Data

Australian shoreline retreat dataset for Bayesian network analysis

The University of Queensland
Dr Daniel Harris (Aggregated by) Dr Daniel Harris (Aggregated by) Dr Yongjing Mao (Aggregated by) Dr Yongjing Mao (Aggregated by) Dr Yongjing Mao (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.14264/fe5a28b&rft.title=Australian shoreline retreat dataset for Bayesian network analysis&rft.identifier=RDM ID: 9447e810-b835-11eb-bdf4-79b3a535a5b2&rft.publisher=The University of Queensland&rft.description=This dataset includes spatial distribution of shoreline retreat rate of Australia as well as variables determining the shoreline migration (e.g. mean wave height, tidal range and sea level rise rate). It also includes Matlab scripts to set-up Bayesian networks, which can be used to understand relations among different variables and predict future shoreline retreat rate under different sea level rise scenarios.&rft.creator=Dr Daniel Harris&rft.creator=Dr Daniel Harris&rft.creator=Dr Yongjing Mao&rft.creator=Dr Yongjing Mao&rft.creator=Dr Yongjing Mao&rft.creator=Dr Yongjing Mao&rft.date=2021&rft_rights=2021, The University of Queensland&rft_rights= https://guides.library.uq.edu.au/deposit-your-data/license-reuse-data-agreement&rft_subject=eng&rft_subject=shoreline retreat rate&rft_subject=Bayesian network analysis&rft_subject=Geomorphology and Regolith and Landscape Evolution&rft_subject=EARTH SCIENCES&rft_subject=PHYSICAL GEOGRAPHY AND ENVIRONMENTAL GEOSCIENCE&rft.type=dataset&rft.language=English Access the data
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[email protected]
School of Earth and Environmental Sciences

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This dataset includes spatial distribution of shoreline retreat rate of Australia as well as variables determining the shoreline migration (e.g. mean wave height, tidal range and sea level rise rate). It also includes Matlab scripts to set-up Bayesian networks, which can be used to understand relations among different variables and predict future shoreline retreat rate under different sea level rise scenarios.

Issued: 2021

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Subjects
Bayesian network analysis | Earth Sciences | Geomorphology and Regolith and Landscape Evolution | Physical Geography and Environmental Geoscience | eng | shoreline retreat rate |

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Identifiers
ACN 633 798 857