*DOI: http://dx.doi.org/10.5772/intechopen.103898 An Overview of Soil Moisture and Salinity Sensors for Digital Agriculture Applications*

#### **Figure 1.**

*Map of global soil salinity and water stress status. Adapted from [28, 29].*

A thorough understanding of soil salinization processes is also required for long-term soil and water management [38], which employs conventional electrical conductivity (EC) sensors [39]. In addition to salinity, EC is an indicator of soil health and nutrient availability for plants [40]. Salinity sensors are designed according to three electromagnetic (EM) phenomena: (i) electrical resistance, (ii) electromagnetic induction, and (iii) reflectometry [41]. The most accurate commercial method of EC estimation is the application of electromagnetic induction, including four electrodes [42]. EM38

is a noninvasive soil electromagnetic induction sensor that can measure EC at 120 cm above the soil and assess the soil nutrient situation [43, 44]. Although soil salinity modeling in farmlands using EC sensors is crucial to assess crop yield and prevent productive soil loss [45], measuring apparent soil EC (ECa) is needed for calibration with the actual content of salts in the laboratory [46], which is not economically cost-effective.

The soil mapping of spatial and temporal variations in soil properties is presumably the most affordable and beneficial approach to front salinity and watering issues. In this regard, Mashimbye et al. [47] evaluated the role of hyperspectral or satellite data in soil mapping potential applications. Satellite technologies make it easier to measure salinity and moisture variables, and as a result, they can provide soil characteristic data instantly, quantitatively, and affordably [48]. For instance, the launching of Sentinel satellites upgraded free data access for users [49], including advanced facilities for earth monitoring [50]. Though the remote sensing of soil properties presents extensive coverage for spatial distribution, multispectral data have limited capabilities, such as low spatial resolution due to spectral and spatial division [35, 50]. A spatial description of soil salinity is essential for salinity management in agriculture [51]. On the other hand, conventional techniques for evaluating soil characteristics are costly and time-consuming [52] (**Figure 2**); the question of whether proximal sensors or aerial sensors are more efficient for controlling soil moisture and salinity levels in farmlands arises.
