Similarity Of Spatial Group Objects

Spatial relationship is the relationship which determined by the geometric properties (location, shape, etc) between spatial objects, includs topological relationship, directional relationship, distance relationship and similarity relationship. As one of the basis theory of Geosciences, Spatial relationship has been pay highly attention by scholars. As one kind of spatial relationship, spatial similarity relationship plays a very important role. Do research on spatial similarity relationship is a complement to spatial relationship theory, can promote the spatial cognition, can help boost the application of spatial information, and can serve for the map generalization etc. However, in current researches, for one reason the similarity between spatial objects is difficult to assess due to the purpose of research on spatial similarity relationship is to reveal the deep-seated information and require complex analysis; for another, there are many factors need to be take into account in the assessment of similarity between spatial objects because of the complexity of the Geo-space, such as spatial relationship, spatial distribution, geometric features, semantic features and so on, result in very few researches on spatial similarity relationship. In response to this situation, take the spatial group objects as study targets, the spatial similarity relationship and the assess model between spatial group objects were studied in this paper, the specific studies include:(1) The basic theories of spatial similarity relationship were studied, include its definition, its characteristics, its classifications, and the factors which influence the spatial similarity relationship and similarity degree between spatial group objects. Based on related researches, the set theory was used to define the spatial similarity relationship; Combined with the characteristics of spatial data, the elements of spatial similarity feature sets and the key elements of this paper {spatial relationship sets, geometric feature sets} were defined, constituted the basis of this paper. Also the spatial similarity relationship's classification was described from different aspects; some related characters of the spatial similarity relationship were also described.(2) The spatial similarity relationship of spatial point cluster was researched. Point cluster object contains much structured information in spatial distribution, which is interested for the research of spatial analysis. With the consideration of Gestalt principles in visual cognition, this paper proposed a similarity assessment model which has a comprehensive consideration of point cluster's spatial relationships, spatial distribution and geometry attributes. The topology relationship of point cluster was defined using point cluster's topology neighbour, the direction relationship and distance relationship was defined using point cluster's standard deviation ellipse, and then the computation method of point cluster's topology, direction and distance similarity assessment was given out on this basis. Also the distribution range and the distribution density of point cluster and their similarity assessment method was put forward. Finally the formal five factors were combined to do a whole assessment of point clusters similarity.(3) The spatial similarity relationship of spatial line group was researched. Based on Spatial statistical characters, the spatial relationships and geometry features of line group were described. The conceptual neighborhood network of topological relationships between lines was used to define topology similarity between line groups, the directional mean was used to define direction similarity between line groups, their circular variance was used to define distance similarity between line groups; Combined with the length, average length, density and tortuosity of line group, a computation model for similarity assessment between line groups was established. The factors mentioned earlier were combined to do a whole assessment of line group similarity.(4) The spatial similarity relationship of spatial polygon group was researched. The conceptual neighborhood network of topological relations between polygons was used to define topology similarity between polygon groups; A proper "dimensionality reduction" treatment was used for polygons of different types to change polygon groups to line groups, then the directional mean was used to define direction relations between line groups namely direction similarity of polygon groups, their circular variance was used to define distance relations between line groups namely distance similarity of polygon groups; Combined with the length, average length, area, average area, density and compactness of polygon group, a computation model for similarity assessment between polygon groups was established.(5) The spatial similarity relationship of spatial scene was researched. Some improvements were made based on Bruns-Egehnoefr Model and Li-Fonseca (TDD) Model. An improved Conceptual neighborhood of topological relations was used to compute the topological similarity between spatial scenes, the conceptual neighborhoods of directional relations was used to compute the directional similarity between spatial scenes, the conceptual neighborhoods of distance relations was used to compute the distance similarity between spatial scenes, finally the 3 factors were combined together to do a whole assessment of spatial scenes.(6) In the experiment section, based on the first law of geography, the "distance" was interpreted as "scale distance" "spatial proximity" and "temporal proximity" respectively, we can get the different performance of spatial group objects in different scale, different spatial proximity and different temporal proximity. The experiments of point cluster in multi-scale, line group in different space proximity and polygon group in different temporal proximity were carried out to verify the similarity assessment model proposed by this paper, and the potential application was also proposed.