AgroScan - An Interactive SOC Prediction Tool for Farmers

Authors

Margarete Breitenhuber (ETH Zürich), Clara Buller (ETH Zürich), Claudio Bussinger (ETH Zürich), Jerome Reiter (ETH Zürich), Mennatallah El-Assady (ETH Zürich), Yannick Metz (ETH Zürich), Christina Humer (ETH Zürich)

Abstract

Soil organic carbon (SOC) is a key indicator of soil health and one of the largest terrestrial carbon pools. Recent European initiatives, including the EU Soil Monitoring Law, highlight the need for scalable and cost-effective approaches for monitoring agricultural soils. This study investigates how visual analytics can support farmers in the long-term monitoring and management of soil carbon stocks. User requirements were elicited through exploratory interviews with farmers and incorporated into AgroScan, an open-source web platform that combines remote-sensing-based SOC prediction with visual analytics. The platform provides field-level SOC estimates and derived soil organic matter (SOM) values together with contextual information such as crop rotation history to facilitate the interpretation of long-term soil health trends. By increasing the transparency and contextualizing the model outputs, AgroScan enables farmers to explore relationships between management practices and soil carbon dynamics and supports adaptive field management decisions.