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  "name": "nsw-seabed-landforms-derived-from-marine-lidar-data-2022",
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  "name": "nsw-seabed-landforms-derived-from-marine-lidar-data-2022",
            
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  "notes": "Seabed landform features were classified from the New 
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  "notes": "Seabed landform features were classified from the New 
            
28
South Wales statewide marine lidar dataset, acquired in 2018 by Fugro 
28
South Wales statewide marine lidar dataset, acquired in 2018 by Fugro 
            
29
Pty Ltd on behalf of the Department of Planning and Environment (data 
29
Pty Ltd on behalf of the Department of Planning and Environment (data 
            
30
available for download on SEED, see below). Seabed features were 
30
available for download on SEED, see below). Seabed features were 
            
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extracted from the marine lidar data and classified into seabed 
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extracted from the marine lidar data and classified into seabed 
            
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landform classes. Classified landform features include reefs, plains, 
32
landform classes. Classified landform features include reefs, plains, 
            
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peaks, scarps, depressions and channels. These landforms capture 
33
peaks, scarps, depressions and channels. These landforms capture 
            
34
variation in the shape and structure of reef outcrops along the NSW 
34
variation in the shape and structure of reef outcrops along the NSW 
            
35
coastal and nearshore environment. \r\nFeatures were classified using 
35
coastal and nearshore environment. \r\nFeatures were classified using 
            
36
the Seabed Landforms Classification Toolset developed for ArcGIS by 
36
the Seabed Landforms Classification Toolset developed for ArcGIS by 
            
37
the Coastal and Marine Unit, DPE (Linklater et al. 2023) which are 
37
the Coastal and Marine Unit, DPE (Linklater et al. 2023) which are 
            
38
publicly available on SEED 
38
publicly available on SEED 
            
39
asets.seed.nsw.gov.au/dataset/seabed-landforms-classification-toolset) 
39
asets.seed.nsw.gov.au/dataset/seabed-landforms-classification-toolset) 
            
40
and GitHub 
40
and GitHub 
            
41
tps://github.com/LinklaterM/Seabed-Landforms-Classification-Toolset/). 
41
tps://github.com/LinklaterM/Seabed-Landforms-Classification-Toolset/). 
            
42
\r\n\r\nThe statewide dataset is provided as ArcGIS shapefiles divided 
42
\r\n\r\nThe statewide dataset is provided as ArcGIS shapefiles divided 
            
43
into 9 segments along the coast. The data covers 4060 km2, extending 
43
into 9 segments along the coast. The data covers 4060 km2, extending 
            
44
from the coastline (0 m AHD) to a maximum of 50 m depth, reaching an 
44
from the coastline (0 m AHD) to a maximum of 50 m depth, reaching an 
            
45
average depth of 35 m. Data coverage extends a maximum distance of 9 
45
average depth of 35 m. Data coverage extends a maximum distance of 9 
            
46
km offshore, with coverage extending on average 3 km 
46
km offshore, with coverage extending on average 3 km 
            
47
offshore.\r\n\r\nThis dataset provides an understanding of the extent 
47
offshore.\r\n\r\nThis dataset provides an understanding of the extent 
            
48
and distribution of submerged reefs along the NSW coast, which 
48
and distribution of submerged reefs along the NSW coast, which 
            
49
contributes fundamental baseline information for managers, users and 
49
contributes fundamental baseline information for managers, users and 
            
50
custodians of the marine environment. \r\n\r\nThis dataset was funded 
50
custodians of the marine environment. \r\n\r\nThis dataset was funded 
            
51
by the Marine Estate Management Authority and NSW Climate Change Fund 
51
by the Marine Estate Management Authority and NSW Climate Change Fund 
            
52
through the Coastal Management Funding Package. \r\n\r\nPlease cite 
52
through the Coastal Management Funding Package. \r\n\r\nPlease cite 
            
53
this dataset as: Linklater, M., Morris, B., Kinsela, M., Ingleton, T. 
53
this dataset as: Linklater, M., Morris, B., Kinsela, M., Ingleton, T. 
            
