Abstract
Graphic and text are two major elements in exhibiting of the results of urban planning and land administration. In combination, they convey the complex relationship resulting from spatial analysis and decision-making. Accurately interpreting and representing these relationships are important steps towards an intelligent GIS for urban planning. This paper employs concept-hierarchy-tree to formalize graphic-text relationships through a framework of spatial object lexicon, spatial relationship lexicon, restriction lexicon, applied pattern base, and word segmentation rule base. The methodology is further verified and shown effective on several urban planning archives.
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