基于空间句法与机器学习的中国古典园林空间指征分析框架建构  

Construction of an Analytical Framework for Spatial Indicator of Chinese Classical Gardens Based on Space Syntax and Machine Learning

作　　者：陈星汉 于瀚婷 熊若璟 叶宇[1,2,3] CHEN Xinghan;YU Hanting;XIONG Ruojing;YE Yu(the College of Architecture and Urban Planning(CAUP),Tongji University;the Key Laboratory of Ecology and Energy-Saving Study of Dense Habitat,Ministry of Education,Tongji University;Built Environment Technology Center,Tongji University)

机构地区：[1]同济大学建筑与城市规划学院 [2]同济大学高密度人居环境与生态节能教育部重点实验室 [3]同济大学建筑与城市规划学院建成环境技术中心

出　　处：《风景园林》2024年第3期123-131,共9页Landscape Architecture

基　　金：国家自然科学基金“基于多源数据和深度学习的公共空间品质评价模型与设计支持研究”(编号52078343);国家重点研发计划“基于文脉保护的城市风貌特色塑造理论与关键技术”(编号2023YFC3805503)。

摘　　要：【目的】中国古典园林空间一直以来难以被量化测度,空间句法的兴起使得相关研究向定量化发展,但既有研究与经典理论的融合度仍显不够,且空间特征分析的系统性有待加强。有必要提出一套系统的空间指征分析框架,以支持对古典园林空间的量化测度。【方法】对中国古典园林空间研究的经典理论进行归纳,使用DepthmapX对园林空间的可视层、可行层模型的各项视域分析指标进行计算,通过叠加分析对空间指征进行测度,借助DBSCAN算法实现对各空间指征聚类特征的识别。以留园、拙政园为例进行分析,并开展感知试验以验证其科学性。【结果】提出了兼顾人本感知和可测度的5项空间指征:渗透性、曲折度、可视性、可达性和差异度。空间指征的分析框架得到了案例研究与感知试验的支持。【结论】搭建了一套可操作、易推广的能够系统地提取、刻画并解释古典园林空间特色的指征分析框架,实现了量化分析工具和经典理论的深度融合,探索了中国古典园林空间量化研究的新可能。[Objective] Existing explorations of Chinese classical gardens have predominantly relied on qualitative analysis. The emergence of quantitative research using space syntax has offered a solution to this issue. Although the applicability of space syntax has been validated with eye-level and knee-level application patterns being explored, most of such applications lack systematic and in-depth analysis, thereby limiting their practical effectiveness. To address these issues, this research aims to integrate classical theory with quantitative methods. By extracting spatial indicators from classical theories, this research constructs a framework using quantitative methods such as space syntax and machine learning. Starting from the human perceptual level, this research aims to systematically measure the spatial indicators of classical gardens that were previously deemed “immeasurable”, while also supporting design practice.[Methods] Theoretical framework: This research utilizes classic theoretical works to extract and summarize five spatial indicators that characterize the uniqueness and perceptibility of garden space: permeability, curvature, visibility,accessibility, and differentiation. To incorporate quantitative analysis, a multiindicator overlay technique is employed to combine spatial indicators, spatial perception experience, and the meaning of visibility graph analysis(VGA)indicators. This approach presents a mapping framework that links indicators to spatial perception and VGA indices. Technical methods: To measure the indicators, VGA is combined with DepthmapX for research on the eye-level and knee-level models of garden space, which involves the calculation of such VGA parameters as connectivity, visual step depth, and integration. ArcGIS is then used to normalize different VGA index values and perform multi-model and multiindex superposition analysis concerning the mapping framework for spatial indicators, achieving preliminary measurement of spatial indicators. The densitybased spatial clustering of a

关 键 词：中国古典园林 量化研究 空间指征 空间句法 机器学习 

分 类 号：TU986[建筑科学—城市规划与设计]