大数据与PSPL调研法相结合的美国城市主街区公共空间调查与研究

发布时间：2018-05-30 15:16

本文选题：大数据 + PSPL调研法　；参考：《华南理工大学》2014年硕士论文

【摘要】：2013年1月29日，随着住房和城乡建设部公布首批90个国家智慧城市试点名单，标志着我国智慧城市发展进入规模推广阶段。基于数据反馈的城市建设是其关键要素。用于数据收集、整理、分析的传统调研方法由于具有样本量小、随机性不强、准确性差等原因越来越不适应不断发展的科学需要。如何提高数据样本的科学指导意义，让其在智慧城市的建设中发挥作用是迫切需要解决的问题。随着智慧城市的推广，大数据研究作为近年来的热点词汇渐渐走入人们的视线。这种大量各种类型的数据进入数据库，经过组织、分析、决策之后，将最后的处理结果提供给决策者参考形成了完整的大数据流程。传统调研方法的访谈法、观察法等进行配合及补充，，为城市设计者提供具有指导意义的数据。以实际案例研究大数据与传统调研方法相结合指导城市公共空间设计的基础上，尝试将它结合我国具体国情进行转化，以期完善我国的智慧城市特别是城市公共空间设计研究，推动城市街区建设，构筑更和谐城市。本论文分为六章进行研究。第一章介绍大数据理论产生的时代背景，对其关键概念进行界定，对相关理论及研究成果进行分析整理，最后确定本论文的研究方法及技术路线。第二章对大数据与传统调研方法的关系进行分析。一方面回顾了美国数据的发展历程，阐述了大数据的价值，并介绍了大数据时代下的城市规划。另一方面介绍了公共空间设计中的传统调研方法。最后总结了两者的区别与互补优势。第三章阐述了美国Santa Monica主街区（Main Street）公共空间现状调研。介绍了项目背景以及分别利用大数据及传统PSPL调研法获取的公共空间现状。第四章提出了该项目的规划设计。分别从理论建构、设计策略和改造建议方面阐述作者自己的设计方式。第五章对大数据与传统调研相结合的城市公共空间设计提出批判性思考，结合我国的数据发展历程，提出其启示作用。
[Abstract]:January 29, 2013, with the Ministry of Housing and Urban-Rural Construction announced the first batch of 90 national pilot list of smart cities, marking the development of smart cities in China into the stage of scale promotion. Urban construction based on data feedback is the key factor. The traditional research methods used in data collection, collation and analysis are more and more unsuitable for the development of science because of their small sample size, low randomness and poor accuracy. How to improve the scientific guiding significance of data samples and make them play a role in the construction of intelligent cities is an urgent problem to be solved. With the promotion of intelligent city, big data research has gradually come into the sight of people as a hot word in recent years. After organizing, analyzing and making decisions, the final processing results are provided to the decision makers to form a complete big data process. The interview method and observation method of traditional research methods are combined and supplemented to provide instructive data for urban designers. Based on the combination of practical case study big data and traditional research methods to guide the design of urban public space, this paper attempts to transform it into consideration of the specific conditions of our country, in order to perfect the research on the design of intelligent cities, especially urban public spaces, in our country. Promote the construction of urban blocks and build a more harmonious city. This thesis is divided into six chapters. The first chapter introduces the background of the generation of big data theory, defines its key concepts, analyzes and arranges the relevant theories and research results, and finally determines the research method and technical route of this paper. The second chapter analyzes the relationship between big data and traditional research methods. On the one hand, this paper reviews the development of American data, expounds the value of big data, and introduces the urban planning in the era of big data. On the other hand, it introduces the traditional research methods in the design of public space. Finally, the differences and complementary advantages between the two are summarized. The third chapter describes the current situation of Santa Monica main Street public space in the United States. This paper introduces the background of the project and the status quo of the public space acquired by big data and traditional PSPL. The fourth chapter puts forward the planning and design of the project. From the theoretical construction, design strategy and reform suggestions, respectively, the author's own design methods. Chapter five puts forward critical thinking on urban public space design combined with big data and traditional research, and puts forward its enlightening function combined with the data development course of our country.
【学位授予单位】：华南理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TU984.114

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