Affiliation:
1. LIASD, University of Paris 8, France
2. CReSTIC, University of Reims Champagne-Ardenne, France
Abstract
When analyzing spatial issues, it is often that the geographer is confronted with many problems concerning the uncertainty of the available information. These problems may appear on the geometric or semantic quality of objects and as a result, a low precision is considered. So, it is necessary to develop representation and modeling methods that are suited to the imprecise nature of geographic data. This leads proposing recently F-Perceptory to manage fuzzy geographic data modeling. From the model described in Zoghlami, et al, (2011) some limits are relieved. F-Perceptory does not manage fuzzy composite geographic objects. The paper shows proposition to enhance the approach by the managing this type of objects in modeling and its transformation to the UML. On the technical level, the object modeling tools commonly used do not take into account fuzzy data. The authors propose new functional modules integrated under an existing CASE tool.