Abstract
Soil moisture has a major impact on the growth and development of grain crops. With a change in moisture, most of the physical or chemical properties of the soil change, which determines the need for systematic control of soil moisture in the practice of agriculture. However, soil moisture is highly variable in space and time, which makes it difficult to measure it on a field-wide scale. Spatial moisture interpolation allows to solve this problem by continuously displaying moisture indicators throughout the landscape. In this paper, we compare two methods of interpolation Nearest neighbor interpolation and Inverse distance weighted for moisture indicators obtained at the soil surface and at a depth of 1 m. Both methods showed results easy to interpret, each at its own level of detailing.