The work is devoted to the problem of interpretation of fuzzy semantics of cognitive descriptions of spatial relations in natural language and their visualization in a geographic information system (GIS). The solution to the problem of determining the fuzzy spatial location of an object based on vague descriptions of the observer in natural language is considered. The task is relevant in critical situations when there is no way to report the exact coordinates of the observed object, except by describing its location relative to the observer itself. Such a situation may be the result of a crime, terrorist act or natural disaster. An observer who finds itself at the scene transmits a text message, which is a description of the location of the object or place (for example, the crime scene, the location of dangerous objects, the crash site). The semantics of the spatial location of the object can be further extracted from the text message. The proposed fuzzy approach is based on the formalization of the observer's phrases, with which it can describe spatial relations, in the form of a set of linguistic variables that determine the direction and distance to the object. Examples of membership functions for linguistic variables are given. The spatial knowledge base is built on the basis of the phrases of observers and their corresponding fuzzy regions. Algorithms for constructing cognitive regions in GIS have been developed. Methods of their superposition to obtain the final fuzzy location of the object are proposed. An example of the implementation of a fuzzy model for identifying cognitive regions based on vague descriptions of several observers, performed using developed Python scripts integrated into ArcGIS 10,5, is considered.

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