A study was conducted to determine the predictive capability of SPOT (Systeme Probatoire d' Observation de la Terre) satellite data for detecting areas that are subjected to salinity encroachment and nutrient deficiencies. The SPOT observations were related to the chemical characteristics of soil samples collected from a corn field located south of Torrington, in east central Wyoming. On a false color infrared composite (FCC) image, the saline areas were bright white patches; healthy vegetation was bright red to magenta in color. A nearby reservoir had a dark blue tone except where light blue tones indicate silty and/or shallow water. From the visual interpretation of the FCC image, it was not possible to predict soil salinity quantitatively. Statistical analysis of SPOT digital counts by bands indicated that the near infrared band (X-3) was superior to the visible bands for salinity detection. Of the three SPOT bands (XS-1, XS-2, and XS-3), XS-3 was significantly correlated with saturated paste electrical conductivity (EC) and water soluble Na. Brightness index (BI), the summation of digital count of the three bands, was positively correlated with soil EC, and water soluble Na, Ca, Mg and was negatively correlated with Mn, while the normalized difference vegetation index (NDVI = (NIR-Red)/(NIR + Red)) and ratio index (RI = NIR/Red) were negatively correlated with EC and water soluble Na, Ca, and Mg. All the spectral bands were significantly and positively correlated among themselves and with BI. Analysis of variance indicated that the sampling points possessing high BI values had higher EC, water soluble Na, Ca, and Mg and lower levels of Mn and Zn. Samples with low NDVI and RI values had high EC, water soluble Na, Ca, and low Mn, indicating that high salinity and nutrient deficiency can be detected with reasonable accuracy with BI, NDVI, and RI. Among the spectral indices, BI proved to be the best indicator of salinity and nutrient deficiency.