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1.
Hao Jiang Qian Li Xian Zhou Yanqiu Chen Shuwen Yi Hai Wang 《International journal of geographical information science》2017,31(12):2359-2381
Human mobility patterns have been widely investigated due to their application in a wide variety of fields, for example urban planning and epidemiology. Many studies have introduced spatial networks into human mobility analyses at the collective level. However, these studies merely analyzed spatial network structure, and the underlying collective mobility patterns were not further discussed. In this paper, we propose a collective mobility discovery method based on community differences (CMDCD). We constructed spatial networks where nodes represent geographical entities and edge weights denote collective mobility intensity between geographical entities. The differences between communities detected from the networks constructed in different periods were then identified. Since collective spatial movement has a large influence on network structure, we can discover groups with different mobility patterns based on community differences. By applying the method to data usage detail records collected from the cellular networks in a city of China, we analyzed different collective mobility patterns between the Spring Festival vacation and workdays. The experimental results show that our method can solve these two problems of identifying community differences and discovering users with different mobility patterns simultaneously. Moreover, the CMDCD method is an integrated approach to discover groups whose mobility patterns have changed in different periods at the large spatial scale and the small spatial scale. The discovered collective mobility patterns can be used to guide urban planning, traffic forecasting, urban resource allocation, providing new insights into human mobility patterns and spatial interaction analyses. 相似文献
2.
Qunying Huang David W. S. Wong 《International journal of geographical information science》2016,30(9):1873-1898
ABSTRACTIndividual activity patterns are influenced by a wide variety of factors. The more important ones include socioeconomic status (SES) and urban spatial structure. While most previous studies relied heavily on the expensive travel-diary type data, the feasibility of using social media data to support activity pattern analysis has not been evaluated. Despite the various appealing aspects of social media data, including low acquisition cost and relatively wide geographical and international coverage, these data also have many limitations, including the lack of background information of users, such as home locations and SES. A major objective of this study is to explore the extent that Twitter data can be used to support activity pattern analysis. We introduce an approach to determine users’ home and work locations in order to examine the activity patterns of individuals. To infer the SES of individuals, we incorporate the American Community Survey (ACS) data. Using Twitter data for Washington, DC, we analyzed the activity patterns of Twitter users with different SESs. The study clearly demonstrates that while SES is highly important, the urban spatial structure, particularly where jobs are mainly found and the geographical layout of the region, plays a critical role in affecting the variation in activity patterns between users from different communities. 相似文献
3.
基于居民行为周期特征的城市空间研究 总被引：4，自引：1，他引：3
伴随着中国经济社会进入“新常态”的发展阶段,对城市存量空间的研究提出了更加精细化的要求,基于居民行为活动的周期规律对城市空间进行研究,进而提升城市空间的品质日益重要。随着信息通信技术的快速发展,使许多大数据的获取成为可能,并由于其低成本、即时、大样本等优势,在城市空间研究方面具有巨大的价值。以上海市中心城区为例,利用手机信令数据,探究居民活动的空间周期变化特征,并基于空间的周期特征曲线,采用相似性传播聚类算法进行空间分类。研究表明,居民活动有平日一日周期和平日加周末二日周期,与人的作息规律相符合。市核心区、城市副中心及主要就业中心,昼夜波动和平日周末活动强度的差异都较为明显。空间分类结果显示,城市活动空间的组织既体现出个体充分的空间能动性,也反映出对土地使用类型以及设施建设、投入程度的耦合性。上海市内环内核心区混合多样的用地模式使得活动区内居民活动内容丰富,周期特征功能区边界模糊。研究成果可为未来的城市空间规划提供指导,为城市空间结构、功能布置、设施布局等优化提供决策支撑和科学依据。 相似文献
4.
移动定位大数据视角下的人群移动模式及城市空间结构研究进展 总被引：5，自引：3，他引：2
了解城市人群移动行为和空间结构对城市规划、交通管理、应急响应等具有重要的意义。近年来,随着信息技术(ICT)的快速发展,采集大规模、长时间序列的人群移动定位大数据变得容易,为人群移动行为研究带来了新的机遇和挑战。本文首先介绍了目前用于城市人群移动行为和空间结构研究的主要数据源及其特征,并分别从人群移动行为、城市空间结构2个方面对近3年国内外相关研究进行归纳总结。目前的研究主要从移动定位大数据中挖掘人群移动模式,理解人群移动时空规律,进一步透视城市的空间结构特征;而对城市空间结构与人群移动行为影响的研究较少。未来可通过融合多源时空数据,综合研究人群移动行为与城市空间结构之间的相互作用,发展大规模群体移动行为时空分析理论和模型,进一步深入理解人群移动行为与城市空间结构的耦合关系。 相似文献
5.
