面向数据集成的城市空间数据内涵与特征分析

GIS对空间对象及其关系表达能力的增强以及多源数据集成应用的需要,不仅扩大 了城市空间数据的内涵,而且推动了城市空间数据集成研究.城市空间数据涉及多个学科,主要来源于航空遥感与摄影测量、勘探量测、内插推算和社会统计,可分 为地上、地表、地下3个空间层次类型.城市空间数据具有离散非连续、构造约束、零散分 布、信息隐含和体特征等特殊性,并存在多语义、多尺度和实体拓扑特征.城市空间数据具有灰白二象性,地下空间数据可以灰、白相互转化.     

地理学视角下城市复杂性研究综述——基于近20年文献回顾

城市作为组织结构复杂的开放人地地域系统,一直是地理学的研究核心之一。论文以2000—2020年相关文献为数据源,构建一套定量分析与定性认知相结合的文献分析判读体系,基于地理学视角从概念内涵、研究主题、技术方法等方面综述城市复杂性研究成果并开展讨论。过去20 a来,中国的城市复杂性研究逐渐从单尺度的格局、过程和机制研究转向于多尺度下复杂交互过程的集成与综合研究,并逐步形成了城市设施网络、城市人居环境、城市经济活动以及城市空间治理4个主要主题,在数据方法上逐步转向于空间技术及社会计算支持下的全景式全生命周期数据支撑的多维场景化分析。今后及未来一段时期,地理学视角下的城市复杂性研究需要进一步加强城市数字基础设施建设及全周期信息采集能力,加深对城市生态经济体系的综合测度及监控,增强跨区域发展机制影响下的城市流空间研究。     

大数据时代城市时空间行为研究方法

信息技术的快速发展带来了“大数据”时代的到来,改变了城市的空间组织和居民行为,并使得城市时空间行为研究方法面临变革。本文在总结传统城市时空间行为研究方法存在问题的基础上,对影响其变革的数据获取与处理技术进行梳理,重点从居民时空行为、城市空间及城市等级体系3个方面综述了国内外应用大数据进行城市时空间行为研究的最新进展,构建了基于大数据应用的城市时空间行为研究方法框架。本文认为,大数据时代城市时空间行为研究方法的变革主要取决于对反映居民时空行为的网络或移动信息设备数据的挖掘、处理及应用,但是还需要进一步推动相关学科间的交叉与融合,加强社交网站等网络数据在居民时空行为和城市空间研究中的应用,并指导城市规划编制与管理方法的创新。     

Geo-Narrative: Extending Geographic Information Systems for Narrative Analysis in Qualitative and Mixed-Method Research∗

This research seeks to contribute to advancing qualitative methodologies at the intersection of qualitative geographic information systems (GIS), narrative analysis, 3D GIS-based time-geographic methods, and computer-aided qualitative data analysis. The approach to GIS-based narrative analysis developed in the study, called “geo-narrative,” is based on extending current GIS capabilities for the analysis and interpretation of narrative materials such as oral histories, life histories, and biographies. The three central elements in this approach are (1) narrative analysis as the qualitative approach; (2) 3D GIS-based time-geographic methods as the representational framework; and (3) 3D-VQGIS as the GIS-based computer-aided qualitative data analysis component. A case example based on a study of the lives of the Muslim women in Columbus, Ohio, after 11 September 2001 is used to illustrate the approach.     

面向城市社区规划的参与式感知与计算——概念模型与技术框架

科学准确地感知社区居民参与现状、诊断存在问题,及时广泛地了解社区居民需求与诉求,对于提升新形势下社区居民参与城市社区规划的能力与水平意义重大。借助网络和移动设备等技术手段,采取以人为主体的参与式感知方式获取数据,可实时感知和分析居民的情感、行为和所处的环境,进而提高社区居民参与的广泛性和时效性。国内外该领域的研究刚刚起步,对面向城市社区规划的参与式感知与计算尚缺乏系统深入的机理探索和方法研究。本文针对中国城市社区规划的实际需求,构建了面向城市社区规划的参与式感知与计算概念模型,提出实现参与式感知与计算的技术框架,并探讨其中涉及的具体技术研究内容。本研究将深化面向城市社区的参与式感知与计算的相关理论与方法研究,为城市社区规划的公众参与和科学评估提供新思路、新方法。     

Defining the Bull'S Eye: Satellite Imagery-Assisted Slum Population Assessment in Hyderabad,India

Abstract

This paper presents an approach to qualitative and spatial assessment of slum population numbers in Hyderabad, India using circle-based population data from the Census of India and results of the analysis of high resolution QuickBird satellite image data (2003) derived from automatic line detection and lacunarity algorithm. This approach provides plausible and spatially explicit aggregate statistics of slum population numbers within the city. This work suggests that both over- and underreporting of slum population numbers does occur in Hyderabad, and provides an improved view on the slum distribution patterns within this urban agglomeration.     

