s “treads are still 
4 23 
ng”. Older was 
zone, ruts visible, 
Trace was defined 
tation is growing 
don, Ft. Bliss). In 
re coincident with 
these, 76 were 
ler, and 555 were 
s were generated 
se points. 
uring the week of 
n two objectives: 
aneuver areas and 
of use, and 2) to 
nt in the satellite 
es were met with 
Bliss staff. 
llowing steps: 
> of two criteria: 
or presence of a 
pact was roughly 
3liss staff. Sites 
ry five-level scale 
impact, moderate 
rmediate classes. 
' features were 
rared (CIR) and 
7 derived from 
lune 1992. The 
especially useful 
rrain which was 
features in the 
road extent in the 
ical land cover. 
using GPS. 
essional Global 
provided by the 
) the field sites. 
to 8 satellites, 
after differential 
| site a GPS file 
-processing. The 
cond; a minimum 
| for each point. 
on the 1:50,000 
(DMA) maps of 
ie June 1992 TM 
  
  
  
3) Describe the site. 
Written descriptions made at each site included 
information on the dominant vegetation cover, soil 
characteristics (e.g., color and texture), and other 
aspects of the site. Impacts such as lack of 
interdunal vegetation and tracks were also noted. 
Photographs of the area around the sites were 
taken from a high vantage point (e.g., on top of a 
dune or car hood) for future reference. 
4. PREPROCESSING 
4.1. Image Rectification 
The 4 June 1992 and 29 October 1990 
Landsat scenes and the 6 October 1990 SPOT 
scene were rectified by digitizing ground control 
points from 7.5 minute quads. Two Landsat 
scenes, dated 19 September 1993 and 28 October 
1984, were rectified using image to image 
registration. In both cases the master image used 
was the rectified 4 June 1992 Landsat scene. An 
affine transformation was used to rectify the 
images to Universal Tranverse Mercator (UTM) 
Zone 13, North American Datum 1927 (NAD27) 
map projection. The Landsat images were 
resampled to 30 meter pixels, while the SPOT 
images were resampled to 20 meter pixels. The 
nearest neighbor algorithm was used to preserve 
the spectral integrity of the data. The root mean 
square error was less than one pixel for all of the 
image rectifications performed. 
4.2. Spectral Calibration 
Comparison of multi-temporal imagery, as 
in change detection studies, requires that the 
images be radiometrically calibrated. Linear 
spectral calibration reduces undesirable changes in 
sun angle, atmospheric scattering, and sensor drift 
(Eckhardt ef al., 1990; Coppin and Bauer, 1994). 
The process has two major requirements. First, 
one image must serve as a reference image to 
which all others will be calibrated. Second, bright 
and dark targets must be identified which are not 
influenced by phenological or other natural 
changes, such as differences in moisture. The 
reference image was arbitrarily chosen as the 19 
September 1993 Landsat scene. The goal of this 
processing was to derive slope and intercept values 
from calibration targets so that the 28 October 
1984 and the 29 October 1990 Landsat scenes 
would more closely match the digital numbers of 
the reference scene. The images were visually 
surveyed, along with various maps of the area, for 
features which could serve as calibration targets. 
Very bright and dark features influenced primarily 
by atmospheric scattering only were chosen as 
calibration targets. 
An industrial facility called Smeltertown in 
southeastern El Paso was selected as the dark 
127 
target. A firing range pad on the eastern edge of 
MA 8 and an area of bright wind blown sand 
across the US-Mexico border, southwest of El 
Paso were chosen as bright targets. 
Spectral signatures were extracted from 
the calibration targets. The signatures for each of 
these targets were plotted and examined to ensure 
that their shape did not vary erratically between all 
three dates. Radical changes in shape would 
indicate that the target was not stable over time 
and could not be used in this analysis; however, all 
the targets met this criterion. 
For each band, the mean digital number 
for each target was plotted for the signatures 
obtained from the 1994 imagery against the those 
obtained from the image being calibrated. The 
slopes and intercepts were found by linear 
regression. The slopes and intercepts were used to 
linearly transform each band of the other Landsat 
images so that new spectrally calibrated imagery 
was obtained. 
The rectified and calibrated satellite 
imagery were then subsetted to cover only the 
study area. The subsets were rectangular with a 
northwest UTM coordinate of 3,566,486N, 
363,728E and a southeast UTM coordinate of 
3,548,426N, 385,418E. 
4.3. GPS Processing 
Given the resolution of the SPOT and TM 
imagery, differential processing was required to 
obtain sub-pixel accuracy of the field locations. 
Unprocessed GPS files yield an approximate 
locational accuracy of 200 meters. Differential 
correction improves this accuracy to within 2-5 
meters. An Arc/Info point coverage was generated 
from these corrected coordinates. 
5. IMAGE PROCESSING 
This study was broken down into three 
sub-projects: detection, monitoring and 
classification. The first sub-project was an image 
interpretation effort to identify how various 
training impacts appear on satellite imagery as 
well as aerial photos. The second sub-project, was 
a change detection investigation, using multi- 
temporal satellite imagery of the area. This would 
provide information on the ability of these systems 
to monitor change due to training impacts. The 
third sub-project was a correlation of a classified 
image with ground-based impact data. This was 
an initial investigation into quantifying levels of 
impact.