Articles | Volume 5, issue 1
https://doi.org/10.5194/gc-5-11-2022
Special issue:
https://doi.org/10.5194/gc-5-11-2022
GC Insights
 | 
06 Jan 2022
GC Insights |  | 06 Jan 2022

GC Insights: Identifying conditions that sculpted bedforms – human insights to building an effective AI (artificial intelligence)

John K. Hillier, Chris Unsworth, Luke De Clerk, and Sergey Savel'ev

Related authors

Editorial: The shadowlands of (geo)science communication in academia – definitions, problems, and possible solutions
Shahzad Gani, Louise Arnal, Lucy Beattie, John Hillier, Sam Illingworth, Tiziana Lanza, Solmaz Mohadjer, Karoliina Pulkkinen, Heidi Roop, Iain Stewart, Kirsten von Elverfeldt, and Stephanie Zihms
Geosci. Commun., 7, 251–266, https://doi.org/10.5194/gc-7-251-2024,https://doi.org/10.5194/gc-7-251-2024, 2024
Short summary
GC Insights: Open-access R code for translating the co-occurrence of natural hazards into impact on joint financial risk
John Hillier, Adrian Champion, Tom Perkins, Freya Garry, and Hannah Bloomfield
Geosci. Commun., 7, 195–200, https://doi.org/10.5194/gc-7-195-2024,https://doi.org/10.5194/gc-7-195-2024, 2024
Short summary
Co-RISK: a tool to co-create impactful university–industry projects for natural hazard risk mitigation
John K. Hillier and Michiel van Meeteren
Geosci. Commun., 7, 35–56, https://doi.org/10.5194/gc-7-35-2024,https://doi.org/10.5194/gc-7-35-2024, 2024
Short summary
Editorial: Geoscience communication – planning to make it publishable
John K. Hillier, Katharine E. Welsh, Mathew Stiller-Reeve, Rebecca K. Priestley, Heidi A. Roop, Tiziana Lanza, and Sam Illingworth
Geosci. Commun., 4, 493–506, https://doi.org/10.5194/gc-4-493-2021,https://doi.org/10.5194/gc-4-493-2021, 2021
Short summary
Demystifying academics to enhance university–business collaborations in environmental science
John K. Hillier, Geoffrey R. Saville, Mike J. Smith, Alister J. Scott, Emma K. Raven, Jonathon Gascoigne, Louise J. Slater, Nevil Quinn, Andreas Tsanakas, Claire Souch, Gregor C. Leckebusch, Neil Macdonald, Alice M. Milner, Jennifer Loxton, Rebecca Wilebore, Alexandra Collins, Colin MacKechnie, Jaqui Tweddle, Sarah Moller, MacKenzie Dove, Harry Langford, and Jim Craig
Geosci. Commun., 2, 1–23, https://doi.org/10.5194/gc-2-1-2019,https://doi.org/10.5194/gc-2-1-2019, 2019
Short summary

Related subject area

Subject: Geoscience engagement | Keyword: Co-creation and co-production
Development of forecast information for institutional decision-makers: landslides in India and cyclones in Mozambique
Mirianna Budimir, Alison Sneddon, Issy Nelder, Sarah Brown, Amy Donovan, and Linda Speight
Geosci. Commun., 5, 151–175, https://doi.org/10.5194/gc-5-151-2022,https://doi.org/10.5194/gc-5-151-2022, 2022
Short summary
Rapid collaborative knowledge building via Twitter after significant geohazard events
Robin Lacassin, Maud Devès, Stephen P. Hicks, Jean-Paul Ampuero, Remy Bossu, Lucile Bruhat, Daryono, Desianto F. Wibisono, Laure Fallou, Eric J. Fielding, Alice-Agnes Gabriel, Jamie Gurney, Janine Krippner, Anthony Lomax, Muh. Ma'rufin Sudibyo, Astyka Pamumpuni, Jason R. Patton, Helen Robinson, Mark Tingay, and Sotiris Valkaniotis
Geosci. Commun., 3, 129–146, https://doi.org/10.5194/gc-3-129-2020,https://doi.org/10.5194/gc-3-129-2020, 2020
Short summary

Cited articles

Allen, J. R. L.: Their Relation to Patterns of Water and Sediment Motion, North Holland Publishing Company, Amsterdam, 433 pp., https://doi.org/10.1017/S001675680005946X, 1968. 
Bishop, C. M.: Neural Networks for Pattern Recognition, Oxford University Press, 1st edition, Clarendon Press, Oxford, 502 pp., ISBN 9780-198538646, 1996. 
Bullard, J., White, K., and Livingstone, I.: Morphometric analysis of aeolian bedforms in the Namib Sand Sea using ASTER data, Earth Surf. Proc. Land., 36, 1534–1549, 2011. 
Duran Vinet, O. D., Adreiotti, B., Claudin, P., and Winter, C.: A unified model of ripples and dunes in water and planetary environments, Nat. Geosci., 12, 345–350, https://doi.org/10.1038/s41561-019-0336-4, 2019. 
Edgett, K. S. and Lancaster, N.: Volcaniclastic aeolian dunes: terrestrial examples and application to martian sands, J. Arid Environ., 25, 271–297, https://doi.org/10.1006/jare.1993.1061, 1993. 
Download
Short summary
It is an aspiration to infer flow conditions from bedform morphology (e.g. riverbed ripples) where sedimentary structures preserve the geological past or in inaccessible environments (e.g. Mars). This study was motivated by the idea of better designing an AI (artificial intelligence) algorithm to do this by using lessons from non-AI (i.e. human) abilities, investigated using a geoscience communication activity. A survey and an artificial neural network are used in a successful proof of concept.
Special issue
Altmetrics
Final-revised paper
Preprint