Affiliations: [a] College of City and Environmental Science, Tianjin Normal University, Xiqing, Tianjin, China
| [b] Honghe Branch of Yunnan Provincial Tobacco Company, Hotspring Road, Mile, Yunnan, China
Correspondence:
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Corresponding author. Jifa Guo, College of City and Environmental Science, Tianjin Normal University, 393#, Binshui West Road, Xiqing District, Tianjin, China. Tel.: +86 02223766313/15900243684; E-mail: [email protected].
Abstract: The division of internal structures and external space of geographical entities is foundation of spatial analysis, query and reasoning. Most current division methods are crisp, and inconsistent with human cognitive habits. Usually existing geographic information systems(GISs) analyze spatial data directly by certain spatial analysis methods and then use natural language or words to explain analysis results, so the encoding process is absence but it is necessary in intelligent GIS (IGIS). Fuzzy geographical entities and phenomena occur throughout the real world, and these semantics of words related spatial locations and relations usually involve uncertainties. First, the geographical perceptual computing (GPC) model based on CWW is proposed and it includes four modules: input, geo-encoder, geographical CWW engine and geo-decoder. Then, the trapezoidal fuzzy set is adopted to represent spatial words. A fine fuzzy spatial partitioning model of line objects based on CWW is proposed. The interior of a line object is divided into several parts according to fuzzy logic and human cognitive habits. The exterior of a line entity is then divided into several parts by combining direction relation and distance relation models with fuzzy logic methods. This model provides a full natural language description of the interior and exterior of crisp or fuzzy line entities and consistent with human cognitive habits. An application case of this model is provided in the last and proves the superiority of this model.
