Data

Seascape classification layer from the Darwin Harbour 2011 Marine Survey (GA0333)

Geoscience Australia
Siwabessy, J. ; Tran, M. ; Huang, Z. ; Nichol, S.L. ; Atkinson, I.
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=https://pid.geoscience.gov.au/dataset/ga/83951&rft.title=Seascape classification layer from the Darwin Harbour 2011 Marine Survey (GA0333)&rft.identifier=https://pid.geoscience.gov.au/dataset/ga/83951&rft.description=This dataset contains seascape classification layer derived from bathymetry and backscatter, and their derivative from seabed mapping surveys in Darwin Harbour. The survey was undertaken during the period 24 June to 20 August 2011 by iXSurvey Australia Pty Ltd for the Department of Natural Resources, Environment, The Arts and Sport (NRETAS) in collaboration with Geoscience Australia (GA), the Darwin Port Corporation (DPC) and the Australian Institute of Marine Science (AIMS) using GA's Kongsberg EM3002D multibeam sonar system and DPC's vessel Matthew Flinders. The survey obtained detailed bathymetric map of Darwin Harbour. Refer to the GA record ' Mapping and Classification of Darwin Harbour Seabed' for further information on processing techniques applied (GeoCat: 79212; GA Record: 2015/xx)Maintenance and Update Frequency: asNeededStatement: Multiple spatial layers of physical data were classified using the Iterative Self Organising (ISO) Unsupervised Classification methodology available in ArcGIS (v.10). This methodology performs unsupervised classification based on a series of input raster bands using the ISO Cluster and Maximum Likelihood Classification tools. Datasets used in the derivation of the seabed habitat classification included bathymetry, slope, rugosity, backscatter and p rock. Statistically, there are an optimum number of classes into which the data can be partitioned that minimises uncertainty. The method we used is called the Distance Ratio method. Classifications were carried out for 2 to 9 classes, with the distance ratio estimated for each class. The distance ratio is the ratio of the average of the mean distance of each class member from its class mean to the overall average distance of each member from the overall mean. This value provides an indication of how well the data matches the assigned classification. The optimal number of classes occurs where the distance ratio has a local minimum, indicating that the addition of more classes will not improve the classification accuracy as much as the addition of previous classes. Choosing fewer classes will not explain the variation in the classes as thoroughly.&rft.creator=Siwabessy, J. &rft.creator=Tran, M. &rft.creator=Huang, Z. &rft.creator=Nichol, S.L. &rft.creator=Atkinson, I. &rft.date=2015&rft.coverage=westlimit=130.69; southlimit=-12.59; eastlimit=130.94; northlimit=-12.32&rft.coverage=westlimit=130.69; southlimit=-12.59; eastlimit=130.94; northlimit=-12.32&rft_rights=&rft_rights=Creative Commons Attribution 4.0 International Licence&rft_rights=CC-BY&rft_rights=4.0&rft_rights=http://creativecommons.org/licenses/&rft_rights=WWW:LINK-1.0-http--link&rft_rights=Australian Government Security ClassificationSystem&rft_rights=https://www.protectivesecurity.gov.au/Pages/default.aspx&rft_rights=WWW:LINK-1.0-http--link&rft_rights=Creative Commons Attribution 4.0 International Licence http://creativecommons.org/licenses/by/4.0&rft_subject=environment&rft_subject=Marine Data&rft_subject=multibeam&rft_subject=marine survey&rft_subject=bathymetry&rft_subject=backscatter&rft_subject=marine environmental baselines&rft_subject=AU-NT&rft_subject=Marine Geoscience&rft_subject=EARTH SCIENCES&rft_subject=GEOLOGY&rft_subject=Published_External&rft.type=dataset&rft.language=English Access the data
Cite Saved to MyRDA Save to MyRDA

Licence & Rights:

Open Licence view details
CC-BY

Creative Commons Attribution 4.0 International Licence
http://creativecommons.org/licenses/by/4.0

Creative Commons Attribution 4.0 International Licence

CC-BY

4.0

http://creativecommons.org/licenses/

WWW:LINK-1.0-http--link

Australian Government Security ClassificationSystem

https://www.protectivesecurity.gov.au/Pages/default.aspx

WWW:LINK-1.0-http--link

Access:

Open

Brief description

This dataset contains seascape classification layer derived from bathymetry and backscatter, and their derivative from seabed mapping surveys in Darwin Harbour. The survey was undertaken during the period 24 June to 20 August 2011 by iXSurvey Australia Pty Ltd for the Department of Natural Resources, Environment, The Arts and Sport (NRETAS) in collaboration with Geoscience Australia (GA), the Darwin Port Corporation (DPC) and the Australian Institute of Marine Science (AIMS) using GA's Kongsberg EM3002D multibeam sonar system and DPC's vessel Matthew Flinders. The survey obtained detailed bathymetric map of Darwin Harbour. Refer to the GA record ' Mapping and Classification of Darwin Harbour Seabed' for further information on processing techniques applied (GeoCat: 79212; GA Record: 2015/xx)

Lineage

Maintenance and Update Frequency: asNeeded
Statement: Multiple spatial layers of physical data were classified using the Iterative Self Organising (ISO) Unsupervised Classification methodology available in ArcGIS (v.10). This methodology performs unsupervised classification based on a series of input raster bands using the ISO Cluster and Maximum Likelihood Classification tools. Datasets used in the derivation of the seabed habitat classification included bathymetry, slope, rugosity, backscatter and p rock. Statistically, there are an optimum number of classes into which the data can be partitioned that minimises uncertainty. The method we used is called the Distance Ratio method. Classifications were carried out for 2 to 9 classes, with the distance ratio estimated for each class. The distance ratio is the ratio of the average of the mean distance of each class member from its class mean to the overall average distance of each member from the overall mean. This value provides an indication of how well the data matches the assigned classification. The optimal number of classes occurs where the distance ratio has a local minimum, indicating that the addition of more classes will not improve the classification accuracy as much as the addition of previous classes. Choosing fewer classes will not explain the variation in the classes as thoroughly.

Issued: 2015

This dataset is part of a larger collection

Click to explore relationships graph
Help

Related Organisations

Related People

130.94,-12.32 130.94,-12.59 130.69,-12.59 130.69,-12.32 130.94,-12.32

130.815,-12.455

text: westlimit=130.69; southlimit=-12.59; eastlimit=130.94; northlimit=-12.32

Subjects
AU-NT | Earth Sciences | Geology | Marine Data | Marine Geoscience | Published_External | backscatter | bathymetry | environment | marine environmental baselines | marine survey | multibeam |

User Contributed Tags    

Login to tag this record with meaningful keywords to make it easier to discover

Other Information
Download the file (File download)

uri : https://d28rz98at9flks.cloudfront.net/83951/83951.zip

Identifiers
Similar data you may be interested in: