Reducing Digital Geographic Images to Solve Problems of Regional Management Information Support

Abstract

Geographic information systems are often used to support decision-making in regional governance. Geoimages synthesized by GIS are an important source of information for decision makers. However, many modern GIS synthesize redundant geoimages from the point of view of the problem being solved. Analysis of redundant geoimages complicates the work of the decision maker. To solve this problem, it is necessary to perform geoimage reduction in accordance with the features of the problem being solved by the user. This paper describes the first step in developing an approach for reducing geoimages synthesized by geographic information systems. A feature of this approach is that during reduction, a change in the level of informativeness of the geoimage is taken into account. Informativeness is evaluated on the basis of a pragmatic measure of information that characterizes the subjective usefulness of a geo-image for solving a problem by a user. The main results of the first step in developing approach to geoimage reduction are the formalized statement of the problem, as well as the user model, the problem model, and the geoimage model. These models represent a methodological basis for further software implementation of geoimage reduction procedures.