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GMU C4I Center Seminar

Importance of Understanding Uncertainty
in Geospatial Data: "Fitness for Use"
and the "Impact of using the data you have"

Dr. Ed Wright
Chief Scientist
Information Extraction and Transport, Inc.

Friday, March 9, 2007 Science & Technology II Bldg, Room 320 2:00 pm

ABSTRACT

Military planning and operations depend on maps and spatial data to provide the geometry of the battlefield. Basic terrain data themes are used in geospatial models to produce Tactical Decision Aids (TDA) that predict terrain effects on military operations. Two important TDA examples are Cross Country Mobility (CCM) and Line Of Sight (LOS). Unfortunately, all maps and digital environmental data sets, even those collected from the latest high resolution sensors, contain errors. These errors, or uncertainties, are propagated through TDA models and result in uncertainties in the TDA products used to make decisions. The problem is that commanders are unaware of the underlying uncertainties in the terrain data and the uncertainty in the TDA products that they are using. As a result, they may make critical battlefield decisions with out being aware of the potential risks. This is the explanation for a number of historical examples where terrain effects have influenced battlefield outcomes.

Problems with environmental data quality used in decision making have been recognized within the academic community, which has resulted in a call for users to evaluate the "fitness for use" of spatial data. The assumption is that if data is not "fit for use", then the decision maker will collect additional data to meet the requirements. Within the military, this option is often not possible. Due to operational constraints, commanders may be required to make decisions using the data immediately available.

This presentation makes the argument that with appropriate tools it is possible to quantify errors in spatial data, propagate these errors through TDA models, and provide commanders with appropriate information about uncertainties, so they can make better decisions. Examples using CCM and LOS products are used to illustrate the potential problems and the benefits of understanding the uncertainties in spatial data.