From 1 - 9 / 9
  • Categories  

    Data from multibeam echosounder surveys taken as part of the Ningaloo Outlook project are classified into various seafloor cover types according to their hardness, rugosity and depth. The classifications are validated with towed video ground truth where it is available. Three AOIs are classified, two that were explicitly part of the Ningaloo Outlook Deep Reefs project and a third transect that was acquired incidentally while RV Investigator was transiting between locations. Due to the nature of the acquired data, two different approaches were taken for the classification, the first approach used multibeam backscatter angular response curves along with rugosity as input to a maximum likelihood classifier. The second approach used flattened multibeam backscatter (i.e. with the angular effects removed), along with rugosity as inputs to a Random Forest Classifier. Estimates of the accuracy of the classifiers are produced, where possible, along with area statistics for the different substratum observed in the classified maps. The maps are GeoTIFFs with text based classification keys. [Note:] Area 3a only

  • Categories  

    Data from multibeam echosounder surveys taken as part of the Ningaloo Outlook project are classified into various seafloor cover types according to their hardness, rugosity and depth. The classifications are validated with towed video ground truth where it is available. Three AOIs are classified, two that were explicitly part of the Ningaloo Outlook Deep Reefs project and a third transect that was acquired incidentally while RV Investigator was transiting between locations. Due to the nature of the acquired data, two different approaches were taken for the classification, the first approach used multibeam backscatter angular response curves along with rugosity as input to a maximum likelihood classifier. The second approach used flattened multibeam backscatter (i.e. with the angular effects removed), along with rugosity as inputs to a Random Forest Classifier. Estimates of the accuracy of the classifiers are produced, where possible, along with area statistics for the different substratum observed in the classified maps. The maps are GeoTIFFs with text based classification keys. [Note:] 120m Transect only

  • Categories  

    Data from multibeam echosounder surveys taken as part of the Ningaloo Outlook project are classified into various seafloor cover types according to their hardness, rugosity and depth. The classifications are validated with towed video ground truth where it is available. Three AOIs are classified, two that were explicitly part of the Ningaloo Outlook Deep Reefs project and a third transect that was acquired incidentally while RV Investigator was transiting between locations. Due to the nature of the acquired data, two different approaches were taken for the classification, the first approach used multibeam backscatter angular response curves along with rugosity as input to a maximum likelihood classifier. The second approach used flattened multibeam backscatter (i.e. with the angular effects removed), along with rugosity as inputs to a Random Forest Classifier. Estimates of the accuracy of the classifiers are produced, where possible, along with area statistics for the different substratum observed in the classified maps. The maps are GeoTIFFs with text based classification keys. [Note:] Area 5 only

  • Categories  

    Name, Brief Description and owner: Baited Remote Underwater stereo-Video (BRUV) systems (6 in total) were used. All equipment (BRUVs, weights, cameras, lights, ropes, etc.) belonged to UWA Relevant component details: make, model, serial number, firmware version, settings: Stereo‐BRUV systems consisted of a frame, protecting 2 convergent video cameras inside waterproof housings (plus one rear-facing video camera) and 2 lights (one forward-facing and one rear-facing), attached to a base bar, with a baited container fixed in front of the cameras. Systems were tethered by rope to surface buoys to facilitate relocation and retrieval. Weights were added to frames due to the current and depth in the area. Cameras used: 2 x Canon HG 25 (forward facing) with the follow settings: • Focus: Manual (3.0m) • Rec Program: P) • Image stabilizer: OFF • Facial recognition: OFF • Recording mode: MXP • Frame rate: PF25 1 x GoPro Hero 3+ (backwards facing), taking photos every 60 seconds. Cameras were calibrated at UWA prior to and at the conclusion of the field trip, using SeaGIS software Cal. Contains files: 8.01.*.avi to 12.11.*.avi

  • Categories  

    Name, Brief Description and owner: Baited Remote Underwater stereo-Video (BRUV) systems (6 in total) were used. All equipment (BRUVs, weights, cameras, lights, ropes, etc.) belonged to UWA Relevant component details: make, model, serial number, firmware version, settings: Stereo‐BRUV systems consisted of a frame, protecting 2 convergent video cameras inside waterproof housings (plus one rear-facing video camera) and 2 lights (one forward-facing and one rear-facing), attached to a base bar, with a baited container fixed in front of the cameras. Systems were tethered by rope to surface buoys to facilitate relocation and retrieval. Weights were added to frames due to the current and depth in the area. Cameras used: 2 x Canon HG 25 (forward facing) with the follow settings: • Focus: Manual (3.0m) • Rec Program: P) • Image stabilizer: OFF • Facial recognition: OFF • Recording mode: MXP • Frame rate: PF25 1 x GoPro Hero 3+ (backwards facing), taking photos every 60 seconds. Cameras were calibrated at UWA prior to and at the conclusion of the field trip, using SeaGIS software Cal. Contains files: 30.01.*.avi to 31.06.*.avi

