城市建筑群空间分布模式的识别方法研究

项目名称： 城市建筑群空间分布模式的识别方法研究

项目编号： No.41471386

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 天文学、地球科学

项目作者： 武芳

作者单位： 中国人民解放军战略支援部队信息工程大学

项目金额： 80万元

中文摘要： 城市建筑群空间分布模式体现了城市的物质形式及与其社会经济功能之间的关系，反映了城市的空间结构特征，对于制图综合、多尺度表达和时空数据挖掘等具有重要意义。本项目拟从定性与定量、宏观与微观、分解与组合、表象与机理、内涵与外延等多重视角，对城市建筑群空间分布模式识别的理论与方法进行深入探索。通过剖析城市建筑群空间分布的认知特性和组织规律，研究其概念模型、科学内涵、影响因素和分类体系。针对大比例尺城市建筑群空间分布模式，归纳演绎和综合其影响因素，基于视知觉原理选择视知觉变量，构建量化指标体系，计算空间参数；然后通过群目标的空间关系模型耦合连接，建立不同建筑群模式的结构化模型。通过对典型建筑群空间分布模式的探测、发现和识别，研究城市建筑群的形态特征及多尺度分异规律，挖掘其所蕴含的深层次地学知识和内在关系，揭示城市建筑群的空间分布格局，丰富面向制图综合和多尺度表达的时空数据挖掘理论与方法。

中文关键词： 城市建筑群；空间分布；模式识别；数据挖掘；数字地图综合

英文摘要： Map patterns in urban building groups reflect the interrelations between material forms of cities and their social and economic functions, as well as their spatial distribution structures, which has a great significance for cartographic generalization, multiscale representation and spatio-temporal data mining. This project aims to excavate theories and methods of recognition of map patterns in urban building groups deeply with various perspectives of quality and quantity, macrocosm and microcosm, decomposition and composition, appearance and mechanism, connotation and epitaxy etc. Map pattern conceptual model, scientific connotation, influential factors and classification system are investigated via analyzing cognitive features and organizational patterns of spatial distribution of urban buildings. For large scale urban buildings, influential dependent factors of map patterns are generalized and deducted，and visual variables based on visual perception are selected to construct quantitative index system and form spatial parameters. Then structural model of different pattern of buildings are built by the coupling spatial relation and parameters.By the investigating and exploring the morphologic features and multiscale heterogeneity of map patterns in urban building groups, this project excavates the deep-seated geo-knowledge and inner relations of map pattern, interprets the spatial arrangement of urban buildings and enriches the spatio-temporal data mining theories and methods for cartographic generalization and multiscale representation.

英文关键词： urban building groups;map pattern;pattern recognition;data mining;digital map generalization