54
and Hanslow, D. (2022), Exploring patterns of reef distribution along 
54
and Hanslow, D. (2022), Exploring patterns of reef distribution along 
            
55
the southeast Australian coast using marine lidar data. Manuscript in 
55
the southeast Australian coast using marine lidar data. Manuscript in 
            
56
preparation. \r\n\r\nNSW statewide marine lidar data \u2013 available 
56
preparation. \r\n\r\nNSW statewide marine lidar data \u2013 available 
            
57
for download on SEED: 
57
for download on SEED: 
            
58
seed.nsw.gov.au/dataset/marine-lidar-topo-bathy-2018\r\n\r\nLinklater, 
58
seed.nsw.gov.au/dataset/marine-lidar-topo-bathy-2018\r\n\r\nLinklater, 
            
59
M., Morris, B.D. and Hanslow, D.J. (2023), Classification of seabed 
59
M., Morris, B.D. and Hanslow, D.J. (2023), Classification of seabed 
            
60
landforms on continental and island shelves. Frontiers in Marine 
60
landforms on continental and island shelves. Frontiers in Marine 
            
61
Science, 10, 
61
Science, 10, 
            
62
iersin.org/articles/10.3389/fmars.2023.1258556/full.\r\n\r\nLinklater, 
62
iersin.org/articles/10.3389/fmars.2023.1258556/full.\r\n\r\nLinklater, 
            
63
M., Ingleton, T. C., Kinsela, M. A., Morris, B. D., Allen, K. M., 
63
M., Ingleton, T. C., Kinsela, M. A., Morris, B. D., Allen, K. M., 
            
64
Sutherland, M. D., & Hanslow, D. J. 2019. Techniques for classifying 
64
Sutherland, M. D., & Hanslow, D. J. 2019. Techniques for classifying 
            
65
seabed morphology and composition on a subtropical-temperate 
65
seabed morphology and composition on a subtropical-temperate 
            
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continental shelf. Geosciences, 9(3), 141.",
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continental shelf. Geosciences, 9(3), 141.",
            
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      "id": "4656ed6e-d0ad-474d-b84c-222d1ecacb60",
n
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      "id": "7685cf30-dac3-4204-b83d-5e2d0ba2d604",
            
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      "last_modified": null,
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      "last_modified": null,
            
t
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      "metadata_modified": "2024-02-07T22:33:30.393436",
t
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      "metadata_modified": "2024-02-07T22:39:40.557419",
            
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      "mimetype": null,
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      "mimetype": null,
            
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      "mimetype_inner": null,
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      "mimetype_inner": null,
            
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      "name": "Mapservice - NSW seabed landforms derived from marine 
364
      "name": "Mapservice - NSW seabed landforms derived from marine 
            
365
lidar data 2022",
365
lidar data 2022",
            
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      "package_id": "25babb7a-f676-4fd1-97a6-8278ec9c2afb",
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      "package_id": "25babb7a-f676-4fd1-97a6-8278ec9c2afb",
            
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      "position": 11,
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      "position": 11,
            
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      "resource_type": null,
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      "resource_type": null,
            
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      "size": null,
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      "size": null,
            
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      "state": "active",
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      "state": "active",
            
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      "url": 
371
      "url": 
            
372
gov.au/arcgis/rest/services/Coastal_Marine/SeabedLandforms/MapServer",
372
gov.au/arcgis/rest/services/Coastal_Marine/SeabedLandforms/MapServer",
            
373
      "url_type": null
373
      "url_type": null
            
374
    }
374
    }
            
375
  ],
375
  ],
            
376
  "spatial": 
376
  "spatial": 
            
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],[150.17,-28.13],[153.73,-28.13],[153.73,-37.55],[150.17,-37.55]]]}",
377
],[150.17,-28.13],[153.73,-28.13],[153.73,-37.55],[150.17,-37.55]]]}",
            
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  "spatial_coverage": 
378
  "spatial_coverage": 
            
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],[150.17,-28.13],[153.73,-28.13],[153.73,-37.55],[150.17,-37.55]]]}",
379
],[150.17,-28.13],[153.73,-28.13],[153.73,-37.55],[150.17,-37.55]]]}",
            
380
  "state": "active",
380
  "state": "active",
            
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  "tags": [],
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  "tags": [],
            
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  "temporal_coverage_from": "2018-01-07",
382
  "temporal_coverage_from": "2018-01-07",
            
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  "temporal_coverage_to": "2018-01-12",
383
  "temporal_coverage_to": "2018-01-12",
            
384
  "title": "NSW seabed landforms derived from marine lidar data 2022",
384
  "title": "NSW seabed landforms derived from marine lidar data 2022",
            
385
  "type": "dataset",
385
  "type": "dataset",
            
386
  "unpublished": "false",
386
  "unpublished": "false",
            
387
  "update_freq": "notPlanned",
387
  "update_freq": "notPlanned",
            
388
  "url": null,
388
  "url": null,
            
389
  "version": null
389
  "version": null
            
390
}
390
}