Urban Big Data and the Development of City Intelligence

This study provides a definition for urban big data while exploring its features and applications of Chi- na＇s city intelligence. The differences between city intelligence in China and the ＂smart city＂ concept in other countries are compared to highlight and contrast the unique definition and model for China＇s city intelligence in this paper. Furthermore, this paper examines the role of urban big data in city intel- ligence by showing that it not only serves as the cornerstone of this trend as it also plays a core role in the diffusion of city intelligence technology and serves as an inexhaustible resource for the sustained development of city intelligence. This study also points out the challenges of shaping and developing of China＇s urban big data. Considering the supporting and core role that urban big data plays in city intel- ligence, the study then expounds on the key points of urban big data, including infrastructure support, urban governance, public services, and economic and industrial development. Finally, this study points out that the utility of city intelligence as an ideal policy tool for advancing the goals of China＇s urban de- velopment. In conclusion, it is imperative that China make full use of its unique advantages-including using the nation＇s current state of development and resources, geographical advantages, and good hu- man relations-in subjective and objective conditions to promote the development of city intelligence through the proper application of urban big data.

Multi-source Data-driven Identification of Urban Functional Areas:A Case of Shenyang,China

Urban functional area(UFA)is a core scientific issue affecting urban sustainability.The current knowledge gap is mainly reflected in the lack of multi-scale quantitative interpretation methods from the perspective of human-land interaction.In this paper,based on multi-source big data include 250 m×250 m resolution cell phone data,1.81×105 Points of Interest(POI)data and administrative boundary data,we built a UFA identification method and demonstrated empirically in Shenyang City,China.We argue that the method we built can effectively identify multi-scale multi-type UFAs based on human activity and further reveal the spatial correlation between urban facilities and human activity.The empirical study suggests that the employment functional zones in Shenyang City are more concentrated in central cities than other single functional zones.There are more mix functional areas in the central city areas,while the planned industrial new cities need to develop comprehensive functions in Shenyang.UFAs have scale effects and human-land interaction patterns.We suggest that city decision makers should apply multi-sources big data to measure urban functional service in a more refined manner from a supply-demand perspective.

Shanghai "Maker" Urban Culture Construction in the Context of Big Cloud Movement

Shanghai should orient its development to becoming a global science and technology innovation center. Now,it plans to launch a strategic research of new round of development in 2050,carry out future urban planning research in 2040,and started start the implementation of thirteenth five-year development planning research. In this process,it is required to fully consider the impact of a new round of scientific and technological revolution and industrial reform,include the construction of global innovation center into the layout of the future development of Shanghai,formulate global scientific and technological innovation center development strategy,and further make clear the leading and support function of scientific and technological innovation to economic and social development of Shanghai. This paper analyzed the relationship between Big Cloud Movement and " Maker",and the necessities for cultivating " Maker" urban culture to building Shanghai global scientific and technological innovation center. On this basis,it elaborated and analyzed how to integrate the Maker Culture into Shanghai urban culture. Finally,it came up with recommendations for establishing Shanghai " Maker" urban culture.

Impact of Big Events on Urban Renewal Based on Urban Catalyst Theory: A Case Study of 2016 Rio Summer Olympics and 2010 Shanghai World Expo

With the acceleration of the process of economic globalization and information synchronization, every major event is accompanied by the simultaneous renewal of the city. In the era of urban development, the launch of major events is also for the renewal and development of the city. 2016 Rio Summer Olympics and 2010 Shanghai World Expo are taken as the research objects. Through the analysis of urban renewal from the perspective of the role of big event catalyst, it is verified that the big event catalyst has a positive impact on urban renewal, transportation, industrial transformation and other aspects. Moreover, it tries to combine the theory of urban catalyst to analyze its inspiration for the Beijing Winter Olympic Games, hoping to play a catalytic role in accelerating the urban renewal and transformation of Beijing and the reorganization of urban structure.

Distribution Pattern of Urban Housing Price Based on Multiple Big Data:A Case Study of Beijing,Shanghai,Guangzhou,and Wuhan

The housing price has been paid close attention by people in all walks of life,and the development of big data provides a new data environment for the study of urban housing price.Housing price data of four national central cities (Beijing,Shanghai,Guangzhou and Wuhan) are taken as research samples.With the help of software GIS,exploratory spatial data analysis method is used to depict the spatial distribution pattern of urban housing price,and commonness and difference of spatial distribution of housing price are explored.The conclusions are as below:①regional imbalance of housing price in national central cities is significant.②Spatial distribution of urban housing price in Beijing,Shanghai,Guangzhou and Wuhan presents a polycentric pattern,and there is obvious spatial agglomeration.③The internal change of housing price in different cities has significant spatial difference.Beijing,Shanghai,Guangzhou and Wuhan are taken as typical city samples for research,with reference and practical significance,which could help to effectively predict spatial development trend of housing prices in other first and second tier cities.The research aims to provide certain reference for the government implementing real estate control policies according to local conditions,project location and reasonable pricing of real estate developers.

