中国工业遗产的时空分布特征与空间整合保护

Spatial-temporal Distribution Characteristic and Spatial Integrated Protection of Chinese Industrial Heritages

综合时空分布特征针对性地提出历史文化遗产的保护策略,既是国土空间规划背景下保护各地建成遗产的基本内涵,也是修复国家文化空间基因的必要举措。选取中国342处工业遗产为研究对象,运用核密度估计和社会网络分析方法,探究了工业遗产的时空分布特征、网络属性特征和空间整合保护策略。主要结论如下:(1)工业遗产发展表现出显著的阶段性特征,6个阶段的数量与门类构成差别大。(2)工业遗产空间分布不均,具有较强的“核心—边缘”特征,揭示出以胡焕庸线为界的宏观区域差异。(3)工业遗产网络的社会关联在东、中、西三大地区间差异较大,且存在着显著的分层集聚现象,遗产集群也表现出显著的“核心—边缘”特征和流域集聚特征。(4)工业遗产的空间整合保护应构建“井字轴、九节点、多集群”的网络化结构,并重点分级保护16个遗产集群。

Proposing specific strategies for the protection of historical-cultural heritages based on the characteristics of spatial and temporal distribution is not only the basic connotation of protecting the heritages under the background of the territorial space planning,but also a necessary measure to restore the national cultural space genes.Selecting 342 Chinese industrial heritages as the research objects and using the methods of kernel density estimation and social network analysis,this paper explores the spatial and temporal distribution characteristics,network attribute characteristics and spatial integration protection strategies of industrial heritages.The main conclusions are as follows:1)The development of industrial heritage shows significant stage characteristics,and the number and category composition of the six stages are very different.2)The spatial distribution of industrial heritages is uneven,with a strong"core-periphery"feature,this reveals the macro-regional differences bounded by the HU Huanyong Line.3)The social connection of industrial heritage network is quite different among three regions which are eastern region,central region and western region,and there is a significant phenomenon of hierarchical agglomeration,and heritage clusters also show significant"core-periphery"characteristics and watershed agglomeration characteristics.4)The spatial integrated protection of industrial heritage should build a networked structure of"double cross axis,nine nodes,and multiple clusters",and focus on grading protection of 16 heritage clusters.