

Observation data (towed video, BRUVs) collected in Victorian state waters at Point Nepean.This footage was collected by researchers from Deakin University, Victorian Department of Primary Industries - Marine and Freshwater Resources Institute (MAFRI) and Parks Victoria.The original footage has been converted from various formats including VHS and MiniDV to digital format, with funds supplied by Deakin University Library. Underwater footage gathered from other geographical locations around Victoria from the Victorian Marine Habitat Mapping Program can be accessed via the links featured at the bottom of this record.High quality versions of the videos may be requested via Deakin University Library.

This dataset compiles georeferenced media - including videos (480), articles (20), and datasets (6) - specifically curated to facilitate the understanding of reef habitats across northern Australia. It was designed as a research tool for virtual fieldwork with a particular focus on identifying sources of information that allow an understanding of both inshore and offshore reef environments. This dataset provides a record of the literature and media that was reviewed as part of mapping the reef boundaries from remote sensing as part of project NESP MaC 3.17.

This dataset only focuses on media that is useful for understanding shallow reef habitats. It includes videos of snorkelling, diving, spearfishing, and aerial drone imagery. It includes websites, books and journal papers that talk about the structure of reefs and datasets that provide fine scale benthic mapping.

This dataset is likely to not comprehensive. While considerable time was put into collecting relevant media, finding all available information sources is very difficult and time consuming.

A relatively comprehensive search was conducted on: - AIMS Metadata catalogue for benthic habitat mapping with tow videos and BRUVS - A review of the eAtlas for benthic habitat mapping - YouTube searches for video media of fishing, cruises, snorkelling of many named locations. The dataset is far less comprehensive on existing literature from journals, reports and dataset.

As the NESP MaC 3.17 project progresses we will continue to expand the dataset.

Changelog:

Changes made to the dataset will be noted in the change log and indicated in the dataset via the 'Revision' date. 1st Ed. - 2024-04-10 - Initial release of the dataset

Methods:

Identifying media - YouTube videos The initial discovery of videos for a given area was achieved by searching for place names in YouTube search using terms such as diving, snorkeling or spearfishing combined with the location name.

Each potential video was reviewed to:

1. Determine if the video had any visual content that would useful for understanding the marine environment.
2. Determine if the footage could be georeferenced to a specific location, the more specific the better.

In cases where the YouTube channel was making travel videos that were of a high quality, then all the relevant videos in that channel were reviewed. A high proportion of the most useful videos were found using this technique.

The most useful videos were those that had named specific locations (typically in their title or description) and contained drone footage and underwater footage. The drone footage would often show enough of the landscape for features to be matched with satellite imagery allowing precise geolocation of the imagery.

To minimise the time required to find relevant videos, the scrubbing feature on YouTube was used to allow the timeline of the video to be quickly reviewed for relevant scenes. The scrubbing feature shows a very quick, but low resolution version of the video as the cursor is moved along the video timeline. This scrubbing was used to quickly look through the videos for any scenes that contained drone footage, for underwater footage. This was particularly useful for travel videos that contained significant footage of overland travel mixed in with boating or shoreline activities. It was also useful for fishing videos where all the fishing activities could be quickly skipped over to focus on any available drone footage or underwater footage from snorkeling or spearfishing.

Where a video lacked direct clues to the location (such as in the title), but the footage contained particularly relevant and useful footage, additional effort was made listen to the conversations and other footage in the videos for additional clues. This includes people in the video talking about the names of locations, or any marine charts in the footage, or previous and proceeding scenes, where the location could be determined, adding constraints to the location of the relevant scene. Where the footage could not be precisely determine, but the footage was still useful then it was added to a video playlist for the region.

In many remote locations there were so few videos that the bar for including the videos was quite low as these videos would at least provide some general indication of the landscape.

When on PC, Google Maps was used to look up locations and act as reference satellite imagery for locating places, QGIS was used to record the polygons of locations and YouTube in a browser was used for video review.

