Data

Northern Australian Reef Mapping through Georeferenced Media - Virtual Fieldwork Toolkit (NESP MaC 3.17, AIMS)

eAtlas
Lawrey, Eric ; Bycroft, Rachel
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.26274/9wr4-q222&rft.title=Northern Australian Reef Mapping through Georeferenced Media - Virtual Fieldwork Toolkit (NESP MaC 3.17, AIMS)&rft.identifier=10.26274/9wr4-q222&rft.description=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 western Australia that need to be mapped. What is the nature of these reefs, are they mainly soft sediment, do they have coral on them? - Fringing reefs: What is the nature of the fringing reefs across northern Australia? Do they have a high biodiversity or are they just rubble, rock and sediment? URL: (String, 255 characters) Hyperlink to the resource. For YouTube videos this might be to a playlist, an individual video, or to part of a video by starting at a particular time code. Where possible it should be as specific as possible. For PDF documents this links directly to the relevant page. Notes: (String, 255 characters) Description of key useful (for reef mapping) features that this media shows. Author: (String, 100 characters) Name of the YouTube channel or author of the media. This is for attribution purposes. Revision: (String, 12 characters) Date of the version of the dataset when the media was added or changed. The attribute indicates new or changed items in the datasets with each update of the dataset. Format: Shapefile containing polygons with one row per media. 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(2024). Northern Australian Reef Mapping through Georeferenced Media - Virtual Fieldwork Toolkit (NESP MaC 3.17, AIMS) (Version 1) [Data set]. eAtlas. https://doi.org/10.26274/9WR4-Q222&rft_subject=oceans&rft_subject=National Environmental Science Program (NESP) Marine and Coastal Hub&rft_subject=marine&rft_subject=MARINE&rft_subject=Coastal Waters (Australia)&rft_subject=Marine Features (Australia)&rft.type=dataset&rft.language=English Access the data

Licence & Rights:

Open Licence view details
CC-BY

Creative Commons Attribution 3.0 Australia License
http://creativecommons.org/licenses/by/3.0/au/

Cite as: Lawrey, E., & Bycroft, R. (2024). Northern Australian Reef Mapping through Georeferenced Media - Virtual Fieldwork Toolkit (NESP MaC 3.17, AIMS) (Version 1) [Data set]. eAtlas. https://doi.org/10.26274/9WR4-Q222

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Other

Full description

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 western Australia that need to be mapped. What is the nature of these reefs, are they mainly soft sediment, do they have coral on them? - Fringing reefs: What is the nature of the fringing reefs across northern Australia? Do they have a high biodiversity or are they just rubble, rock and sediment? URL: (String, 255 characters) Hyperlink to the resource. For YouTube videos this might be to a playlist, an individual video, or to part of a video by starting at a particular time code. Where possible it should be as specific as possible. For PDF documents this links directly to the relevant page. Notes: (String, 255 characters) Description of key useful (for reef mapping) features that this media shows. Author: (String, 100 characters) Name of the YouTube channel or author of the media. This is for attribution purposes. Revision: (String, 12 characters) Date of the version of the dataset when the media was added or changed. The attribute indicates new or changed items in the datasets with each update of the dataset. Format: Shapefile containing polygons with one row per media. Data Location: This dataset is filed in the eAtlas enduring data repository at: data\custodian\2023-2026-NESP-MaC-3\3.17_Northern-Aus-reef-mapping.

Notes

Credit
Team members: Eric Lawrey (AIMS), Rachel Bycroft (Aerial Architecture)
Credit
National Environmental Science Program (NESP) Marine and Coastal Hub
Credit
Department of Climate Change, Energy, the Environment and Water (DCCEEW), Australian Government
Credit
In addition to NESP (DCCEEW) funding, this project is matched by an equivalent amount of in-kind support and co-investment from project partners and collaborators.
Purpose
This dataset was compiled as virtual field data to assist in the mapping of reefs across northern Australia.

Data time period: 2000-01-01 to 2024-04-01

This dataset is part of a larger collection

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Subjects

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Other Information
Shapefile dataset [400 KB total]

url : https://nextcloud.eatlas.org.au/apps/sharealias/a/AU_AIMS_NESP-3-17_Reef-map-geo-media

View service WMS (nesp-mac-3:AU_AIMS_NESP-3-17_Reef-map-geo-media)

url : https://maps.eatlas.org.au/maps/wms

Interactive map of the dataset

url : https://maps.eatlas.org.au/index.html?intro=false&z=6&ll=128.71350,-17.66010&l0=ea_nesp-mac-3%3AAU_AIMS_NESP-3-17_Reef-map-geo-media,ea_ea-be%3AWorld_Bright-Earth-e-Atlas-basemap,google_HYBRID,google_TERRAIN,google_SATELLITE,google_ROADMAP&o0=,,0.46&v0=,,f,f,f,f

Video Tutorial on georeferencing YouTube videos for virtual field work

url : https://youtu.be/bum7Co38y2w

global : 58f3a091-2463-4963-a908-2a5505e2baf9

ror : 03x57gn41

ror : 03x57gn41

NESP MaC Project 3.17 - Locating Unidentified Reef and Habitat Features in the Northern Australian Seascape, 2023-2025 (AIMS, UQ)

raid : 10.82210/dbdfe884

Identifiers
ACN 633 798 857