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1.
Luliang Tang Xia Zhang Fei Sun Xue Yang Qingquan Li 《International journal of geographical information science》2016,30(9):1717-1737
ABSTRACTKernel Density Estimation (KDE) is an important approach to analyse spatial distribution of point features and linear features over 2-D planar space. Some network-based KDE methods have been developed in recent years, which focus on estimating density distribution of point events over 1-D network space. However, the existing KDE methods are not appropriate for analysing the distribution characteristics of certain kind of features or events, such as traffic jams, queue at intersections and taxi carrying passenger events. These events occur and distribute in 1-D road network space, and present a continuous linear distribution along network. This paper presents a novel Network Kernel Density Estimation method for Linear features (NKDE-L) to analyse the space–time distribution characteristics of linear features over 1-D network space. We first analyse the density distribution of each linear feature along networks, then estimate the density distribution for the whole network space in terms of the network distance and network topology. In the case study, we apply the NKDE-L to analyse the space–time dynamics of taxis’ pick-up events, with real road network and taxi trace data in Wuhan. Taxis’ pick-up events are defined and extracted as linear events (LE) in this paper. We first conduct a space–time statistics of pick-up LE in different temporal granularities. Then we analyse the space–time density distribution of the pick-up events in the road network using the NKDE-L, and uncover some dynamic patterns of people’s activities and traffic condition. In addition, we compare the NKDE-L with quadrat method and planar KDE. The comparison results prove the advantages of the NKDE-L in analysing spatial distribution patterns of linear features in network space. 相似文献
2.
Hengfeng Li Lars Kulik Kotagiri Ramamohanarao 《International journal of geographical information science》2013,27(12):2194-2222
Monitoring and predicting traffic conditions are of utmost importance in reacting to emergency events in time and for computing the real-time shortest travel-time path. Mobile sensors, such as GPS devices and smartphones, are useful for monitoring urban traffic due to their large coverage area and ease of deployment. Many researchers have employed such sensed data to model and predict traffic conditions. To do so, we first have to address the problem of associating GPS trajectories with the road network in a robust manner. Existing methods rely on point-by-point matching to map individual GPS points to a road segment. However, GPS data is imprecise due to noise in GPS signals. GPS coordinates can have errors of several meters and, therefore, direct mapping of individual points is error prone. Acknowledging that every GPS point is potentially noisy, we propose a radically different approach to overcome inaccuracy in GPS data. Instead of focusing on a point-by-point approach, our proposed method considers the set of relevant GPS points in a trajectory that can be mapped together to a road segment. This clustering approach gives us a macroscopic view of the GPS trajectories even under very noisy conditions. Our method clusters points based on the direction of movement as a spatial-linear cluster, ranks the possible route segments in the graph for each group, and searches for the best combination of segments as the overall path for the given set of GPS points. Through extensive experiments on both synthetic and real datasets, we demonstrate that, even with highly noisy GPS measurements, our proposed algorithm outperforms state-of-the-art methods in terms of both accuracy and computational cost. 相似文献
3.
Xue Yang Kathleen Stewart Zhen Dong Xia Zhang Qingquan Li 《International journal of geographical information science》2018,32(3):601-621
Lane-level road network updating is crucial for urban traffic applications that use geographic information systems contributing to, for example, intelligent driving, route planning and traffic control. Researchers have developed various algorithms to update road networks using sensor data, such as high-definition images or GPS data; however, approaches that involve change detection for road networks at lane level using GPS data are less common. This paper presents a novel method for automatic change detection of lane-level road networks based on GPS trajectories of vehicles. The proposed method includes two steps: map matching at lane level and lane-level change recognition. To integrate the most up-to-date GPS data with a lane-level road network, this research uses a fuzzy logic road network matching method. The proposed map-matching method starts with a confirmation of candidate lane-level road segments that use error ellipses derived from the GPS data, and then computes the membership degree between GPS data and candidate lane-level segments. The GPS trajectory data is classified into successful or unsuccessful matches using a set of defuzzification rules. Any topological and geometrical changes to road networks are detected by analysing the two kinds of matching results and comparing their relationships with the original road network. Change detection results for road networks in Wuhan, China using collected GPS trajectories show that these methods can be successfully applied to detect lane-level road changes including added lanes, closed lanes and lane-changing and turning rules, while achieving a robust detection precision of above 80%. 相似文献
4.