YouTube Playlists: The initial collection of videos were compiled into YouTube playlists corresponding to relatively large regions. Using playlists was the most convenient way to record useful videos when viewing YouTube from an iPad. This compilation was done prior to the setup of this dataset.

Localising Playlists: For YouTube playlists the region digitised was based on the region represented by the playlist name and the collection of videos. Google maps was used to help determine the locations of each region. Where a particularly useful video is found in one of the playlists and its location can be determined accurately then this video was entered into this database as an individual video with its own finer scale mapping. However this process of migrating the videos from the playlists to more highly georeferenced individual videos in the dataset is incomplete.

The playlists are really a catch-all for potentially useful videos.

Localising individual videos: Candidate videos were quickly assessed for likely usefulness by reviewing the title and quickly scrubbing through the video looking for any marine footage, in water or as drone footage. If a video had a useful section then the focus was to determine the location of that part of the footage as accurately as possible. This was done by searching for locations listed in the title, chapter markers, video description, or mentions in video. These were then looked up in Google Maps. In general we would start with any drone footage that shows a large area with distinct features that could be matched with satellite imagery. The region around named locations were scanned for matching coastline and marine features. Once a match was found then the footage would be reviewed to track the likely area that the video covers in multiple scenes.

The video region was then digitised approximately in QGIS into the AU_AIMS_NESP-3-17_Reef-map-geo-media.shp shapefile. Notes were then added about the important features seen in the footage. A link to the video, including the time code so that it would start at the relevant portion of the video. Long videos showing multiple locations were added as multiple entries, each with a separate polygon location and a different URL link with a different start time.

Articles and Datasets While this dataset primarily focuses on videos, we started adding relevant datasets, websites, articles and reports. These categories of media are not complete in this version of the dataset.

Data dictionary:

RegionName: (String, 255 characters): Name of the location, Examples: 'Oyster Stacks Snorkelling Area', 'Kurrajong Campground', 'South Lefroy Bay' State: (String, 30 characters): Abbreviation of the state that the region corresponds to. For example: 'WA', 'QLD', 'NT'. For locations far offshore link the location to the closest state or to an existing well known region name. For example: Herald Cay -> Coral Sea, Rowley shoals -> WA. MediaType: (String, 20 characters): One of the following: - Video - Video Playlist - Website - Report - EIS - Book - Journal Paper

HabitatRef: (Int): An indication that this resource shows high accuracy spatial habitat information can be used for improving the UQ habitat reference datasets. This attribute should indicate which resources should be reviewed and converted to habitat reference patches. It should be reserved for where a habitat can be located on satellite imagery with sufficient precision that it has high confidence. Media that corresponds to information that is deeper than 15 m is excluded (assigned a HabitatRef of 0) as this is too deep to be used by the UQ habitat mapping. - 1 - Use for habitat reference data. - 0 - Only provides general information about the patch. Imagery can be spatially located accurately or detail is insufficient.

Highlight: (String, 255 characters): This records the classification of reef mapping, or research question that this video is most useful for. Not all videos need this classification. In general this attribute should be reserved for those videos that have the highest level of useful information. Think of it as a shortlist of videos that someone trying to understand a particular aspect of categorising reefs from satellite imagery should review. The following are some of the questions associated with each category that the videos provide some answers. - High tidal range fringing reef: Here we want to understand the structure of fringing reefs in the Kimberleys and Northern Territory where the tides are large and the water is turbid. Is there coral on the tops of the reef flats? Won't the coral dry out if it grows on the reef flat? How will it get enough light if it grows on the reef slope? - Ancient coastline: Along many parts of WA there are shallow rocky reefs off the coast that appear to be acient coastline. What is the nature of these reefs? Does coral or macroalgae grow on them? - Seagrass: What does seagrass look like from satellite imagery - Ningaloo backreef coral: Ningaloo is a very large reef system with a large sandy back. Should the whole back reef be considered coral reef or something else? What are all the dark areas in this back reef area, macroalgae, seagrass, coral? - Macroalgae: What does macroalgae look like from satellite imagery. How can we tell it apart from coral or seagrass? - Deep shoal benthic habitat: There are many deep banks and shoals across north