Qunying Huang 《International journal of geographical information science》2017,31(3):523-541
Social media applications are widely deployed in mobile platforms equipped with built-in GPS tracking devices, and these devices have led to an unprecedented collection of geolocated data (geo-tags). Geo-tags, along with place names, offer new opportunities to explore the trajectory and mobility patterns of social media users. However, trajectory data captured by social media are sparsely and irregularly spaced and therefore have varying degrees of resolution in both space and time. Previous studies on next location prediction are mostly applicable for detecting the upcoming location of a moving object using dense GPS trajectories where locations are recorded at regular time intervals (e.g., 1 minute). Additionally, point features are commonly used to represent the locations of visits, but using point features cannot capture the variability of human mobility. This article introduces a new methodology to predict an individual’s next location based on sparse footprints accumulated over a long time period using social networks, and uses polygons to represent the location corresponding to the physical activity area of individuals. First, the density-based spatial clustering algorithm is employed to discover the most representative activity zones that an individual frequently visits on a daily basis, and a polygon-based region is then derived for each representative activity zone. A sparse mobility Markov chain model considering both the movements and online behaviors of the social media user is trained and used to predict the user’s next location. Initial experiments with a group of Washington DC Twitter users demonstrate that the proposed methodology successfully discovers the activity regions and predicts the user’s next location with accuracy approaching 78.94%. 相似文献
6.
由于各地资源禀赋差异和各级政府之间的复杂关系,城市群交界地区不可避免地存在经济社会发展上的矛盾和不平衡。已有研究揭示了行政边界效应在省域、城市群等不同尺度均普遍存在,且在不同阶段影响土地利用变化的程度大小不一,但多将行政边界转化为虚拟变量而非空间地理要素,不足以理解中微观尺度各种因素之间的复杂相互作用。论文旨在利用1985—2020年的中国年度土地覆盖数据集,以区县为单元,运用质心迁移、核密度分析和Logistic回归方法,分析京津冀典型城市群交界地区“通州—武清—廊坊(通武廊)地区”不透水面(ISA)的扩张机理并测度行政边界效应的影响。结果显示：① 不同行政区因资源禀赋和所处发展阶段的不同,城市用地扩张的速度和主要时期存在一定的差异;② 由于要素的高度流动,地理邻近的行政区城市扩张驱动要素表现出一定的相似性;③ 在不同区域分工水平下,行政界线的边界效应对城市用地扩张的影响表现出一定差异性。通过“强—弱”管控提高通武廊地区各要素协调水平,减少行政边界对地方之间资源整合的负面影响,对于实现京津冀城市群协同发展具有重要作用。 相似文献
7.
Pengxiang Zhao Wenzhong Shi Tao Jia Wengen Li Min Chen 《International journal of geographical information science》2020,34(6):1089-1116
ABSTRACTMovement patterns of intra-urban goods/things and the ways they differ from human mobility and traffic flow patterns have seldom been explored due to data access and methodological limitations, especially from systemic and long timescale perspectives. However, urban logistics big data are increasingly available, enabling unprecedented spatial and temporal resolutions to this issue. This research proposes an analytical framework for exploring intra-urban goods movement patterns by integrating spatial analysis, network analysis and spatial interaction analysis. Using daily urban logistics big data (over 10 million orders) provided by the largest online logistics company in Hong Kong (GoGoVan) from 2014 to 2016, we analyzed two spatial characteristics (displacement and direction) of urban goods movement. Results showed that the distribution of goods displaceFower law or exponential distribution of human mobility trends. The origin–destination flows of goods were used to build a spatially embedded network, revealing that Hong Kong became increasingly connected through intra-urban freight movement. Finally, spatial interaction characteristics were revealed using a fitting gravity model. Distance lacked substantial influence on the spatial interaction of goods movement. These findings have policy implications to intra-urban logistics and urban transport planning. 相似文献
8.
