Soil salinity represents a significant global challenge affecting agricultural productivity and soil health, with approximately 20% of irrigated lands experiencing salinization. Traditional soil salinity assessment methods are time-consuming, labor-intensive, and provide limited spatial coverage. Electromagnetic induction (EMI) has emerged as a rapid, non-invasive geophysical technique for mapping soil apparent electrical conductivity (ECa), which serves as a robust proxy for soil salinity. This research investigates the application of EMI technology for digital soil salinity mapping, examining its theoretical foundations, methodological approaches, and practical implementations. The study synthesizes current knowledge on EMI sensor configurations, calibration procedures, and spatial interpolation techniques used to generate high-resolution salinity maps. Results demonstrate that EMI-based approaches provide accurate salinity predictions with significantly reduced sampling requirements compared to conventional methods. The integration of EMI data with geostatistical modeling and machine learning algorithms enhances mapping accuracy and enables precision agriculture applications. This comprehensive review establishes EMI as an essential tool for sustainable soil and water management in salt-affected agricultural systems.