Аннотация
The application of ground-based sensor monitoring data to assess soil and microclimatic conditions on agricultural land is considered. The study uses automatic measurements of air temperature and soil moisture at several depths with high temporal resolution, their aggregation and visual analysis of time series and profiles, as well as comparison with official meteorological data. It has been shown that local series are well consistent with regional ones in terms of dynamics, but more accurately reflect the levels characteristic of a particular field; moisture shows pronounced stratification and varying inertia at different depths. The obtained features and patterns are directly applicable for calibrating and improving the accuracy of yield prediction models, which confirms the practical value of local sensor data in agromonitoring