Accession Number:

ADA495794

Title:

Generating Imagery for Forecasting Terror Threats

Descriptive Note:

Technical article

Corporate Author:

NAVAL RESEARCH LAB WASHINGTON DC ADVANCED INFORMATION TECHNOLOGY BRANCH

Personal Author(s):

• Schmidt, Greg
• Goffeney, Jason
• Dalton, Jason
• Willis, Ruth

Report Date:

2006-01-01

Pagination or Media Count:

3.0

Abstract:

Maps indicating threat levels based on key feature proximity and incorporating event location uncertainty are useful for planning countermeasures in the global war on terrorism. Intelligence analysts and military planners need predictions about likely terrorist targets to better plan the deployment of security forces and sensing equipment. The authors have addressed this need using Gaussian-based forecasting and uncertainty modeling. Their approach excels at indicating the highest threats expected for each point along a travel path and for a global war on terrorism mission. It also excels at identifying the greatest-likelihood collection areas that would be used to observe a target. Their methods are extensions of Donald Browns work on geospatial analysis and asymmetric-threat forecasting in the urban environment. He showed how to extract distinct signatures from associations made between historical event information and contextual information sources such as geospatial and temporal political databases. The authors have augmented this method to include uncertainty estimates associated with historical events and geospatial information layers.

Descriptors:

• *THREATS
• *TERRORISM
• *MAPS
• *PREDICTIONS
• *IMAGES
• *IMAGE PROCESSING
• *TARGETS
• *FORECASTING
• CONFIDENCE LEVEL
• HISTORY
• MONTE CARLO METHOD
• INTELLIGENCE
• UNCERTAINTY
• POSITION(LOCATION)
• URBAN AREAS
• ALGORITHMS
• COMPUTERIZED SIMULATION

Subject Categories:

• Cartography and Aerial Photography
• Computer Programming and Software
• Cybernetics
• Military Intelligence
• Unconventional Warfare

Distribution Statement:

APPROVED FOR PUBLIC RELEASE