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Spatial association rules mining for land use based on fuzzy concept lattice

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4 Author(s)
Jiqiang Niu ; Sch. of Urban & Environ. Sci., Xinyang Normal Univ., Xinyang, China ; Yang Zhang ; Wenjuan Feng ; Lele Ren

Spatial data mining can extract the spatial patterns and characteristics, general relations of spatial and non spatial data, and other data features in common that hidden in the spatial database. Formal concept analysis theory is very suitable for data mining research. In this paper, a fuzzy concept lattice is proposed to mine the spatial association of knowledge. The incremental algorithm and drawing algorithm of Hasse are established, and the index tree is applied in this algorithm to solve the problem of complex spatial system. This paper selects the land use database and other data of Yicheng, Hubei province, China, which are integrated by existing mathematical models. These data compose a new data set that can be mining by proposed algorithm. The fuzzy concept lattice is applied to acquire the spatial association rules of land use.

Published in:

Geoinformatics, 2011 19th International Conference on

Date of Conference:

24-26 June 2011