The Australasian Hydrographic Society’s (AHS) internationally recognised hydrographic conference program will return in 2026, beginning with the Hydrospatial 2026 Conference.
The conference will be held from 23 to 26 March 2026 at Shed 6 in Wellington, New Zealand.
With a theme of ‘Shaping the Future of Marine Discovery,’ the event will bring together professionals and thought leaders from across government, defence, research, industry and academia to explore the evolving role of hydrography.
The four-day program will feature keynote speakers, technical sessions, panel discussions, exhibitions, and networking opportunities across six key themes:
- Advances in hydrographic technology and autonomous systems
- Blue Economy and sustainable maritime development
- Coastal infrastructure, ports and harbour innovation
- Climate change, oceanography and marine environmental science
- Law of the Sea, sovereignty and maritime domain awareness
- Hydrospatial data for marine policy, planning and heritage
Further details of the event will be posted on the conference website and also on the Society’s website during the coming months.
This ECMWF-ESA Machine Learning Workshop aims to explore the fusion of traditional Earth System Observation and Prediction (ESOP) techniques with machine learning (ML) and deep learning (DL) methods.
It seeks to showcase the impact achieved through this fusion, while also addressing the remaining challenges that need further exploration. The presenters will show their contributions to this field and engage the attendees in discussions to provide a comprehensive understanding of the subject. The workshop strongly welcomes industry to demonstrate their commercial lenses for ML4ESOP applications.
This event will delve into the transformative role of ML in enhancing data analysis and predictive modelling within atmospheric sciences. Participants will engage with leading experts, partake in hands-on sessions, and explore cutting-edge innovations that are shaping the future of climate research and operational forecasting.