How to Teach Urban Big Data

For an urban planning perspective,industrial revolutions have always represented a disruptive moment in lives of cities.What will be the impacts of this fourth industrial revolution in the training of urban planners?This paper aims to investigate the contribution of Urban Big Data within the curricula of the Schools of Architecture.Adopting a qualitative and quantitative approach to analyze the syllabi of the schools of architecture,this work presents a first picture of the different approaches of this promising teaching subject,to foster a discussion on the different visions proposed to forge the next generation of town planner practitioners.

笔谈:数字化为文明赋彩——文物和文化遗产数字技术应用现状与实践路径

数字技术在文化遗产领域的应用已从最初的信息储存和传输,发展到数据处理分析,进而进化到今天的自动化和智能化处理与展示,在文化遗产研究、记录、保护、利用等方面起到了至关重要的作用。当前,我国基本形成覆盖文物保护工作全链条的数字化解决方案,并不断创新核心技术与设备,形成通用技术与国际并驾齐驱、特色技术引领国际潮流的发展趋势。数字技术在考古遗址三维空间信息的获取、分析、模拟、研究和展示等全过程中发挥着重要作用,为古代遗址与自然环境之间的人地关系等研究开辟了新的途径。新一代测绘技术,可实现对建成遗产三维数字形式的记录与保存,在精度、纹理、展示分析、交互以及文物古建的数字修复等方面具有不可替代的价值。通过“空间历史大数据”途径,可以打破过往人文学科与空间操作之间的知识鸿沟与技术壁垒,促进文化遗产以体系化技术操作实现“公众化”,通过文化空间实践达成未来城乡高质量发展和历史人文知识存续之间的良性互动。数字化实践在非物质文化遗产保护中的应用范围在不断扩大,已然从保存、宣传扩展到传承、振兴的层面。从全球视野审视数字化这一新兴领域的发展历程和前沿动态,文化遗产数字化面临着建立更完善的数据资源等挑战。

智能城市规划的理论与技术机制探索

为预判智能城市规划未来发展趋势,研究了既有城市规划研究模式及其中的技术机制与技术流程.在现代城市规划研究模式的发展历程中,先验模式、循证模式、定量模式和智能模式4种模式的传承与迭代呈现螺旋式发展特征.相较传统,智能城市规划的技术机制着眼于城市规划的全链条,呈现自动化集成的特征.智能城市规划的流程包含智能分析、智能规划、智能管控3个阶段,具体包括智能城市感知、智能洞察识别、智能模拟仿真、智能稳态预测、智能规划生成、智能交互优化、智能公众参与、智能规划审批和智能规划管控9个技术模块.未来,智能城市规划需进一步依托人工智能大模型技术的发展,增强可解释性,逐步实现智能化的先验与循证,针对城市问题提出创新、可信、可行的智能化解决方案.

信息消费何以赋能城市活力?——基于需求侧和供给侧的双重视角

中国正处于实施城市更新行动与践行人民城市理念的关键时期,信息消费作为重要的新兴消费领域,对满足多样化、高品质的消费需求,提升城市活力、人居品质发挥着重要的作用。本文以国家信息消费试点政策为准自然实验,选取相关统计数据与开源大数据,运用多期双重差分模型实证检验了信息消费赋能城市活力的影响效应。研究结果显示:(1)信息消费试点政策能够提高试点城市的活力水平。这一结论在替换被解释变量、克服内生性问题、排除异质性处理效应与控制国家智慧城市试点政策等一系列稳健性检验后依然成立。(2)信息消费试点政策主要从供需两端推动城市活力提升,需求侧提高消费需求效应,供给侧信息产业集聚、创新促进与信息基础设施建设是影响城市活力的重要途径。(3)信息消费试点政策的城市活力提升效应在行政等级更高、地理区位更具优势、城市规模更大以及经济发展水平更高的城市更为明显。(4)信息消费试点政策对城市活力的提高具有正向空间溢出效应。本文的研究结论为加速释放信息消费潜力,促进信息消费扩容提质,推动城市高质量发展和现代化建设提供了政策依据。

城市文化特色重塑影响因素与提升研究——以保定“全国书院之城”建设为例

党的十八大以来,党中央和国务院启动了新型城镇化建设,城市文化建设得到加强并从广泛性挖掘转为更加注重自身特色的重塑与提升。河北省保定市作为第二批国家历史文化名城,在其丰富的历史文化资源中深入挖掘“书院”这一特色资源,是政治、经济、历史文化、社会因素共同作用的结果。保定市作为全国范围内率先提出要打造“全国书院之城”的城市,为其他城市文化特色重塑与提升提供了一定的经验启示:地方政府应明确城市未来规划与立法方向、建立健全主体间的协同治理体系、重视机制创新、按照人民城市建设的原则寻找特色文化与其他城市文化品牌的交叉点,在突出特色文化的同时,实现多元城市文化品牌的融合发展。

