Soil moisture, the water held within the soil pores in liquid or vapor phase is the major factor that supports plant growth. Plants can readily absorb water if the moisture content of the soil is optimum. Knowledge of spatiotemporal variation of soil moisture is of utmost importance as it helps in understanding the health of crops and can thereby predict soil agricultural yield.

Conventional way of measuring soil moisture is to install soil moisture sensors in the ground which measures the volumetric water content indirectly by using properties of the soil, such as electrical resistance, dielectric constant, or interaction with neutrons etc. But this method is time-consuming and has limited coverage. Hence a number of methodologies are developed globally utilizing the satellite data to retrieve relative soil moisture which provides better coverage compared to the former method. Soil moisture data is provided by passive and active microwave sensors. Passive microwave sensors provide soil moisture globally at a coarser spatial resolution whereas active microwave sensors have a higher spatial but low temporal resolution (2–4 weeks). Using soil moisture data directly from any of these sensors will have compromised spatial or temporal resolution. Some of the applications where higher spatiotemporal resolution soil moisture data is useful are:

• Optimal irrigation in farms: Identify area being over irrigated.
• Improved flood risk estimation: We can estimate the area impacted by flood in near real time (with a latency of 24 hours) using satellite soil moisture data. We can also provide the future flood risk map by using the weather forecast and satellite data.
• Monitor agricultural drought in near real time: We can map the agricultural drought in near real time (upto 48 hours) in any part of the globe without requiring any local information.
• Likely crop Yield: Satellite soil moisture can be used to estimate the likely crop yield. These predictions are available at weekly frequency during the cropping season. We require crop yield data to provide this service.
• Irrigation Management: The satellite soil moisture can be combined with the Maximum Allowable Deficit (MAD) to obtain the irrigation requirement in near real time. The MAD can be estimated by knowing the crop and soil type.
• Improved weather forecast: Soil moisture is one of the important variables which influence the rainfall. The soil moisture data can be combined with the open source weather forecast data to provide an improved weather forecast.
• Analyze the impact of an irrigation project: The temporal trend in soil moisture along with ET helps in identifying the impact of the irrigation projects. The impact can be measured in terms of the area getting impacted and how much help it has provided to improve the crop yield.
• Identify the irrigated area by an irrigation source
• Automatic billing of farm based on the actual irrigation: The soil moisture and ET can provide the information on the areas being irrigated with a source e.g. canal or a tank. This information can be used for the automatic billing of farms and avoid the uncertainty coming due to the lack of field data.
• Estimation of actual evapotranspiration taking place
• Estimation of area getting degraded: The satellite soil moisture helps in identifying the areas having better or poorer irrigation over time. This can help us identify the areas being degraded over time. This information can be used in computing the agriculture risk associated with a geographical area.