本文選題：大數(shù)據(jù) + PSPL調研法��； 參考：《華南理工大學》2014年碩士論文

【摘要】：2013年1月29日，隨著住房和城鄉(xiāng)建設部公布首批90個國家智慧城市試點名單，標志著我國智慧城市發(fā)展進入規(guī)模推廣階段。基于數(shù)據(jù)反饋的城市建設是其關鍵要素。用于數(shù)據(jù)收集、整理、分析的傳統(tǒng)調研方法由于具有樣本量小、隨機性不強、準確性差等原因越來越不適應不斷發(fā)展的科學需要。如何提高數(shù)據(jù)樣本的科學指導意義，讓其在智慧城市的建設中發(fā)揮作用是迫切需要解決的問題。 隨著智慧城市的推廣，大數(shù)據(jù)研究作為近年來的熱點詞匯漸漸走入人們的視線。這種大量各種類型的數(shù)據(jù)進入數(shù)據(jù)庫，經(jīng)過組織、分析、決策之后，將最后的處理結果提供給決策者參考形成了完整的大數(shù)據(jù)流程。傳統(tǒng)調研方法的訪談法、觀察法等進行配合及補充，，為城市設計者提供具有指導意義的數(shù)據(jù)。 以實際案例研究大數(shù)據(jù)與傳統(tǒng)調研方法相結合指導城市公共空間設計的基礎上，嘗試將它結合我國具體國情進行轉化，以期完善我國的智慧城市特別是城市公共空間設計研究，推動城市街區(qū)建設，構筑更和諧城市。 本論文分為六章進行研究。 第一章介紹大數(shù)據(jù)理論產(chǎn)生的時代背景，對其關鍵概念進行界定，對相關理論及研究成果進行分析整理，最后確定本論文的研究方法及技術路線。 第二章對大數(shù)據(jù)與傳統(tǒng)調研方法的關系進行分析。一方面回顧了美國數(shù)據(jù)的發(fā)展歷程，闡述了大數(shù)據(jù)的價值，并介紹了大數(shù)據(jù)時代下的城市規(guī)劃。另一方面介紹了公共空間設計中的傳統(tǒng)調研方法。最后總結了兩者的區(qū)別與互補優(yōu)勢。 第三章闡述了美國Santa Monica主街區(qū)（Main Street）公共空間現(xiàn)狀調研。介紹了項目背景以及分別利用大數(shù)據(jù)及傳統(tǒng)PSPL調研法獲取的公共空間現(xiàn)狀。 第四章提出了該項目的規(guī)劃設計。分別從理論建構、設計策略和改造建議方面闡述作者自己的設計方式。 第五章對大數(shù)據(jù)與傳統(tǒng)調研相結合的城市公共空間設計提出批判性思考，結合我國的數(shù)據(jù)發(fā)展歷程，提出其啟示作用。
[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.
【學位授予單位】：華南理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TU984.114

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