Integration of air pollution data collected by mobile sensors and ground-based stations to derive a spatiotemporal air pollution profile of a city

ABSTRACT

Air pollution has become a serious environmental problem causing severe consequences in our ecology, climate, health, and urban development. Effective and efficient monitoring and mitigation of air pollution require a comprehensive understanding of the air pollution process through a reliable database carrying important information about the spatiotemporal variations of air pollutant concentrations at various spatial and temporal scales. Traditional analysis suffers from the severe insufficiency of data collected by only a few stations. In this study, we propose a rigorous framework for the integration of air pollutant concentration data coming from the ground-based stations, which are spatially sparse but temporally dense, and mobile sensors, which are spatially dense but temporally sparse. Based on the integrated database which is relatively dense in space and time, we then estimate air pollutant concentrations for given location and time by applying a two-step local regression model to the data. This study advances the frontier of basic research in air pollution monitoring via the integration of station and mobile sensors and sets up the stage for further research on other spatiotemporal problems involving multi-source and multi-scale information.     

定性地理信息系统在城市社会空间研究中的应用

定性地理信息系统(定性GIS)是西方人文地理学定性研究的重要方法。它集成了定性和空间元素,更全面地阐明空间背景是如何被社会建构的。这种多元要素的整合,可以表达人们生活空间的多样性和复杂性,有助于展示生活路径的三维可视化细节,实现可视化社会空间过程。本文试图梳理西方定性GIS的方法论并探讨其在基于情感表达的个体数据采集分析、基于混合方法的可视化活动空间研究以及基于多重互动视角的社会空间研究中的应用。定性GIS包含微观和宏观层面的多重含义,使得研究者可以从多个有利位置观察问题并参与其中,有助于城市社会空间研究理论创新,为社会空间研究提供可探索空间。最后,从学科建设、方法论拓展、研究成果表达和研究议题选择等方面对中国开展同类研究进行展望。     

定性GIS在时空间行为研究中的应用

定性GIS已经成为地理学混合研究方法的重要组成部分,通过扎根理论并与可视化结合、GIS和民族志整合等途径,对时空间行为研究产生了深远的影响。其通过文本或非文本质性材料与GIS地理特征的整合,形成了时空行为研究中独特的地理环境系统与空间机制分析,一个重要的前沿领域就是地理叙事在时间地理学研究中的应用。时间地理学是研究人类时空行为的重要视角,但由于对个体主观性及行为的社会文化因素的相对忽视等原因,受到了一定的质疑。近年来以GIS为代表的地理空间技术的定性分析与表达,为时间地理学融入质性分析提供了方法论基础。关美宝创建的基于GIS的地理叙事方法,通过借鉴叙事分析的一般方法尤其是三维叙事空间分析,结合时间地理学概念框架,开发了基于GIS平台的计算机辅助叙事分析组件(3D-VQGIS),实现了在GIS内可视化的、循环交互的叙事分析,为定性GIS发展中GIS与叙事分析方法的融合做出了贡献。将地理叙事方法用于时空行为研究,可以为时间地理学方法创造一个更便于理解与解释研究对象日常行为的地理环境,为其融入行为与主体的质性分析提供从数据整合、数据分析到解释与展示的一整套研究方法与具体操作工具。     

Classifying urban land use by integrating remote sensing and social media data

Urban land use information plays an important role in urban management, government policy-making, and population activity monitoring. However, the accurate classification of urban functional zones is challenging due to the complexity of urban systems. Many studies have focused on urban land use classification by considering features that are extracted from either high spatial resolution (HSR) remote sensing images or social media data, but few studies consider both features due to the lack of available models. In our study, we propose a novel scene classification framework to identify dominant urban land use type at the level of traffic analysis zone by integrating probabilistic topic models and support vector machine. A land use word dictionary inside the framework was built by fusing natural–physical features from HSR images and socioeconomic semantic features from multisource social media data. In addition to comparing with manual interpretation data, we designed several experiments to test the land use classification accuracy of our proposed model with different combinations of previously acquired semantic features. The classification results (overall accuracy = 0.865, Kappa = 0.828) demonstrate the effectiveness of our strategy that blends features extracted from multisource geospatial data as semantic features to train the classification model. This method can be applied to help urban planners analyze fine urban structures and monitor urban land use changes, and additional data from multiple sources will be blended into this proposed framework in the future.     

