RA
Consideration factors Weight
Observation / line of fire 1|0.1400| 13.1 | 14.0 | 12.0 | 13.5
Covered / Concealed area [0.1400| 12.8 | 14.0 | 9.44 | 12.2
Obstacles 0.1500 | 13.3 | 15.0 | 8.94 | 9.43
Major terrain & features |0.1800| 12.0 | 6.00 | 18.0 | 12.0
Mobile Space 0.1900 | 19.0 | 17.3 | 11.7 | 12.0
Easiness of troop disposition [0.2000 | 20.0 | 17.7 | 15.8 | 15.0
Total(Score) 90.4 | 84.0 | 76.0 | 74.3
Exit Priority 1 2 3 4
Table 1. Priority table for simulation in Figure 3
DISCUSSION
This method greatly depends on how objectively
military experts and terrain analysts prepare accurate
GIS data and set weights for six factors. Usually it
is not easy to prepare the accurate terrain data in
time on the anticipated operation field in various
situations. However, this problem can be somehow
overcome by using GIS technologies (ERDAS, 1990;
ESRI, 1990).
The integration techniques of remotely-sensed
image and GIS procedures such as precision
registration, overlay, and online editing techniques
have been developed and utilized in the study (Yang,
1989a; 1989b). Additionally the simulation results can
be significantly varied if consideration factors and the
corresponding weight values change. The advice and
consult from the experts can be helpful However, the
artificial intelligence techniques such as
knowledge-based processing and expert system are
required.
CONCLUSION
The RA modeling has been developed to
synthesize and analyze the enemy, terrain, and
weather in the battlefield. This RA analysis technique
is expected to reduce the uncertainty in troop
maneuvering, fire planning, and communication site
selection. The accurate information produced by the
RA modeling will be able to enhance the combat
capability of a military unit and the efficiency of
weapon system and also support military officers to
make a prompt decision and operation plan. Thus this
modeling provides a tool for the field officers who
select the candidate RA of enemy troop and who
evaluate the strong and weak points of each RA.
This modeling makes a table as a final results
which is generated by evaluating the six factors, one
for each layer, derived in the previous sections.
This modeling is equipped with 2D and 3D
graphic tools(O'Reilly, 1990.) as well as images and
GIS data processing tools such as precision
registration, overlay, online editing, etc. The test area
of 30km x 30km is selected and entire process of RA
modeling have been performed. The results of
simulation match that of manual analysis very well.
More research is required to adopt AI techniques
such as knowledge based processing and expert
system to obtain weight values for consideration
factors.
References
ATTAS, .1993 A Study for Development of
Computerized Tactical Terrain Analysis System for
the Battlefield Operation, SERI Report #BC GO 2270,
139 pg.
ERDAS, 1990. ERDAS Field Gride.
The ARC/INFO
ESRI, 1990. Understanding GIS
Method.
Laurini, R., and Thompson D., 1992. Fundamentals of
Spatial Information Systems. 680 pg., Academic Press.
O' Reilly, T., 1990. X Toolkit Intrinsic Programming
Manual, OSF/Motif Edition, Vol 4, O' Reilly and
Associates, Inc.
Yang, Y. K, et al, 1989a. Development of a
Microcomputer Image Processing Systems for
Analyzing Satellite and Airborne Sensor Data.
Ministry of Science and Technology (MOST) National
Research Report BS N20622. pp. 173.
Yang, Y. K, et al, 1989b. Development of Satellite
Image Processing Software on Mainframe Computer.
Journal of Korean Society of Remote Sensing,
5(1):pp29-39.
402
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996
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