An advanced new online prediction engine is transforming how soil spectroscopy laboratories assess landscape health across countries, cutting analysis and prediction costs while dramatically accelerating the delivery of data critical to landscape restoration and food system transformation.
The new technology was developed through the Soil and Land Health Lab and the Spatial Data Science and Applied Learning Lab (SPACIAL) at the Center for International Forestry Research and World Agroforestry (CIFOR-ICRAF). It builds on the state-of-the-art soil spectroscopy analysis combined with remote sensing to rapidly generate a widening network of detailed predictive maps showing what…