Spatial soil properties maps for Switzerland at 30 m resolution

The Swiss Soil Property Map (SSPM) was developed using the quantile random forest machine learning algorithm and remotely sensed surrogate information such as terrain, climate, vegetation, and soil covariates. The SSPM dataset provides maps at 30 m resolution for different soil depths (0, 30, 60, and 100 cm) in GeoTIFF format. The mean and respective uncertainty information is provided for each map. Please note that the phosphorus spatial map is only available for the topsoil (0-20 cm) due to the unavailability of the dataset at deeper depths.

For more details / to cite this dataset please use:

• Gupta, S. , Hasler, K. J.,  Alewell, C.: Mapping soil properties of Switzerland using remote sensing datasets and machine learning approach. Manuscript submitted, Geoderma Regional, 2023