The development of fuzzy sets in geographic information systems (GIS) arose out of the need to handle uncertainty and the ability of soft computing technology to support fuzzy information processing. An overview of the fundamentals of fuzzy sets is used to illustrate its use in GIS. The use of some terms within both the GIS and fuzzy information processing community is clarified. Since one of t...

Fuzzy theory provides a rigorous, flexible approach to the problem of defining and computing. Therefore, to facilitate decision-making in geographic information system (GIS), the graph layer indicator and the Takagi Sugeno (TS) fuzzy model have to be integrated. This study explains several versions of the TS fuzzy model based on fuzzy theory and fuzzy operation. An inference model is constructe...

The fuzziness-based uncertainty of GIS products is studied from objective and subjective aspects respectively in this paper. From the point of view of objective aspect, the fuzziness-based uncertainty of GIS products consists of items concerning the data sources of GIS products. From the point of view of subjective aspect, the fuzziness-based uncertainty of GIS products includes human’s apprais...

GIS systems are frequently coupled with fuzzy logic systems implemented in statistical packages. For large GIS data sets including millions or tens of millions of cells, such an approach is relatively timeconsuming. For very large data sets there is also an input/output bottleneck between the GIS and external software. The aim of this paper is to present low-level implementation of Mamdani’s fu...

The spatial relationships plays an important role in GIS spatial data modeling, spatial query and spatial analysis etc. From the cognitive view, we represent and apply the information of relationships between spatial objects in the real world in computer system, study the fuzzy extension about description of spatial relationships at the base. Guided the spatial query the paper makes the model o...

The methods used in commercial GIS packages for both the representation and analysis of geographic data are inadequate, because they do not handle uncertainty. This leads to information loss and inaccuracy in analysis with adverse consequences in the spatial decision-making process. The incorporation of fuzzy set methodologies into a DBMS repository for the application domain of GIS should be b...

Topological relations have played important roles in spatial query, analysis and reasoning in Geographic Information Systems (GIS) and spatial databases. The topological relations between crisp and fuzzy spatial objects based upon the 9intersections topological model have been identified. However the formalization of the topological relations between fuzzy regions needs more investigation. The ...

In this paper, we show how standard GIS operations like the complement, union, intersection, and buffering of maps can be made more flexible by using fuzzy set theory. In particular, we present a variety of algorithms for operations on fuzzy raster maps, focusing on buffer operations for such maps. Furthermore, we show how widely-available special-purpose hardware (in particular, z-buffering in...

To obtain more flexibility and more effective capability of handling and processing imprecise information about the real world, fuzzy set theory is introduced into GIS. FuzzyCell is a system designed and implemented to enhance conventional GIS software (ArcMap®) with fuzzy set theory. Extending GIS with fuzzy logic (a linguistic approach as the model of human thinking) not only offers a way to ...

Present analytical functions and conventional cartographic modeling techniques in Geographic Information Systems (GIS) are based on Boolean logic, which implicitly assumes that objects in a spadal database and their attributes can be uniquely defined. The inherent constraint of the classical set theory does not allow for partial set membership conditions and imprecise information in GIS. The in...