基于多源数据分析的上海街道空间宜人性测度与影响因素识别  

Measurement of Street Space Amenity and Identification of Influencing Factors in Shanghai Based on Multi-source Data

作　　者：方智果[1] 贺丽洁[2] 章丹音 FANG Zhiguo;HE Lijie;ZHANG Danyin

机构地区：[1]上海理工大学艺术设计学院,上海200093 [2]中国矿业大学(北京)力学与建筑工程学院,北京100083

出　　处：《新建筑》2021年第5期142-147,共6页New Architecture

基　　金：国家自然科学基金青年科学基金项目(51808337,51608321)。

摘　　要：选取上海市内环街道为研究案例,利用多源数据与图像分割、智能识别技术对街道物理特征、界面特征、城市功能、宏观形态四类指标及个体对街道的宜人性感知展开探索,构建数理模型对与街道感知相关的关键因子及数值进行辨别。研究发现:绿视率是影响街道宜人性的关键因子;建筑密度、高宽比对于宜人性感知具有积极影响。通过客体指标与宜人性评分进行回归分析得出适宜的空间感知的临界指标,并对上海街道设计提出指引与建议。This study investigates the streets in the inner ring of Shanghai through multi-source data and image segmentation,intelligent recognition technology to explore the physical characteristics of the street,interface characteristics,urban functions,macro morphology and the individual's perception of the street amenity and build a mathematical model to identify key factors and values related to street perception.It finds that green viewing rate is a key factor affecting the street amenity,and building density and aspect ratio have a positive effect on the perception of the amenity.Through regression analysis of object index and amenity score,it obtains the critical index of spatial perception,so as to provide guidelin es for street design in Shanghai.

关 键 词：多源数据 街道空间 量化评价 街景图像 宜人 

分 类 号：TU984.1[建筑科学—城市规划与设计]