Observation data (towed video, BRUVs) collected in Victorian state waters at Lewis Channel, Vic.This footage was collected by researchers from Deakin University, Victorian Department of Primary Industries - Marine and Freshwater Resources Institute (MAFRI) and Parks Victoria.The original footage has been converted from various formats including VHS and MiniDV to digital format, with funds supplied by Deakin University Library. Underwater footage gathered from other geographical locations around Victoria from the Victorian Marine Habitat Mapping Program can be accessed via the links featured at the bottom of this record.High quality versions of the videos may be requested via Deakin University Library.

Observation data (towed video, BRUVs) collected in Victorian state waters at Point Addis, Vic.This footage was collected by researchers from Deakin University, Victorian Department of Primary Industries - Marine and Freshwater Resources Institute (MAFRI) and Parks Victoria.The original footage has been converted from various formats including VHS and MiniDV to digital format, with funds supplied by Deakin University Library. Underwater footage gathered from other geographical locations around Victoria from the Victorian Marine Habitat Mapping Program can be accessed via the links featured at the bottom of this record.High quality versions of the videos may be requested via Deakin University Library.

Observation data (towed video, BRUVs) collected in Victorian state waters at Kirk Point.This footage was collected by researchers from Deakin University, Victorian Department of Primary Industries - Marine and Freshwater Resources Institute (MAFRI) and Parks Victoria.The original footage has been converted from various formats including VHS and MiniDV to digital format, with funds supplied by Deakin University Library. Underwater footage gathered from other geographical locations around Victoria from the Victorian Marine Habitat Mapping Program can be accessed via the links featured at the bottom of this record.High quality versions of the videos may be requested via Deakin University Library.

Observation data (towed video, BRUVs) collected in Victorian state waters at Mornington.This footage was collected by researchers from Deakin University, Victorian Department of Primary Industries - Marine and Freshwater Resources Institute (MAFRI) and Parks Victoria.The original footage has been converted from various formats including VHS and MiniDV to digital format, with funds supplied by Deakin University Library. Underwater footage gathered from other geographical locations around Victoria from the Victorian Marine Habitat Mapping Program can be accessed via the links featured at the bottom of this record.High quality versions of the videos may be requested via Deakin University Library.

Abstract: This shapefile provides the location information for the USGS SEABOSS seafloor video surveys in 2017-2018 related to the sediment samples collected with the SEABOSS Van Veen grab sampler device. The Long Island Sound Mapping and Research Collaborative (LISMaRC) is a joint effort of the University of Connecticut, the University of New Haven and the US Geological Survey. Funding provided by the Long Island Sound Seafloor Mapping Fund administered cooperatively by the EPA Long Island Sound Study and the Connecticut Department of Energy and Environmental Protection (DEEP).

Aiming at the problem that it is difficult to accurately calibrate massive Pan-Tilt-Zoom Camera (PTZ) cameras on telecommunication tower and the visualization effect of orthographic geo-image is poor, this paper proposes a new method of realtime orthographic geo-image generating, which is considering Digital Elevation Model (DEM) and semantic information (ROGI-DS). First, through integrating tower cameras with 3D GIS, a camera calibration method based on view fitting (3D GIS-GeoC) is designed. Then, using the trained semantic segmentation model (TCSM), the sky area can automatically be identified and removed. Finally, based on the results of camera calibration and viewshed analysis, and the orthographic geo-image are generated. The results show that: (1) 3D GIS-GeoC method outperforms the traditional Perspective-n-Point (PnP) algorithm;(2) The tower camera semantic segmentation model (TCSM) achieves an accuracy of 96.7%; (3) ROGI-DS method improves the accuracy and visualization of orthographic geo-image under different terrain constraints, and can be used real-time monitoring of natural resources and emergency reliefs.