Ick-Hoi Kim Chen-Chieh Feng Yi-Chen Wang Brian H. Spitzberg Ming-Hsiang Tsou 《The Professional geographer》2017,69(4):629-643
The 2015 Middle East respiratory syndrome (MERS) outbreak in South Korea gave rise to chaos caused by psychological anxiety, and it has been assumed that people shared rumors about hospital lists through social media. Sharing rumors is a common form of public perception and risk communication among individuals during an outbreak. Social media analysis offers an important window into the spatiotemporal patterns of public perception and risk communication about disease outbreaks. Such processes of socially mediated risk communication are a process of meme diffusion. This article aims to investigate the role of social media meme diffusion and its spatiotemporal patterns in public perception and risk communication. To do so, we applied analytical methods including the daily number of tweets for metropolitan cities and geovisualization with the weighted mean centers. The spatiotemporal patterns shown by Twitter users' interests in specific places, triggered by real space events, demonstrate the spatial interactions among places in public perception and risk communication. Public perception and risk communication about places are relevant to both social networks and spatial proximity to where Twitter users live and are interpreted in reference to both Zipf's law and Tobler's law. 相似文献
9.
提出基于夜间灯光遥感影像、电子地图兴趣点和社会经济统计数据等,以经济地理学中的“点-轴”理论为基础,以“点-轴集聚区”的识别为核心,利用迭代自组织聚类、聚合分析、指标阈值筛选等方法,识别中国城市群及其空间范围的技术方法。通过该方法识别出中国14个城市群,其中8个城市群的空间范围与规划范围接近;与规划范围不一致的则表现为三种情况,分别揭示出规划中需要考虑的不同问题。研究结果表明,本文提出的方法能突破行政边界限制,科学反映城市群辐射范围,客观反映城市之间的社会经济联系强度,并基于“现状-动态”视角有利于深入发掘潜在的城市群对象。研究结果可以为城市群规划和管理提供参考。 相似文献
10.
Global multi-layer network of human mobility 总被引：2，自引：0，他引：2
Alexander Belyi Iva Bojic Izabela Sitko Bartosz Hawelka Lada Rudikova 《International journal of geographical information science》2017,31(7):1381-1402
Recent availability of geo-localized data capturing individual human activity together with the statistical data on international migration opened up unprecedented opportunities for a study on global mobility. In this paper, we consider it from the perspective of a multi-layer complex network, built using a combination of three datasets: Twitter, Flickr and official migration data. Those datasets provide different, but equally important insights on the global mobility – while the first two highlight short-term visits of people from one country to another, the last one – migration – shows the long-term mobility perspective, when people relocate for good. The main purpose of the paper is to emphasize importance of this multi-layer approach capturing both aspects of human mobility at the same time. On the one hand, we show that although the general properties of different layers of the global mobility network are similar, there are important quantitative differences among them. On the other hand, we demonstrate that consideration of mobility from a multi-layer perspective can reveal important global spatial patterns in a way more consistent with those observed in other available relevant sources of international connections, in comparison to the spatial structure inferred from each network layer taken separately. 相似文献
11.
Mei‐Po Kwan 《The Professional geographer》2007,59(4):434-446
The widespread use of mobile communications is leading to new practices in family life and social life, and these changes have significant implications for the study of urban travel. Because of the adoption of new modes of space‐time coordination, changing time use and increasing mobility, changing use of existing urban nodes, the blurring of boundaries between home and work, the importance of social networks and social capital, and the shift to person‐to‐person connectivity, the spatial structure and processes of interaction among individuals have become much more complicated in this age of mobile communications. Static spatial frameworks based on fixed points (e.g., home or workplace) and distances among them are no longer adequate for understanding urban travel. The study of urban travel now needs new conceptualizations and new methodologies. 相似文献
12.
复杂网络视角下的城市人流空间概念模型与研究框架 总被引：1，自引：0，他引：1
城市内人流特征研究一直是城市地理学和城市空间研究的重要领域之一。针对已有相关研究存在仅侧重于从人口规模、密度视角分析空间分布及格局特征,而对隐藏于空间分布背后,因人流动而建立的空间交互关系关注不足的问题。本文以流空间理论、复杂网络理论、空间行为交互理论为理论基础,立足基于流、网络剖析城市内部空间中各要素间的相互作用及关系,选取人流为观测研究对象,将城市空间、人、设施、服务和地理环境等要素之间的互动关系抽象为网络,提出了基于复杂网络视角的城市人流空间概念模型。在此基础上,进一步构建了城市人流空间研究框架,即基于理论融合、数据支撑与研究方法的整合创新,以探究人流视角下的城市空间特征、功能结构、人流与建成环境时空耦合关系及流动的时空模拟预测为重点的研究内容体系,并探讨其在规划实践业务中的方法技术支撑与应用拓展。以期为未来开展实证研究提供指导,提升城市感知数据在城市空间规划及管理中的应用价值,丰富“以流定形”的理性城市规划方法体系。 相似文献
13.
