Unified Soil Classification System

Geotechnical engineering

Cartography

Soil carbon

Digital elevation model

Hydraulic conductivity

Geology

Soil water

Digital soil mapping

Soil classification

Geography

Hydrology (agriculture)

Environmental science

Soil map

Soil science

Soil texture

Remote sensing

Terrain

Pedotransfer function

Digital mapping

CATENA

Detailed maps of soil properties are essential for soil protection planning and management; however, creating very high-resolution maps at the national level with sufficient accuracy is a challenging task and remains unavailable for most countries. For the Czech Republic, very high resolution (20 m·pixel−1) soil property maps (soil organic carbon—SOC, texture, pH, bulk density, soil depth) were created using digital soil mapping methods, combined with a wide database of soil legacy and current samples. The latest approaches were employed for predictive mapping: a quantile random forest model with the determination of prediction intervals, a mosaic of bare soils from Sentinel-2 satellite data, a Gaussian pyramid of terrain attributes, and a buffer distance map. These variables were found to be among the most important in the resulting models. The properties were mapped with an RMSE accuracy of 0.43% SOC, 5.56–11.14% for texture fractions, 0.70 pH, 0.13 g·cm−3 bulk density, and 20.03 cm for soil depth, thus providing detailed data on soil cover. Greater levels of inaccuracy were found in areas with extreme values, for which further investigation is necessary either through more detailed sampling based on active learning, or adapted methods for enhanced predictive ability.

High-resolution agriculture soil property maps from digital soil mapping methods, Czech Republic