中国传统聚落景观基因组图谱特征

传统聚落是优秀的民族文化遗产,现阶段迫切需要加强相关研究方法的探索,这对中国经济和社会发展具有重要意义。针对目前不能有效解释传统聚落景观要素与整体意象之间的关系这一问题,结合生物基因组图谱和传统聚落景观基因理论开展了景观基因组图谱的探索。根据基因的特性,首先阐述了传统聚落景观基因组的概念。在此基础上,本文提出了传统聚落景观基因组图谱的概念并分析了其与景观基因、景观基因组三者之间的关系,进一步分析了传统聚落景观基因组图谱的类型、功能和意义。根据前述理论研究成果,以湖南省具有代表性的30个传统聚落为例,构建了传统聚落景观基因组图谱的案例,据此分析了湖南省传统聚落的群系性特征;同时,以汝城金山村为例进行了传统聚落景观基因组的识别。结果表明,传统聚落景观基因组图谱对于实现传统聚落景观数字化、挖掘传统聚落的规划模式、识别不同区域的传统聚落景观特征等具有实际意义。

The conceptual model and characterizations of landscape genome maps of traditional settlements in China

Thousands of traditional settlements with prominent historical and cultural information of China are considered as the Chinese traditional treasures. They play an important role in the new tide of current social-economic development and urbanization processes of China. Recently, the Landscape Gene Theory (LGT), which aims to dissect the cultural features of traditional settlements of China, is a powerful tool for a better understanding of the landscape patterns of traditional settlements and is gaining more and more attention. Plenty of prominent cultural factors derived from the traditional settlements are identified by LGT. These are very helpful knowledge about the intrinsic cultural features implicated in the traditional settlements. However, LGT does not still cope well with the co-relationships among landscape genes of traditional settlements. Therefore, LGT cannot capture the mechanisms between the prominent cultural factors and landscape images of traditional settlements. Targeted to partly resolve this issue, this paper employs methods in genome mapping of biology and LGT to integrate into a new research framework to address these mechanisms. The framework is named as Traditional Settlement Landscapes' Genome Maps (TSLGM) according to its conception and connotation. The paper is organized in the following orders. Firstly, it makes the definition and classification of TSLGM by the theoretical fundamental and essential features of LGT. Secondly, the functionalities and academic significances of TSLGM are also highlighted. Thirdly, practical flowcharts for constructing and organizing an instance of TSLGM are brought forward. Finally, 30 well-known traditional settlements of Hunan Province of China are taken as study areas. The paper portrays the spatial pattern for the 30 traditional settlements according to their TSLGM. Furthermore, a genome pattern identification of landscape genes of traditional settlements is performed by using Jinshan village of Rucheng County as an example. To sum up, this paper indicates that TSLGM plays a paramount role in capturing characteristics of the traditional settlements, which is a potential methodological progress for LGT. From this paper, it is found that TSLGM has some potential points in traditional settlement digitalization, planning pattern mining and characteristics of regional traditional landscapes identification.