Soil moisture is an essential factor in supporting the crop's growth. The total soil moisture affects plant fertility, which impacts its productivity. The information about soil moisture can be used for crop scheduling to optimize the potential of the harvest and reduce crop failure risk. The utilization of remote sensing data to measure soil moisture can be implemented for routine agricultural practices. This information is important, especially for dryland agriculture such as in the Semanu,

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... nung Kidul Regency. Value of soil moisture can be obtained from Sentinel-1 satellite image through the backscattering (σ•) method, which involves Apply Orbit File, Thermal Noise Removal, Border Noise Removal, Calibration, Speckle Filtering, Range Doppler Terrain Correction, and Conversion to dB. The dB (σ•) was then processed using the Dubois Model and Topp Model until the importance of soil moisture volumetric value was obtained, known in cm 3 /cm 3 . In this research, measuring the soil moisture value was also conducted by taking the soil sample tests under gravimetry methods for validation and sensor soil meter for comparison. Using Sentinel-1 to find soil moisture value is an alternative that can be done without conducting ground measurements. It is supported by a high resolution of 10x10 m and a standard error value of ±0,045. Furthermore, Sentinel-1 uses SAR (Synthetic Aperture Radar) possible to penetrate the cloud and land surface covers, even covered by lush vegetation. The backscattering data is, therefore, likely to be continuously generated. Based on the calculation of crops' water requirements by inputting the soil moisture values obtained from the calibrated Sentinel-1 data, the crop scheduling for dryland agriculture in the Semanu region was adjusted. Sentinel-1, which has interval data available every 12 days, is ideal for routine agriculture practices in real time. Therefore, the opportunity for agriculture development through Sentinel-1 is auspicious.