Unsustainable land use and population pressure are major drivers of soil degradation. The threats to soil health include loss of soil organic matter, biodiversity, and the soil itself through erosion. We are at a crossroads in history in our attempt to preserve European and global soil resource. It is a striking paradox that on the one hand soils are one of the solutions to mitigating greenhouse gas emissions, while on the other hand 60–70% of EU soils are unhealthy, mainly because of unsustainable management practices. To prevent soil degradation and help combat climate change, the European Commission has set an ambitious goal with several concrete targets such as net zero emissions and planting 3 billion trees by 2030. The ability to measure and assess progress toward healthy soils will be critical to the success of improving soil health across Europe for both stakeholders and policy-makers.
In soil science, especially through pedometrics, AI (Artificial Intelligence) is forging a path for a diverse range of applications including soil measurements, soil image recognition and soil mapping. Now is the moment to systematically apply cutting edge AI methods to soil datasets and measurements and build an automated data-driven decision support for soils. In this project we aim to develop a robust indicator framework by harnessing the advances in AI and digital technologies that present new and untapped opportunities for monitoring the pressures and condition of soils and land. For this, we will utilize a pan-European soil monitoring system (LUCAS) in conjunction with EO and ancillary data to produce AI4SoilHealth — an open access European-wide digital infrastructure for monitoring and forecasting soil health indicators. More details about AI4SoilHealth and the team involved can be found at here [https://cordis.europa.eu/project/id/101086179] or DOI:10.3030/101086179.
