Mapping soil organic carbon in Tuscany through the statistical combination of ground observations with ancillary and remote sensing data

The organic carbon stored in the topsoil is an essential component of the global carbon cycle which should be quantified for a variety of purposes. The current paper proposes a new approach to map the amount of organic carbon stored in the 0.3 m topsoil (SOC), based on the statistical combination of a large number of ground observations with ancillary and remote sensing data. This approach is applied and tested in Tuscany, a region of Central Italy that is characterised by extremely diversified and heterogeneous environmental features. More than 3500 soil samples were collected and made available for the purpose, together with a soil map, meteorological data, a land use map and MODIS Normalised Difference Vegetation Index (NDVI) imagery. This information was processed by advanced statistical methods to yield a final map which describes the SOC spatial distribution in the region with a spatial resolution of 250 m. The map well reproduces the SOC variability in the region, showing higher SOC values for forests with respect to grasslands and croplands and SOC peaks related to peats and acidic soils. The accuracy assessment, carried out both versus all ground observations and by a leave-one-out cross validation strategy, testifies to the high quality of the SOC map, which has a global RMSE comprised between 17.5 and 32.3 t ha(-1). The map is also accompanied by per-pixel estimates of error variance which are informative on the uncertainty of SOC prediction.

Automated summary

This study introduced a new approach to map organic carbon stored in soil, successfully applied and tested in Central Italy. The research revealed higher SOC values in forested areas and peaks in peats and acidic soils. The high-quality SOC map and per-pixel error variance estimates provide valuable insights into SOC prediction uncertainties.