Agricultural water management is key for a sustainable agricultural productivity. Accurate soil moisture measurements are essential in irrigation management, hydrological modelling, ground water recharge, flood, and drought forecasting. There are many different techniques for estimating soil moisture at different scales, from point to landscape scales. In this paper, we used a modified version of change detection approach for near surface soil moisture modelling coupled with a Cosmic-Ray Neutron Sensor (CRNS) installed at a field site 100 km outside Vienna, Austria. The model allows a conversion of Vertical-Vertical (VV) polarization into soil moisture. The model is calibrated with 2019 CRNS data and validated with data from 2020 to 2021. The results showed the good performance of the model with a high correlation for the calibration (R 2 = 0.81) and predicted the soil moisture with an absolute error of 0.2%. This study is a major step in the monitoring of soil moisture at high spatial and temporal resolution by combining remote sensing and the CRNS based nuclear technology.