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Recent years have witnessed a dramatic increase in the acquisition of remote sensing?€?observations from satellite, aircraft and drone-based sensors, and in-situ devices. Technological advances have led to improvements in measurement resolution and precision, which is shifting the paradigm of?€?Earth?€?observation?€?from data scarcity to data abundance.?€?While these data have enormous potential?€?for?€?helping us achieve a range of global challenges, such as meeting the United Nations Sustainable Development Goals, identifying the optimal approaches?€?for handling and analysing these ever-growing datasets remains a challenge. Recent breakthroughs in AI/ML offer promising solutions to these challenges, including automated identification and extraction of key?€?observations, predicting future trends, identifying key environmental factors, and dealing with noisy signals under uncertainty.?€??€??€?
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This is the second ML4EO workshop following a successful pilot event in 2023. The broad aim is to?€?bring together remote sensing researchers, data science and AI experts, and industrial/third sector partners to build links?€?and share ideas. We hope the workshop will promote further collaboration and help develop research proposals to address specific global challenges.?€?
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There are several different ways to participate in this event:?€?
• Attend the workshop as a delegate
• Oral presentation (e.g. 10 mins + 5 mins discussion)?€?
• Poster presentation (ideal for preliminary results or ‘works in progress’)
• Chairing/contributing to a thematic discussion session.

Please and purchase a ticket. Further information can be found on the . A detailed schedule will be circulated closer to the event.

Please use the  to register for the event and purchase a ticket. If you would like to give an oral presentation or submit a poster, please submit a title/abstract using the .
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This event is supported by?€?the Ó£»¨¶¯Âþ via the Global Systems Institute (GSI), the Institute for Data Science and Artificial Intelligence (IDSAI) and the Environmental Intelligence Research Network.

Further details can be found on the dedicated .

Any queries?

Please contact the ML4EO Organising Commitee, a.laskey@exeter.ac.uk.

We hope to see you in Exeter!

ML4EO Committee