智能技术的影响已经渗透到城市的不同方面,空间要素的流动更快更复杂,城市功能需要进行调整以适应居民活动的变化,城市空间的智能化发展与运营管理也成为新的挑战。论文从城市空间要素组织、居民活动与空间功能、空间运营管理3个方面梳理当前智能技术对城市空间的影响,并展望未来5~10 a的城市空间应具有瞬时异地、空间智能化、复杂流动性以及韧性能力更强的特点,最后从城市空间组织、功能形态、运营管理与规划方法4个方面探讨了未来的城市空间研究需要关注的重点内容,以期为智能技术影响下的城市空间研究与规划设计提供参考。 相似文献
14.
Chen Zhong Stefan Müller Arisona Xianfeng Huang Michael Batty Gerhard Schmitt 《International journal of geographical information science》2014,28(11):2178-2199
Urban spatial structure in large cities is becoming ever more complex as populations grow in size, engage in more travel, and have increasing amounts of disposable income that enable them to live more diverse lifestyles. These trends have prominent and visible effects on urban activity, and cities are becoming more polycentric in their structure as new clusters and hotspots emerge and coalesce in a wider sea of urban development. Here, we apply recent methods in network science and their generalization to spatial analysis to identify the spatial structure of city hubs, centers, and borders, which are essential elements in understanding urban interactions. We use a ‘big’ data set for Singapore from the automatic smart card fare collection system, which is available for sample periods in 2010, 2011, and 2012 to show how the changing roles and influences of local areas in the overall spatial structure of urban movement can be efficiently monitored from daily transportation.
In essence, we first construct a weighted directed graph from these travel records. Each node in the graph denotes an urban area, edges denote the possibility of travel between any two areas, and the weight of edges denotes the volume of travel, which is the number of trips made. We then make use of (a) the graph properties to obtain an overall view of travel demand, (b) graph centralities for detecting urban centers and hubs, and (c) graph community structures for uncovering socioeconomic clusters defined as neighborhoods and their borders. Finally, results of this network analysis are projected back onto geographical space to reveal the spatial structure of urban movements. The revealed community structure shows a clear subdivision into different areas that separate the population’s activity space into smaller neighborhoods. The generated borders are different from existing administrative ones. By comparing the results from 3 years of data, we find that Singapore, even from such a short time series, is developing rapidly towards a polycentric urban form, where new subcenters and communities are emerging largely in line with the city’s master plan.
To summarize, our approach yields important insights into urban phenomena generated by human movements. It represents a quantitative approach to urban analysis, which explicitly identifies ongoing urban transformations. 相似文献
15.
Spatial co-location pattern mining of facility points-of-interest improved by network neighborhood and distance decay effects 总被引：1，自引：0，他引：1
Wenhao Yu Tinghua Ai Yakun He Shiwei Shao 《International journal of geographical information science》2017,31(2):280-296
The aim of mining spatial co-location patterns is to find the corresponding subsets of spatial features that have strong spatial correlation in the real world. This is an important technology for the extraction and comprehension of implicit knowledge in large spatial databases. However, existing methods of co-location mining consider events as taking place in a homogeneous and isotropic context in Euclidean space, whereas the physical movement in an urban space is usually constrained by a road network. Furthermore, previous works do not take the ‘distance decay effect’ of spatial interactions into account, which may reduce the effectiveness of the result. Here we propose an improved spatial co-location pattern mining method, including the network-constrained neighborhood and addition of a distance-decay function, to find the spatial dependence between network phenomena (e.g. urban facilities). The underlying idea is to utilize a model function in the interest measure calculation to weight the contribution of a co-location to the overall interest measure instance inversely proportional to the separation distance. Our approach was evaluated through extensive experiments using facility points-of-interest data sets. The results show that the network-constrained approach is a more effective method than the traditional one in network-structured space. The proposed approach can also be applied to other human activities (e.g. traffic accidents) constrained by a street network. 相似文献
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17.