大数据战略视角下数字经济对城市生态效率的影响研究

以数据为关键要素的数字经济已成为中国式现代化的新引擎,为新质生产力跃升提供持续性的创新动力和重要支撑,并赋能生态效率提升和绿色可持续发展。基于2011—2021年中国277个地级市的面板数据,运用SBM—GML模型,构建多维投入和产出指标体系,测算城市生态效率,以国家级大数据综合试验区为政策评估对象,实证检验数字经济发展对城市生态效率的影响及作用机制。研究发现:数字经济发展可以提高城市生态效率,该结论经过一系列稳健性检验依旧成立。数字经济发展能够提高绿色创新能力和人工智能水平,进而提升城市生态效率。国家级大数据综合试验区试点效果随着试点城市生态效率水平的提高而逐渐增强,且其因知识产权、城市区位的不同而存在政策效果差异。从空间演变特征来看,数字经济发展产生的“溢出效应”大于“虹吸效应”,总体上呈现正向的空间溢出效应。

北京市职住失衡驱动因素研究及其对雄安新区规划的启示

职住失衡是近年来国内城市治理领域常见的“大城市病”之一,北京市尤为典型与严重,其成因与治理经验对新城规划有重要借鉴意义。我们采用“昼夜人口比”作为职住失衡水平的测度,发现由于城市产业结构的空间布局由核心城区向外围郊区扩散的速度暂未能跟上人口向外围转移的速度,考察期内北京市整体职住失衡程度趋于加剧,核心城区越来越偏向工作区,而外围郊区尤其是近郊区县则愈加偏重居住功能。基于2005—2021年北京市16区县面板数据模型的一系列实证研究发现:区县房价收入比越高,该区县越倾向成为常住人口流出的工作区;而地铁开通以及教育、医疗、零售市场的发展则会吸引居住人口流入,使之更偏向于居住而非工作的“睡城”,且该影响在去除了密云、延庆、平谷三个远郊区县后更为显著;各因素对核心城区与近郊区职住比的影响存在显著差异。雄安新区等国内新城规划时应注意借鉴北京经验,通过在城市区域内多点均衡配置优质产业、平衡区域间房价与房租差距、设置网格状交通系统等措施预防严重职住失衡现象。

城市轨道交通系统的层次化功能结构解析——以上海为例

解析城市轨道交通系统的功能结构对于建立以轨道交通为骨架的城市空间结构至关重要,其有助于优化城市空间布局,促进交通与土地利用融合,进而推动城市可持续发展。本文利用交通刷卡大数据,基于轨道交通站域的功能相似性和邻接关系提出了功能站组的概念,并形成了一套“站域功能分类—站组范围划定—站群结构识别”的方法体系。以上海市轨道交通系统为例,针对单个站域,构建表征站域土地利用功能的连续客流时间序列,并依据时间序列特征分类得到站域功能类型;将多个具有相似的出行模式和土地利用功能的相邻站域划定为功能站组;以功能站组为基本单元,采用社区发现算法,对功能站组间的客流交互网络进行分析以识别站群。研究结果表明,城市轨道交通系统的“站域—站组—站群”层次化功能结构解析方法综合了场所空间和流空间视角,有助于认识特大城市轨道交通系统的功能结构特征,并为轨道交通系统的发展提供多层次的空间优化建议。

基于物联网大数据的智慧城市可持续建设研究

文中针对智慧城市建设可持续发展与规划的重要意义和重大影响,利用物联网和大数据分析技术,提出了一种以物联网和大数据分析为基础的智慧城市可持续发展规划与建设框架。首先,设计了一种基于物联网的异构聚合智慧城市架构;然后,对框架进行了大数据分析与探讨;最后,利用HadoopEco系统,对数据吞吐率曲线与数据量大小进行了评估,验证了所提框架的实用性和先进性。

高速公路对城市多中心空间结构的影响

城市道路的发展是城市空间发展的根本动力,基于2001—2019年LandScan高分辨率全球人口分布数据构建了多组多中心空间结构指标,并利用历史交通路线、规划路线等工具变量,系统识别了高速公路对多中心空间结构的影响效应。结果表明,多中心已经成为中国城市空间结构的主要发展趋势,射线状或外围过境的高速公路能够提升外围地区的区位优势,通过集聚土地、开发区、企业和人口要素的途径来加速空间结构从单中心向多中心转变,这一结论在更换变量、限制样本、消除内生性、非线性回归等一系列稳健性检验后始终成立。此外异质性分析结果显示,高速公路对大城市和东部、南方城市多中心空间结构的塑造作用更大;特别地,地方政府财政能力本身越强,越有利于城市塑造出多中心空间结构,但也会弱化高速公路对多中心空间结构的塑造效应。