These seafloor bottom photos were collected as part of the Long Island Sound mapping phase 2 project. During three surveys in 2017 and 2018 aboard the research vessels Pritchard and Seawolf, a GoPro Hero 6 video camera was mounted on the frame of a sediment grab device. The camera was set to record video during the sediment sampling operations. The videos were processed using open-source Shotcut software (www.shotcut.org). The Shotcut video editor was then used to extract frame grab still images after identifying the best image of the seafloor. These still images are in JPEG format. An exiftool script was later used to add the location to each still image file. During the first survey, in 2017, the camera was deployed without external lights and the image was dark below water depths of 8-10m. As result there are some grab stations for which no usable bottom photos exists. For the later surveys, external artificial lights were deployed (Sola video lights, model 3800). These lights allowed video images to be collected in deeper waters. The location of each JPEG image was tagged in the EXIF header with the coordinate information for the corresponding sediment grab station. Location information is based on DGPS navigation using the ship GPS antenna. Lateral offset between the ship GPS antenna and the grab sampling device, and drift of the grab sampling device in the water, have not been corrected. The resulting uncertainty in true position could be on the order of 5-10m. Funding was provided by the Long Island Sound Mapping Fund administered cooperatively by the EPA Long Island Sound Study and the Connecticut Department of Energy and Environmental Protection (DEEP).

These seafloor images were captured as frame grabs from the downward-looking video files obtained by the Ponar Imaging and Sampling System for Assessing Habitat (PISSAH) developed by the Long Island Sound Mapping and Research Collaborative (LISMaRC) to obtain both physical sediment grab samples and ultra-high definition (4K) video using the latest version of GoPro cameras. A four-day survey using the Ponar Imaging and Sampling System for Assessing Habitat (PISSAH) deployed from the Research Vessel Weicker was conducted from June 12-16, 2023 including mobilization and demobilization. The PISSAH system was used to acquire both physical sediment grab samples as well as the GoPro video from 60 sites in the Phase III area of the Long Island Sound Cable Fund (LISCF) Seafloor Habitat Mapping Initiative. These sites were identified in the Phase IIIA area based upon an analysis of existing acoustic backscatter data obtained from multiple surveys by NOAA that exhibited what appeared to be inconsistent gray scale settings. The down-looking video files were reviewed and two to five still images (frame grabs) were captured in the .tiff format for image analysis. The images were color-corrected using the IrfanView software. Images were geolocated using time. Each image was analyzed using the ImageJ software to assess the nature of the seafloor taxa and seafloor sediment type. Image file names included original GoPro video file names and frame time code (i.e., hours, minutes, and seconds since the start of recording). Frames of the seafloor were captured when the seafloor was visible and clear; care was taken to ensure frames provided representative images of the seafloor throughout the transect. At some sites, poor visibility inevitably reduced the number of usable frames available for analysis. Once saved as .TIFF files, frame captures were referred to as images. All .tiff images were then converted to .jpeg files to meet data standardization requirements of the Long Island Sound Cable Fund initiative prior to being sent to the Lamont-Doherty Earth Observatory Long Island Sound data archive. The results of the image analysis were provided to the team led by Roger Flood from the Stony Brook University to assist with the interpretation of new and existing acoustic backscatter data in the area. The images in this data set are in JPEG format. Funding was provided by the Long Island Sound Cable Fund Seafloor Habitat Mapping Initiative administered cooperatively by the EPA Long Island Sound Study and the Connecticut Department of Energy and Environmental Protection (DEEP).

Comparison of camera calibration results and errors.

Abstract: These seafloor videos were acquired with the USGS SEABOSS sled during the 2017-2018 field surveys in eastern Long Island Sound. The SEABOSS sled was towed from R/V Connecticut. The video files are in MPEG4 format. The Long Island Sound Mapping and Research Collaborative (LISMaRC) is a joint effort of the University of Connecticut, the University of New Haven and the US Geological Survey. Funding provided by the Long Island Sound Seafloor Mapping Fund administered cooperatively by the EPA Long Island Sound Study and the Connecticut Department of Energy and Environmental Protection (DEEP).