A study was conducted to determine the predictive capability of SPOT (
Systeme Probatoire d'Observation de la Terre) satellite data for detec
ting areas that are subjected to salinity encroachment and nutrient de
ficiencies. The SPOT observations were related to the chemical charact
eristics of soil samples collected from a corn field located south of
Torrington, in east central Wyoming. On a false color infrared composi
te (FCC) image, the saline areas were bright white patches; healthy ve
getation was bright red to magenta in color. A nearby reservoir had a
dark blue tone except where light blue tones indicate silty and/or sha
llow water. From the visual interpretation of the FCC image, it was no
t possible to predict soil salinity quantitatively. Statistical analys
is of SPOT digital counts by bands indicated that the near infrared ba
nd (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 co
rrelated with saturated paste electrical conductivity (EC) and water s
oluble Na. Brightness index (BI), the summation of digital count of th
e three bands, was positively correlated with soil EC, and water solub
le Na, Ca, Mg and was negatively correlated with Mn, while the normali
zed difference vegetation index (NDVI = (NIR-Red)/(NIR + Red)) and rat
io index (RI = NIR/Red) were negatively correlated with EC and water s
oluble Na, Ca, and Mg. All the spectral bands were significantly and p
ositively correlated among themselves and with BI. Analysis of varianc
e indicated that the sampling points possessing high BI values had hig
her EC, water soluble Na, Ca, and Mg and lower levels of Mn and Zn. Sa
mples with low NDVI and RI values had high EC, water soluble Na, Ca, a
nd low Mn, indicating that high salinity and nutrient deficiency can b
e detected with reasonable accuracy with BI, NDVI, and RI. Among the s
pectral indices, BI proved to be the best indicator of salinity and nu
trient deficiency.