Evaluating Soil Reflectance Composites generated by SCMaP using different Sentinel-2 reflectance data inputs.

Soils contain the largest global carbon pool and thus, play an important role in atmospheric CO2 sequestration through increase in soil organic carbon (SOC) stock (Minasny et al., 2017). Therefore, large scale mapping and reporting of soil status, quality and health is starting to get a requirement amongst policy-makers and implemented in target setting of the Sustainable Development Goals and relevant EU policies. Soil quality and health monitoring is commonly described as a sum of physical, chemical and biological properties of soils. Since many years, multispectral and hyperspectral Earth Observation (EO) have been valuable data sources for analyzing the chemical and physical constitution of top soils (Chabrillat et al., 2019). Mainly two approaches are used, the Digital Soil Modelling (DSM) approach as well as the Spectral Soil Modelling (SSM) approach. Both approaches assimilate EO data products such as information regarding the vegetation dynamics and exposed soil reflectance data.