Fitness for Use - to Support Military Decision Making

Edward J. Wright
Information Extraction and Transport, Inc.
1911 N. Ft. Myer Dr., Suite 600
Arlington, VA, USA, 22209

“Determining fitness for use is solely the user's responsibility.” These, or similar words, are common in the licenses or disclaimers associated with most government or commercial producers of spatial data. Unfortunately, the user, who is often not an expert on spatial data or spatial data quality, has no tools or methodology for accomplishing this fitness for use determination. This paper presents results of research to develop technology and a methodology that allows users to evaluate how well uncertainty in the spatial data translates into risk in operational decisions of interest to the user. A prototype application based on this research has been integrated with a commercially available GIS software package. The approach starts with the user definition of the spatial data to be evaluated and the decision process that the data supports. Although we know there is uncertainty in the data, it is initially declared to be “truth” data, and is used to make a baseline decision. Next we have developed error models that represent the data quality attributes of the spatial data layers for the features of interest to the user. The error models handle discrete  and continuous data, and include spatial correlation. Additional models define the relationships between geographic features, and the influence of geographic features on parameters of the error models. We have implemented algorithms to generate simulated spatial data which varies from the assumed ground “truth” data in a way that is consistent with the relationship and error models. The simulated data is used as input to a simulated decision process and the result of the decision is then implemented on the “truth” data and compared to the baseline decision. The differences in results are in an operational dimension that the user understands. Because this is a stochastic process, the process is automated and repeated a large number of times. Graphical displays allow the user to assess the impact of the data uncertainty on operational decisions. This paper describes error models and relationship models, and an example of an experiment to evaluate the “fitness for use” for a military decision support product. While motivated by military applications, the research provides a tool which implements a methodology applicable to any user who must determine fitness for use of a spatial dataset.

Keywords: decision making, uncertainty, risk, probabilistic models, simulation

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português

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