  • Categories  

    Name, Brief Description and owner: Baited Remote Underwater stereo-Video (BRUV) systems (6 in total) were used. All equipment (BRUVs, weights, cameras, lights, ropes, etc.) belonged to UWA Relevant component details: make, model, serial number, firmware version, settings: Stereo‐BRUV systems consisted of a frame, protecting 2 convergent video cameras inside waterproof housings (plus one rear-facing video camera) and 2 lights (one forward-facing and one rear-facing), attached to a base bar, with a baited container fixed in front of the cameras. Systems were tethered by rope to surface buoys to facilitate relocation and retrieval. Weights were added to frames due to the current and depth in the area. Cameras used: 2 x Canon HG 25 (forward facing) with the follow settings: • Focus: Manual (3.0m) • Rec Program: P) • Image stabilizer: OFF • Facial recognition: OFF • Recording mode: MXP • Frame rate: PF25 1 x GoPro Hero 3+ (backwards facing), taking photos every 60 seconds. Cameras were calibrated at UWA prior to and at the conclusion of the field trip, using SeaGIS software Cal. Contains files: 13.02.*.avi to 23.09.*.avi

  • Categories  

    Name, Brief Description and owner: Baited Remote Underwater stereo-Video (BRUV) systems (6 in total) were used. All equipment (BRUVs, weights, cameras, lights, ropes, etc.) belonged to UWA Relevant component details: make, model, serial number, firmware version, settings: Stereo‐BRUV systems consisted of a frame, protecting 2 convergent video cameras inside waterproof housings (plus one rear-facing video camera) and 2 lights (one forward-facing and one rear-facing), attached to a base bar, with a baited container fixed in front of the cameras. Systems were tethered by rope to surface buoys to facilitate relocation and retrieval. Weights were added to frames due to the current and depth in the area. Cameras used: 2 x Canon HG 25 (forward facing) with the follow settings: • Focus: Manual (3.0m) • Rec Program: P) • Image stabilizer: OFF • Facial recognition: OFF • Recording mode: MXP • Frame rate: PF25 1 x GoPro Hero 3+ (backwards facing), taking photos every 60 seconds. Cameras were calibrated at UWA prior to and at the conclusion of the field trip, using SeaGIS software Cal. Contains folders: Backwards, Forwards, New Convert, Videos Done

  • Categories  

    Name, Brief Description and owner: Baited Remote Underwater stereo-Video (BRUV) systems (6 in total) were used. All equipment (BRUVs, weights, cameras, lights, ropes, etc.) belonged to UWA Relevant component details: make, model, serial number, firmware version, settings: Stereo‐BRUV systems consisted of a frame, protecting 2 convergent video cameras inside waterproof housings (plus one rear-facing video camera) and 2 lights (one forward-facing and one rear-facing), attached to a base bar, with a baited container fixed in front of the cameras. Systems were tethered by rope to surface buoys to facilitate relocation and retrieval. Weights were added to frames due to the current and depth in the area. Cameras used: 2 x Canon HG 25 (forward facing) with the follow settings: • Focus: Manual (3.0m) • Rec Program: P) • Image stabilizer: OFF • Facial recognition: OFF • Recording mode: MXP • Frame rate: PF25 1 x GoPro Hero 3+ (backwards facing), taking photos every 60 seconds. Cameras were calibrated at UWA prior to and at the conclusion of the field trip, using SeaGIS software Cal. Contains files: 1.01.*.avi to 7.08.*.avi

  • Categories  

    The Secretariat to the Australian Landcare Council provided a table summarising government and non-government investment programs in ILM. We used this table to guide our searching of web sites and other documents to compile an Excel spreadsheet which now includes 2,229 records of separate projects. We were not able to source complete data on a number of the identified sources of investment, including those from State governments, investments by private corporations and not-for-profit organisations. Nevertheless, the data set is the most comprehensive that has ever been assembled on ILM in Australia. While substantial literature exists on Indigenous land management, the relevant documents are widely scattered across internet sites, in diverse State and Territory jurisdictions, in regional and local government and non-government organisations, and across sectoral boundaries (e.g. water management reports, biodiversity management reports). We anticipate that the opportunities and barriers faced by Indigenous land managers may vary across locations, sectors and local/regional/national scales. A simple national maps was produced demonstrating the locations of specific studies contained within reviewed literature.