Interviews and Questionnaires as Mixed Methods in Population Geography: TheCase of Lone Fathers in Newcastle,Australia

A mixed method approach was adopted to study the experiences of lonefathers, using a classic triangulation approach of interview and questionnaire data. This study utilised an empirical realist framework of scientific enquiry, with the ‘soft’ individual interview data seen as an adjunct to the ‘hard’ aggregate quantitative methods. A review of this study found that the interviews worked well as a pilot study in a classic mixed methods framework. The questionnaires provided a range of information about thecharacteristics of this group of lone fathers, but it was the interviews which provided astonishing depth on the causes of marital breakdown and post-marital conflict, and on the discourses and other structures which sustain social processes. In this study, the interview techniques could have been used differently, in a different framework of analysis (that of critical rather than empirical realism) without the support of other mixed methods.     

县域特色产业形成和演化机理研究进展

培育壮大县域特色产业是中国统筹区域城乡发展的战略重点之一, 研究县域特色产业也是区域可持续发展研究的重要内容。本文从理论视角、热点领域、研究方法3 个方面对近年来县域特色产业研究的重点进行了梳理。县域特色产业作为区域优势和产业特点的结合产物, 相关研究的理论视角基本属于人地关系地域系统的基础理论体系, 同时借鉴了生态学、系统学理论观点和分析框架, 为清晰刻画产业内外影响因子的共栖关系和互动效应提供了有效途径。从研究领域上看, 关注点从地方经济发展到全球生产网络、从传统影响因素到新因素, 与时俱进, 但是宏观研究和微观研究相互脱节现象突出, 在一定程度上影响了研究成果的实践指导意义。从研究方法上看, 相关研究正在从以定性描述和逻辑推理为主, 向定性和定量相结合的综合集成方法应用转变, 但受到数据可获取性的限制, 现象和变化趋势的驱动机制分析的技术方法亟待完善。     

国内外失地农民城市融合及保障制度综述

随着我国城市化进程的加快,失地农民的数量越来越多,成为影响社会和谐发展的重大问题。文章根据国内外近十多年来的相关文献,总结了国内外失地农民城市融合及保障制度的研究进展,并对未来的研究进行了展望。国外学者利用社会学模型和质性研究方法,对失地农民的城市融合及其影响因素进行了分析,提出政府完善法律法规和创建救助组织的融合策略建议。国内学者侧重于研究失地农民个人属性、就业培训、户籍、生活空间等因素对其城市融合的影响,提出政府和失地农民个人都需进行改变以促进失地农民的全面融合。未来失地农民城市融合及保障制度问题的研究应注重量化方法与质性方法的综合运用,建立具有广泛适用性的测量模型,将理论与实际联系得更加紧密,改善失地农民的生存与生活质量。     

国内外城乡空间复杂性研究进展及其启示

我国新时期城乡统筹发展及城乡空间一体化规划仍然面临着城乡关系的恶化和城乡空间分离的挑战。从本质上看,新时期城乡空间统筹规划应是以优化"城乡关系"为重点的城乡空间融合规划,其基础工作则是认识城乡空间的复杂性。当前,在国内掀起新一轮城乡统筹规划热潮的背景下,回顾、梳理国内外城乡空间复杂性研究进展,对指导国内城乡空间统筹规划具有重大意义。文章认为,目前城乡空间复杂性研究仍然以城市单系统为中心,乡村空间"被边缘";研究方法上应加强方法的集成综合,同时强调质性研究和定量分析的结合;在研究内容上应深化城乡关系空间复杂性、城乡关联空间复杂性、城乡空间自组织演化机制与模拟、城乡社会网络空间复杂性等方面的研究。     

