China has a deep traditional culture and a long history, and is rich in traditional settlements (designated as “Famous Historic-Cultural Villages/Towns”, “Chinese Traditional Villages” by Chinese Government). To help people develop these traditional settlements to achieve the great goal of Chinese National Rejuvenation, Chinese scholar put forward the Cultural Landscape Genes of Traditional Settlements (CLGTS) in 2003. Since then, CLGTS theory has been employed to solve the issues of Chinese traditional settlements, such as the identification and regionalization of cultural landscape genes in traditional settlements, and the understanding of architectural features. Although CLGTS theory has made great strides in many application fields, there is still a lack of scientific findings in exploring the symbol mechanism from a perspective of semiotics. To explore this, we firstly examined the core features of CLGTS through a dialectical perspective. We analyzed two features of CLGTS in depth. First, CLGTS is the dialectical combination of macro settlement image and micro cultural factors of traditional settlements, material appearance and inherent traditional cultural implications, overall features and local self-renewal mechanisms, qualitative and quantitative methods, superiority of cultural factors and rich cultural connotation. Second, CLGTS is famous for its nonlinearity, self-organization, and self-iteration due to various spatial shapes and complex structures. Based on the above, we first proposed the concept of Symbolization Method of CLGTS (SM-CLGTS). Then, we further explored the key features, classification methods, and corresponding representation methods of CLGTS symbols. Finally, by using Visual C#.net program language, we developed a prototype system of the Traditional Landscape Genetic Symbol Database (TLGSD) to create and centrally manage CLGTS symbols. Test results show that TLGSD can meet the needs of constructing a CLGTS symbol database for a given region. This study is of great significance to explore and contribute to visualizing the CLGTS symbols.

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Reconstruction of 3D building objects from 2D drawings is a vital approach for 3D model reconstructing, and the key is symbol recognition of the architectural construction components in 2D graphics. Existing algorithms of graphics symbol recognition are lack of robustness, scalability and with low recognition ability to deal with graphics transformation. This study constructed Attributed Graph to express the geometrical characteristics, topological relationships and semantic characteristics of architectural drawing symbols uniformly. The recognition approach with Attributed Graph can expand easily and flexibly to deal with rotation transformation and scaling transformation. Considering the semantic mapping from drawings to models systematically, created corresponding mapping mechanism to guarantee robustness of model creating system. Achieve internal and external integration of three-dimensional architectural models automatically, by using 3Dmax modeling script. Import models to GeoDatabase, so as to using the model in 3DGIS application.