Anders Bjørn Møller, Triven Koganti, Amélie Beucher, Bo Vangsø Iversen, Mogens Humlekrog Greve

Coarse-resolution soil maps at regional to national extents are often inappropriate for mapping intra-field variability. At the same time, sensor data, such as electromagnetic induction measurements and aerial imagery, can be highly useful for mapping soil properties that correlate with electrical conductivity or soil color. However, maps based on these data nearly always require calibration with local samples, as multiple factors can affect the sensor measurements. In this study, we present a method, which combines coarse-resolution, large extent soil maps with sensor data in order to improve predictions of soil properties. We test this method for predicting clay and soil organic matter contents at five agricultural fields located in Denmark. We test the method for one field at a time, using soil samples from the four other fields to predict soil properties. Results show that the method generally improves predictions over the predictions from the coarse-resolution maps, especially for soil organic matter. The method generally overestimates prediction uncertainties, a disadvantage, which will require improvements. Overall, the method is a simple, promising tool for giving a quantitative estimate of soil properties, when no local soil samples are available.