中国城市住宅价格的空间分异格局及影响因素 总被引：4，自引：2，他引：4
分别研究2009年中国286个地级以上城市住宅均价和房价收入比的空间分异格局、总体趋势、空间异质性和相关性;根据供需理论和城市特征价格理论建立了影响中国城市住宅价格空间分异的初选因素,并根据半对数模型分析主要影响因素。结果表明：① 中国城市住宅价格空间分异显著,呈现出空间集聚性分异（东南沿海三大城市群与内陆城市之间）和行政等级性分异（省会与地级市之间）的双重格局;② 房价收入比较高的城市数量更多,分布范围更广,购房难度较大的城市已超过一半;③ 住宅均价的总体分异趋势和空间异质性都强于房价收入比;④ 城市居民收入与财富水平和城市区位与行政等级特征是住宅价格空间分异的两大核心影响因素。 相似文献
18.
基于POI与NPP/VIIRS灯光数据的城市群边界定量识别 总被引：1，自引：2，他引：1
科学识别城市群边界是城市群精明紧凑发展的关键,也是国家空间治理体系与空间治理能力的重要标志。论文以京津冀、长三角和珠三角3大城市群为研究区域,采用NPP/VIIRS(Suomi National Polar-orbiting Partnership / Visible Infrared Imaging Radiometer Suite)夜间灯光影像与POI(Point of Interest)数据,基于密度的曲线阈值法与分形网络演化算法,对3个城市群的实际物理边界和集聚空间范围进行精准识别与空间特征解析。研究结果表明：① 基于POI密度的曲线阈值法与NPP/VIIRS分形网络演化算法识别出城市群边界均小于国家城市群规划的行政边界,识别范围约占规划范围的20.90%~24.40%,识别结果显示3大城市群中长三角城市群发育最好,识别的城市群面积是京津冀和珠三角城市群的2倍左右;② 从POI与NPP/VIIRS灯光数据提取的城市群边界面积非常接近,其中POI数据提取的城市群面积偏大,更大程度上反映的是城市群整体边界轮廓而非内部细节;NPP/VIIRS影像提取的城市群更细碎,能更好地识别城市群聚集中心与关键核心区域,2种方法可以相互比较和验证;③ POI与灯光数据识别的城市群边界叠置分析发现,3大城市群中除了关键核心地带(集聚区)以外,外围还有众多孤立的点状区域(中小城镇),外围的点状区域与城市群集聚中心区空间割裂,一定程度上很难快速有效地接受来自城市群核心区域的辐射带动(涓滴效应)。 相似文献
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城市绿色空间格局时空演变及其生态系统服务评价的研究进展与展望 总被引：1，自引：1，他引：1
科学合理的城市绿色空间格局是城市可持续发展的物质空间保障,对其时空演变和影响因素进行研究,可揭示城市绿色空间在城市化进程中各要素与演变过程的复杂关系,以确保城市生态系统服务功能的正常发挥。在生态文明建设背景下,城市绿色空间将在多尺度国土空间规划中发挥积极作用,然而城市绿色空间规划与国土空间规划如何衔接却有待商榷。因此,论文在梳理城市绿色空间概念界定和发展历程的基础上,一方面讨论城市绿色空间格局的时空评价、驱动因子、情景模拟及优化策略的研究进展;另一方面总结生态系统服务在城市绿色空间格局评价中的应用进展。通过归纳以上研究内容,提出国土空间规划体系中有关城市绿色空间格局的评价及优化框架,以期为新时代背景下的城市绿色空间规划提供参考。 相似文献
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就业分布是城市空间结构的核心组成部分。当前,就业多中心化正在成为一个全球现象并主导着城市空间结构研究的范式转变,然而中国对这一主题的研究尚缺乏系统性探讨。论文在梳理中西方相关文献基础上,试图呈现城市就业多中心化的研究进展,以期为国内相关研究提供参考。首先,系统总结国内外城市就业集散与多中心化的地理格局与过程,重点回顾当前研究的共识与争论以及就业中心的生长动态与趋势。其次,从不同理论视角追踪城市就业集散与多中心模式演化的动力机制,关注空间政治经济学视角下就业多中心结构的形成机理,特别是空间规划与管治等制度因素和市场力量的相互作用。最后,从就业多中心化对城市空间结构、城市通勤的影响2个方面总结就业多中心化的空间效应。城市就业多中心模式演化为我们认知城市的空间增长逻辑提供了独特观察窗口,可以为中国城市转型与空间重构相关政策的制定提供决策参考。 相似文献