基于微服务架构的城市土壤污染物联网监测及可视化系统研发

土壤污染具有累积性、隐蔽性、潜在性和不可逆性,对城市土壤污染进行预防和科学系统的监测至关重要。传统监测方法存在时效性差、数据处理能力有限等问题,无法满足城市土壤污染预防和科学系统监测的需求。本研究旨在开发一套能够实时在线监测、处理和分析城市土壤污染数据的系统,以提高预测和预警的时效性。基于微服务框架Spring Cloud Alibaba,整合开发基于EMQX平台的订阅端,实现土壤数据的采集和入库。同时,开发与Geoserver服务器对接的WebGIS功能模块,利用OpenLayers渲染地图和土壤元素浓度图,实现对土壤状态的监控和可视化分析,进而实现对土壤污染的预测和预警。突破相关监测元素的传感器技术,可以实现城市土壤污染的物联网实时在线监测,处理和分析土壤污染数据,显著提高土壤污染预测和预警的时效性。

生命的悲剧意识:关于“苦”的符号学漫谈

从符号学的视角看,悲剧意识赋予生命中的种种痛苦以意义,由此将这些苦“识别为”并“创造成”悲剧经验。悲剧现象可以从“历苦”(经验)、“知苦”(理解/阐释)、“述苦”(表征/再现)三个方面加以理解。这三个方面的划分,是以悲剧现象作为意义生成的具体例子而做出的。举凡意义生成,均发生在相对独立的个体身上,个体作为意义的主体和生成场而存在。“苦”与“消苦”的努力,也只能在主体上完成。因为符号活动,主体在意义生成的过程中,面临着“双重符号悖论”。但符号活动并非生命唯一必要的标准属性。对这一问题的反思,能够为理解生命的悲剧意识提供一个独特的切入点。

Modeling urban scale human mobility through big data analysis and machinelearning

In the United States,the buildings sector consumes about 76%of electricity use and 40% of all primary energy use and associated greenhouse gas emissions.Occupant behavior has drawn increasing research interests due to its impacts on the building energy consumption.However,occupant behavior study at urban scale remains a challenge,and very limited studies have been conducted.As an effort to couple big data analysis with human mobility modeling,this study has explored urban scale human mobility utilizing three months Global Positioning System(GPS)data of 93,o00 users at Phoenix Metropolitan Area.This research extracted stay points from raw data,and identified users'home,work,and other locations by Density-Based Spatial Clustering algorithm.Then,daily mobility patterns were constructed using different types of locations.We propose a novel approach to predict urban scale daily human mobility patterns with 12-hour prediction horizon,using Long Short-Term Memory(LSTM)neural network model.Results shows the developed models achieved around 85%average accuracy and about 86%mean precision.The developed models can be further applied to analyze urban scale occupant behavior,building energy demand and flexibility,and contributed to urban planning.

基于公交数据融合的城市人群移动模式识别——以重庆市中心城区为例

揭示城市人群移动模式对理解人群移动行为、优化城市空间结构和解决交通问题具有重要意义。针对传统问卷方式存在数据量少、准确性差、实时性不足等问题,该文融合公交刷卡、公交GPS、公交线路和轨道交通刷卡数据,提出一种数据驱动的城市人群移动模式识别方法。首先,对多源公交数据进行匹配融合,提取公交、地铁联运的城市人群移动OD,再进行稳定居住地和稳定工作地识别,最后以稳定职住地匹配判别出行语义,识别居民通勤、购物、聚餐等社会活动出行模式。利用重庆市中心城区连续1周的公交数据进行验证,实验结果显示:①重庆市中心城区人群出行主要集中在工作日,且出行人数随出行频率的增加而降低;②79.34%的人群出行呈现“两点一线”移动模式,呈现三点、四点和多点移动模式的人群出行占比分别为13.03%、5.99%和1.64%。该文方法可以更全面精细地识别城市人群移动模式,有助于城市管理者、规划者了解城市人群移动方向,优化城市资源配置。

数字化治理视域下提升地摊经济治理水平的对策

城市地摊经济的健康持续发展,需要地方政府以数字化治理思维更新治理理念、提升治理能力。数字化治理视域下地方政府的城市地摊经济治理,应充分运用大数据技术建立城市地摊经济的信息化管理平台,加大对城市地摊经济从业者的技能培训,强化对城市地摊经济交易过程的监督管理,重视对城市地摊经济经营方式的引导升级,才能不断提升城市地摊经济的治理水平。