' image identified 
from darker to 
change indicated 
This processing 
f MA 4D where 
A horizontal line, 
the North Bliss 
There were small 
the Camp Hueco 
ding the various 
cas could indicate 
; however, these 
iagnitude than the 
he playas of the 
described in the 
rocessing (section 
ct classes to be 
Che histograms in 
g each field point 
  
  
  
  
    
    
  
   
EY 
S 
RSS 
SEN 
NX 
NWN 
A 
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2 
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7 [A 
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10 11 12 13 14 15 
ass Value 
SNS 
   
listograms 
ted a few trends. 
ipacts exhibited a 
ectral class (i.e. 
her hand, peaked 
13 and 14). The 
pacts may have 
oints), but a peak 
how higher class 
ipacts and lower 
ce impacts. The 
h Recent impacts 
iore exposed soil 
9, the lower class 
mpacts may be 
lunal spaces. 
  
These trends are also in agreement with 
the basic observation made in all the sub-projects 
that an increase in soil exposure increases the 
brightness of the signature recorded by the 
satellite. ^ Conversely, the more  interdunal 
vegetation that is present tends to "darken" the 
basic soil signature found in the study area. These 
findings indicate that the age classes may be a 
very good indicator of vegetation regrowth and 
vehicle impacts. 
7. DISCUSSION 
7.1. Detection 
The results of this first sub-project 
answered basic questions of detectability of 
impact. In some respects, detection was 
dependent on level of use. This was particularly 
true of roads which fell into three categories 
(paved, unpaved, and less frequented trails). 
Perhaps most notably, the spatial resolution of the 
satellite sensors did not necessarily represent the 
limiting factor in detecting impact. 
Both Landsat TM and SPOT-XS imagery 
were shown to be useful for detecting areas of 
heavy impact and decreasing levels of impact away 
from unimproved roads in the area. Given 
appropriate ground truth, the observed halo effect 
may offer an opportunity to quantitatively measure 
the level of training impacts. 
7.2. Monitoring 
Assessment of the use of image 
differencing for monitoring change due to training 
impacts was complicated by a lack of accurate, 
quantifiable maneuver rate data. The main 
difficulty stemmed from inability to separate 
natural changes from man-made changes. 
The method of image differencing requires 
accurate image registration and spectral calibration 
of the multi-date images. Minimal seasonal spread 
in image dates is also desirable. Anniversary dates 
should be used where possible. 
For further studies of this type on Ft. 
Bliss, imagery should be selected from mid to late 
June because it is typically the driest time of the 
year and offers the highest sun angle. Periodic 
aerial photo surveys and ground surveys should be 
developed and maintained for monitoring changes 
in the landscape. This work would also benefit 
from local knowledge of the terrain, of seasonal 
changes, and how these changes influences the 
imagery. 
131 
7.3. Classification 
This sub-project served as a preliminary 
classification of impacts due to vehicle activities. 
While statistical correlation was not made, a 
positive relationship between spectral classes and 
age of impact appeared evident. Image 
classification should be accompanied by extensive 
field work, followed by rigorous procedures of 
accuracy assessment. In this case, however, 
constraints of data content and quality prevented 
full development of the classification. The spatial 
distribution of the survey points in the study area 
was also limited. Results would be improved with 
more widely distributed points. Most of the 
analysis relied on data that were collected for other 
purposes (i.e. without satellite image classification 
in mind). Thus, the work here can be considered a 
first-approximation with many possibilities for 
further analysis. 
The number of spectral classes chosen for 
this study was arbitrary. Determination of the 
optimum number of information classes would 
make these results more reliable. Finally, and 
possibly most importantly, if data on the level of 
impact is desired, a ground survey should be 
conducted to collect specifically this kind of 
information. Recommendations for such a survey 
would include sampling points which would 
adequately represent the various types of terrain 
found in the MAs. In addition, the survey should 
be conducted as close to a Landsat overpass as 
possible. A rigorous classification of the 
multispectral image should be performed and the 
survey points and spectral classes then correlated. 
Associations of particular levels of impact with 
spectral classes might be found. If this is the case, 
these classes could be isolated and used to produce 
an impact classification map of the MAs. Land 
use planners would then have a powerful tool to 
aid in maintaining the terrain for continued realistic 
training exercises. 
8. CONCLUSIONS 
This work sought to determine the utility 
of remote sensing for detecting, monitoring, and 
classifying training impacts at Ft. Bliss. The 
following conclusions were drawn: 
* The spectral capability of the satellite sensor was 
more of an influence than its spatial resolving 
power in detecting trails and other impacts. 
* A "halo" effect existed in the multispectral 
imagery which can be used to identify gradations 
in intensity of impact. 
* SPOT's spatial resolution helped to detect 
impacts; the advantages of Landsat's higher 
spectral resolution was inconclusive.