Abstract
Generalization of geographic information enables cognition and understanding not only of objects and phenomena located in space but also the relations and processes between them. The automation of this process requires formalization of cartographic knowledge, including information on the spatial context of objects. However, the question remains which information is crucial to the decisions regarding the generalization (in this paper: selection) of objects. The article presents and compares the usability of three methods based on rough set theories (rough set theory, dominance-based rough set theory, fuzzy rough set theory) that facilitate the designation of the attributes relevant to a decision. The methods are using different types (levels of measurements) of attributes. The author determines reducts and their cores (common elements) that show the relevance of attributes stemming from the spatial context. The fuzzy rough set theory method proved the least useful, whereas the rough set theory and dominance-based rough set theory methods seem to be recommendable (depending on the governing level of measurement).
Highlights
Dominance-based rough set theory [dominance-based rough set method (DRST)]: attributes are expressed on an ordinal scale, which provides a specific order between the particular values of the attribute [14,15]
There is number of basic researches about rough sets theories being conducted, like relating rough sets with testors [38]. They are very interesting approaches using bireducts based on fuzzy-rough sets which allow for a reduction of dimensionality and data size at the same time [39]
One example can be a use of dynamic reducts with the FRST based attribute reduction which can be very useful for practical applications where data are gathered incrementally [49]
Summary
Generalization is a process that relies on understanding the geographical space [1] and plays a vital role in ensuring that the content of a map or a spatial database serves its goal at specified levels of detail (LoD) [2]. One of the approaches to the formalization of the generalization rules is the condition-action modeling (along with the interactive, that is human interaction modeling, and restrictive, namely constraint-based modeling, approaches) [1]. This process demands choosing of the attributes which are substantial for making generalization decisions. The selection is not just the first stage of generalization of geographical information—it is part of other operators; for example, simplifying the shape of a line relies on the selection of its proper nodes. Due to the vital role of selection, the research in this article concerns the proper selection of geographic objects
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