SCIENCE TALK: A Novel Approach for Quantifying Soil Degradation Using Big Data & AI for Soil Health

Soils around the world face threats from various degradation processes, posing serious risks to food security, ecological integrity, biodiversity, climate regulation, and socio-economic activities. Current methods for assessing soil degradation often use arbitrary thresholds, limiting their effectiveness. Anticipating changes in soil degradation requires the integration of new approaches. In this talk, Professor Nima Shokri introduced the Soil Vulnerability Index (SVI), a continuous metric for spatio-temporal monitoring of soil degradation while providing both the extent and magnitude of the degradation. The SVI integrates indicators like the erosion rate, soil pH, electrical conductivity, and soil organic carbon. Applied across Europe, the SVI reveals higher vulnerability in southern regions and healthier conditions in northern and central areas. He used machine learning algorithms to train models that relate the SVI to various environmental drivers, enabling predictions of soil vulnerability and future variations under different scenarios. This approach highlights the roles of climate, vegetation, and land management in soil vulnerability and underscores the need for integrated approaches to soil health and conservation.