Points of interest recommendation from GPS trajectories

Recently, points of interest (POIs) recommendation has evolved into a hot research topic with real-world applications. In this paper, we propose a novel semantics-enhanced density-based clustering algorithm SEM-DTBJ-Cluster, to extract semantic POIs from GPS trajectories. We then take into account three different factors (popularity, temporal and geographical features) that can influence the recommendation score of a POI. We characterize the impacts caused by popularity, temporal and geographical information, by using different scoring functions based on three developed recommendation models. Finally, we combine the three scoring functions together and obtain a unified framework PTG-Recommend for recommending candidate POIs for a mobile user. To the best of our knowledge, this work is the first that considers popularity, temporal and geographical information together. Experimental results on two real-world data sets strongly demonstrate that our framework is robust and effective, and outperforms the baseline recommendation methods in terms of precision and recall.     

Artificial neural networks and geostatistical models for housing valuations in urban residential areas

Property valuation studies often use classical statistics techniques. Among these techniques, the Artificial Neural Networks are the most applied, overcoming the inflexibility and the linearity of the hedonic models. Other researchers have used Geostatistics techniques, specifically the Kriging Method, for interpreting spatial-temporal variability and to predict housing unit prices. The innovation of this study is to highlight how the Kriging Method can help to better understand the urban environment, improving the results obtained by classical statistics. This study presents two different methods that share the general objective of extracting information regarding a city’s housing from datasets. The procedures applied are Ordinary Kriging (Geostatistics) and Multi-Layer Perceptron algorithm (Artificial Neural Networks). These methods were used to predict housing unit prices in the municipality of Pozuelo de Alarcon (Madrid). The implementation of both methods provides us with the urban characteristics of the study area and the most significant variables related to price. The main conclusion is that the Ordinary Kriging models and the Neural Networks models, applied to predicting housing unit prices are necessary methodologies to improve the information obtained in classical statistical techniques.

Abbreviations: ANN: Artificial Neural Networks; OK: ordinary Kriging; MLP: multi-layer perceptron     

国内外城市时空间结构研究的渊源及述评

本文在梳理城市地理学与时间地理学相关概念的基础上总结给出了城市时空间结构的概念内涵。城市时空间结构的内涵是以时间地理学对人地关系地域系统的研究作为基本方法,在城市地域内,以居民日常活动的一个基本周期作为时间尺度,该时空范围内所有人时空活动的关系及其组合状态。具体研究内容包括四个方面:其一,回顾了城市时空间结构的渊源,并对城市实体空间、城市社会空间、城市认知空间以及城市时空间概念进行了对比分析。其二,对国内外城市时空间及其相关研究进行了简要的归纳和梳理。其三,对国内城市时空结构的相关研究进行了回顾。其四,对城市时空间结构研究的相关内容进行了述评。认为随着地理信息技术的发展和多元数据的出现,城市时空间结构有如下特点:在研究内容方面,城市时空间结构研究的内容和切入点不断增多;在研究方法方面不断成熟,时空路径模拟、时空展示和对大数据处理技术方面不断成熟;在研究数据方面,逐步从传统的以出行日志为主的数据源走向以GPS数据和手机数据及其他数据相结合的多元数据融合。     

城市碳基能源代谢分析框架及核算体系

城市碳基能源代谢是当前应对全球气候变化与资源耗竭研究的重要突破口。针对碳排放研究在城市尺度核算的薄弱环节,以及城市代谢研究在社会经济子系统碳基能源转移分析上的缺陷,文章基于碳足迹与城市代谢阐释城市碳基能源代谢的内涵,界定其核算范畴与边界,构建城市复合生态系统碳基能源四种范畴不同代谢过程的核算方法体系。以北京市为案例,阐明三种核算方法的特点。研究认为,城市碳基能源代谢是对城市社会经济发展过程中资源利用与环境协调发展量度的一组低碳生态城市指标体系;不同碳基能源代谢核算方法各具特色,应根据数据可得性与研究目标针对性进行选择,以增加研究结果之间的规范性与可比性;不同范畴界定下的碳基能源代谢核算可以根据生产、消费及共担责任原则处理碳减排的责任问题;中国的城市碳基能源代谢实质是一种城市区域碳基能源代谢,三种核算方法从不同视角与层面揭示城市碳基能源代谢特点,三者结合能全面分析产业与能源结构调整、居民生活方式变化对低碳生态城市发展的作用路径与规律;城市部门结构(产业、居民) 与技术结构变化的碳基能源代谢响应是进一步研究的重点。