Data
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://espace.library.uq.edu.au/view/UQ:410016&rft.title=Coral reef habitat maps derived from a high-spatial-resolution multi-spectral satellite image using object based image analysis&rft.publisher=The University of Queensland&rft.description=Archived high spatial resolution images were pre-processed and mosaics were created for the reef systems. Georeferenced benthic photo transect surveys were used to acquire cover information. Field and image data were integrated using an object-based image analysis approach that resulted in a hierarchically structured classification. Objects were assigned class labels based on the dominant benthic cover type, or location-relevant ecological and geomorphological principles, or a combination thereof. This generated a hierarchical sequence of reef maps with an increasing complexity in benthic thematic information that included: 'reef', 'reef type', 'geomorphic zone', and 'benthic community'. The overall accuracy of the 'geomorphic zone' classification for each of the six study sites was 76-82% using 6-10 mapping categories. For 'benthic community' classification, the overall accuracy was 52-75% with individual reefs having 14-17 categories and reef systems 20-30 categories.&rft.creator=Associate Professor Chris Roelfsema&rft.creator=Associate Professor Chris Roelfsema&rft.creator=Associate Professor Simon Albert&rft.creator=Associate Professor Simon Albert&rft.creator=Ms Stacy Jupiter&rft.creator=Phinn, Stuart&rft.creator=Phinn, Stuart&rft.creator=Professor Stuart Phinn&rft.creator=Professor Stuart Phinn&rft.creator=Roelfsema, Christiaan&rft.creator=Roelfsema, Christiaan&rft.date=2013&rft.coverage=162.104690,-4.834733 146.944382,-4.834733 146.944382,-11.836375 162.104690,-11.836375 162.104690,-4.834733&rft_rights=2013, The University of Queensland&rft_rights= http://creativecommons.org/licenses/by/3.0/deed.en_US&rft_subject=eng&rft_subject=ENVIRONMENTAL SCIENCE AND MANAGEMENT&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=Environmental Monitoring&rft_subject=Environmental Management&rft.type=dataset&rft.language=English Access the data

Licence & Rights:

Open Licence view details
CC-BY

http://creativecommons.org/licenses/by/3.0/deed.en_US

2013, The University of Queensland

Access:

Open

Contact Information

c.roelfsema@uq.edu.au

Full description

Archived high spatial resolution images were pre-processed and mosaics were created for the reef systems. Georeferenced benthic photo transect surveys were used to acquire cover information. Field and image data were integrated using an object-based image analysis approach that resulted in a hierarchically structured classification. Objects were assigned class labels based on the dominant benthic cover type, or location-relevant ecological and geomorphological principles, or a combination thereof. This generated a hierarchical sequence of reef maps with an increasing complexity in benthic thematic information that included: 'reef', 'reef type', 'geomorphic zone', and 'benthic community'. The overall accuracy of the 'geomorphic zone' classification for each of the six study sites was 76-82% using 6-10 mapping categories. For 'benthic community' classification, the overall accuracy was 52-75% with individual reefs having 14-17 categories and reef systems 20-30 categories.

Issued: 2013

This dataset is part of a larger collection

162.10469,-4.83473 146.94438,-4.83473 146.94438,-11.83638 162.10469,-11.83638 162.10469,-4.83473

154.524536,-8.335554

Subjects

User Contributed Tags    

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

Other Information
Mapping coral reefs at reef to reef-system scales, 10s-1000s km(2), using object-based image analysis

local : UQ:306370

Roelfsema, Chris, Phinn, Stuart, Jupiter, Stacy, Comley, James and Albert, Simon (2013). Mapping coral reefs at reef to reef-system scales, 10s-1000s km(2), using object-based image analysis. International Journal of Remote Sensing, 34 (18), 6367-6388. doi: 10.1080/01431161.2013.800660

Research Data Collections

local : UQ:289097

School of Earth Sciences Publications

local : UQ:161068