Soil salinity is a major environmental hazard in Liaohe River Delta, Liaoning Province, China. In spite of considerable efforts
dedicated to soil salinization, the extent of secondary salinization tends to increase. This requires careful monitoring the soil salinity status and variation to curb soil salinization trends, and secure sustainable land use and management. Multi-sensor and multi-temporal and multi-spectral and microwave remote sensing data has been widely used to detecting temporal and spatial changes of soil salinization. Airborne remote sensing and ground-based electromagnetic induction meters and laboratory and field spectrometers, combined with ground soil salinity data, have shown potential for monitoring soil salinization. When the vegetation cover threshold is below 25%~35% in semi-arid and arid, soils differ widely in their spectral response, and it is a most effective method to monitoring soil salinity by integrating soil salinity data and soil spectral data. However, if the vegetation cover threshold is beyond 25%~35%, the above method doesn't work well, soil salinity can be only inferred from the above vegetation spectra. The objective of this research is to discuss the relationships between soil salinity and above vegetation field-derived spectra, and use above vegetation field-derived spectra to predict soil salinity status in Liaohe River Delta tentatively. The result shows that it is feasible.