The overlay functions in Geographic Information Systems (GIS) are considered as one of the basic functions of these systems, and often, a variety of data stored in layers may be integrated together to generate new layers that contain useful informati
on for decision-makers. All geographic objects are stored in layers and usually rely on crisp set theory, whether, stored in a vector or raster format. In many cases, boundaries of classes or objects are not clearly defined, or when we perform classification of features into classes, the geographic objects located in the boundaries of classes could be classified into the wrong class. This research aims to develop overlay functions methodology based on fuzzy logic, reclassify the objects into fuzzy classes, and study the usability of this method to integrate data of specific phenomenon to help make optimal decisions. To implement and examine this idea, a set of Fuzzy Membership Functions was developed using the Python programming language embedded within the ArcGIS environment. Through this Fuzzy Membership Functions, the user can generate fuzzy sets and combine with each other according to one of fuzzy operations, and thus the generation of fuzzy sets allows supporting the right and reliable decision. To test the proposed fuzzy model capabilities, it has been applied in Tartous governorate to select suitable tourist facility sites in accordance with groups of factors. In summary, data integration using proposed fuzzy overlay functions can improve the reliability of data representation and thus the reliability of make the best decisions.
This research
aims to develop overlay functions methodology based on fuzzy
logic, reclassify the objects into fuzzy classes, and study the
usability of this method to integrate data of specific phenomenon
to help make optimal decisions.
