USMA Department of Systems Engineering1
Terrain Data Analysis and Visualization
USMA Department of Systems Engineering
LTC Rob KewleyUSMA Department of Systems Engineering(845) 938-5206, Fax: (845) [email protected]
Terrain Visualization AdvisorCadet Aaron FairmanUSMA Department of System Engineering(845) [email protected]
Cadet Daniel PateUSMA Department of Systems Engineering(845) [email protected]
Cadet Collin SmithUSMA Department of Systems Engineering(845) [email protected]
Cadet Grace GarciaUSMA Department of Mathematics(845) [email protected]
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Agenda
• Problem Definition
• Background
• Assumptions
• Cost Analysis
• Simulation Findings
• Conclusions
• Future Work
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Problem Definition
• Problem Statement: Provide information to assist in creating realistic terrain databases for operational testing of the Army’s Future Combat Systems – Providing adequate, realistic data for mission
planning and execution.
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Stakeholder Analysis• Key stakeholders listed in bold:
– Research, Development & Engineering Command (RDECOM)
– Topographic Engineering Center (TEC)– Future Combat System (FCS)– National Geospatial-Intelligence Agency (NGA)– Tactical Terrain Teams– US Army Soldiers: DIV, BDE, BN, CO, PLs, NCOs– Joint Command and Operations: Army, Air Force, Marines,
Navy, Coast Guard– Army National Guard and Reserve Component– Possible Civil Applications: Disaster Relief (FEMA),
Homeland Security
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Integration
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Overview
• Terrain Databases are used for various military operations.
• Constraints:– Network bandwidth– Limited information/intelligence for a given area.– Different data formats between source data and final
product.
• Designed three different scenarios to test terrain data sufficiency: – Low Level (basic “on-the-shelf” data)– Medium Level (basic data plus significant analysis)– High Level (extensive analysis, additional intelligence)
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Functional HierarchyImprove
Terrain Data Generation
Obtain Source Data
Display Data
Visually NumericallyLIDAR Fly Over
NGA Data
Create Dataset
Raster Vector
Identify Target Areas
Identify Area
Identify Components of Analysis
Camp Shugart-
Gordon, Fort Polk, LA
River
Buildings
Roads
Elevation
Vegetation
Add Polygon
Data
Add Line Data
Create Database
Increase Layers of
Detail
Showing Dataset
3D
Database Administration
Analyze Cost
Input Cost and Detail into Data
Matrix
Analyze Cost and Detail of Imgery
Analyze C2 Results and
Cost of Dataset
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Camp Shea
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Value Hierarchy
Dynamic
Integration of Database in C2 System
Security Cost Accessibility
Maximize Amount
Services can use Database
Maximize Format of
Data
Number of Formats
(MIB)
Number of Joint OPS using
Dataset/Database(MIB)
Maximize Verification/
Authentication for changing
datasets
Maximize Amount of Users can
Access Database
Number of People (MIB)
Minimize Time to Produce Database
Maximize Data
Resolution
Minimize Cost of Storing
Data
Analyst Hours (LIB)
Meters (LIB)
MB (LIB)
Number of Security Checks (MIB)
Minimze Error In Obrtaining
Data
Number of Errors (LIB)
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Operational ScenariosAssumptions for Different Scenarios• Low Level
– Less than a week’s notice before the data is given to the commander.
– Only imagery available will be off-the-shelf data.– Not detailed
• Medium Level– Four weeks of contingency planning time was available prior to the
operation– Better imagery will allow for elevation, precise base images,
apparent large features.
• High Level– Air and Ground control over the area for at least two months.– Availability of LIDAR collection equipment and cameras
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Levels of Detail
Low Medium High4 Meter Image Roads Key Features (Cultural, Landmarks)DTED2 Railroads Vertical Obstruction Points
Bridges Information PageRunways Ground PhotosWater Features (Lines and Polygons) Buildings of InterestForested Areas RoadsOpen Urban Areas RailroadsResidential Built-up Terrain Zones BridgesCommercial Built-up Terrain Zones RunwaysInstitutional Built-up Terrain Zones Water Features (Lines and Polygons)1 Meter Image (Quickbird view) Forested AreasDTED 2 Elevation Open Urban Areas1:50K Military Overview Map Residential Built-up Terrain Zones4 Meter Image Commercial Built-up Terrain Zones
Institutional Built-up Terrain Zones1 Meter ImageDTED 2 Elevation1:50K Military Overview Map4 Meter ImageLIDAR
Levels of Terrain Layers
Lay
ers
of
Det
ail
Wit
hin
th
e D
iffe
ren
t L
evel
s
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Low
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Low (close up)
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Medium
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Medium (close up)
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High
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High (close up)
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Assumptions
Data Generation Assumption• A Team can produce a Medium Density product
given:– 8 hour working days (Monday-Friday)– Minimal breaks– Trained Professionals who know how to create the database– Teams of 4 analysts are constantly available– Urban area that is 15 x 15 kilometers with a 3 to 4 kilometer
“suburban” area
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Cost Data Matrix
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Digital Terrain Elevation Data(DTED)
• From DTED 5 to 1 the storage space required decreases to between 8-10% of the previous level.
• Only about a 24 hour difference in man hours between best and worst.
• Biggest concern is Operational status pre-deployment to boots on ground.
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Level Effectiveness
12
3
0
10
20
30
40
50
60
70
80
90
100
Mission Planning
Effectiveness
Exercise Level of Detail
Terrain Data Layer vs. Mission Planning Effectiveness
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Cost Analysis
Cost Analysis
00.10.20.30.40.50.60.70.80.9
1
0.0000 0.2000 0.4000 0.6000 0.8000 1.0000 1.2000
Cost
Val
ue
Hours
Storage
Operational
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Conclusion (Data Analysis)
• Data Development– Feature layers are manpower intensive
• Roads, vegetation, and urban areas are easiest to create• Marshes, streams, and rivers are most difficult to create• Categorization of urban areas requires human intelligence
• Analyzed Elevation in the Cost Analysis– Level 1 to Level 2
• 55% Increase in Value for a 10% Increase in Storage Cost
– Level 2 to Level 3• 25% Increase in Value for a 90% Increase in Storage Cost
– Analyst Hours stay constant throughout Cost Analysis.
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Future Work
• Continue to Analyze the Cost versus Value– Individual attributes at varying levels of detail– Individual cost for varying attributes
• Advisor and LTC Hendricks will continue work in Ft. Bliss
• Move to gain an understanding between FCS and TEC
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Questions