A long-overdue check-in conversation with Tom Hengl, director at OpenGeoHub, one of the leading scientists in earth observation and remote sensing—one of the most cited in his field, belonging to the top 0.1% (based on Clarivate Highly Cited Researchers). We discuss the significant changes in the world of remote sensing, satellites, and the hype surrounding AI, machine learning, and large language models over the past three years. While the hype has brought some interesting advancements, it also distracts people from the real work that needs to be done.

We delve into the AI4SoilHealth European project we are part of, discussing how we can already monitor and observe most places on Earth from the sky at a resolution of 30 by 30 meters. Importantly, we can now look back nearly 25 years for almost all locations in Europe and analyse changes on a field-by-field basis. While we might not know the individual farmers, we can identify their fields, and we can train models to make predictions and provide actionable, relevant advice.
We explore the idea of celebrating farmers and land stewards who have successfully regenerated their plots of land over the past decades. But how do we shift a culture that celebrates sports over regenerative farming? Finally, we touch on the challenges holding back some of this work, including the need for reliable and affordable in situ in-field soil health analysis.

More about this episode on https://investinginregenerativeagriculture.com/tom-hengl.

This podcast is part of the AI 4 Soil Health project which aims to help farmers and policy makers by providing new tools powered by AI to monitor and predict soil health across Europe. For more information visit ai4soilhealth.eu.

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

This work has received funding from UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee [grant numbers 10053484, 1005216, 1006329].

This work has received funding from the Swiss State Secretariat for Education, Research and Innovation (SERI).

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