基于二分网络的北京公交线路布局的空间依赖性 总被引：2，自引：0，他引：2
公交网络运行系统的结构性缺陷常常致使其成为城市交通拥堵的罪魁祸首。传统公交网络空间研究皆将其视为一个独立的交通运输方式,忽视了城市道路网形态与结构的内生作用。本文基于二分网络的思想,通过构建公交线路—城市道路的空间依赖矩阵,引入系列空间依赖度测度指标从局域、全局两个尺度探讨了北京市的公交线路的空间依赖度及依赖的核心空间,并通过社团识别对北京市公交线路的依赖空间进行了划分。结果发现：① 局域依赖度方面,北京市公交线路布局高度依赖度少数城市主干道和城—郊区快速干道,其空间依赖格局形成了以市中心为核心,以城—郊区快速干道为通道的中心—外围的廊道扩散格局;② 全局依赖度方面,北京市公交线路空间布局结构失衡,比较脆弱,受城市道路路面路况影响较大,同时以四环为模糊边界的市中心区域成为北京市公交线路依赖的核心空间;③ 依赖空间划分上,北京市公交线路布局与城市地域空间呈现良好的对应性,朝阳、海淀、三环内（东城和西城）是公交线路布局规模最密的3个区域。 相似文献
5.
上海大都市交通网络分形的时空特征演变研究 总被引：18，自引：4，他引：14
分形理论的城市形态发生学研究应用,首先是从交通网络的应用开始的。国内外学者进行的大量案例研究表明,分形分维有可能是表征城市交通网络特征、解释城市交通网络发展,演化的一种较为理想的测度指标。以上海这一国际性大都市的交通网络为研究主体,通过测算上海市不同行政区域交通网络的分维值,研究分形特征的空间变化;利用不同时代上海市全域及典型行政区交通网络的分维,研究分形特征的时间演化。研究结果表明,在上海与一些发展相当成熟的大、中城市与城市化地区,交通网络形态1.7左右的分形分维值具有普适性,有可能是判断网络形态与功能、结构完善度的一个较为合宜的测度指标;分维的变化,表现在空间域上,上海城市交通网络的分形特征内域明显复杂于外域,在城市发展主轴方向表现为由内向外分维测度值的有序降低;而在时间域,近期的交通网络分形复杂度明显高于早期,网络的构型不断得到优化;这一总体趋势,与城市形态开发、经济发展的历程相一致。可以相信,分形测度与分维的演化将成为描述城市形态发生学过程的一个最有用的指标。 相似文献
6.
Yizhuo Li Fan Zhang 《International journal of geographical information science》2013,27(12):2385-2405
ABSTRACTRegionalization attempts to group units into a few subsets to partition the entire area. The results represent the underlying spatial structure and facilitate decision-making. Massive amounts of trajectories produced in the urban space provide a new opportunity for regionalization from human mobility. This paper proposes and applies a novel regionalization method to cluster similar areal units and visualize the spatial structure by considering all trajectories in an area into a word embedding model. In this model, nodes in a trajectory are regarded as words in a sentence, and nodes can be clustered in the feature space. The result depicts the underlying socio-economic structure at multiple spatial scales. To our knowledge, this is the first regionalization method from trajectories with natural language processing technology. A case study of mobile phone trajectory data in Beijing is used to validate our method, and then we evaluate its performance by predicting the next location of an individual’s trajectory. The case study indicates that the method is fast, flexible and scalable to large trajectory datasets, and moreover, represents the structure of trajectory more effectively. 相似文献
7.
Min Deng Jincai Huang Huimin Liu Luliang Tang Jianbo Tang 《International journal of geographical information science》2018,32(12):2337-2361
Detailed real-time road data are an important prerequisite for navigation and intelligent transportation systems. As accident-prone areas, road intersections play a critical role in route guidance and traffic management. Ubiquitous trajectory data have led to a recent surge in road map reconstruction. However, it is still challenging to automatically generate detailed structural models for road intersections, especially from low-frequency trajectory data. We propose a novel three-step approach to extract the structural and semantic information of road intersections from low-frequency trajectories. The spatial coverage of road intersections is first detected based on hotspot analysis and triangulation-based point clustering. Next, an improved hierarchical trajectory clustering algorithm is designed to adaptively extract the turning modes and traffic rules of road intersections. Finally, structural models are generated via K-segment fitting and common subsequence merging. Experimental results demonstrate that the proposed method can efficiently handle low-frequency, unstable trajectory data and accurately extract the structural and semantic features of road intersections. Therefore, the proposed method provides a promising solution for enriching and updating routable road data. 相似文献
8.
城市道路数据的完整性和实时性是保障位置服务和规划导航路径的关键支撑。该文提出一种基于共享单车轨迹数据的新增自行车骑行道路自动检测和更新方法:首先,结合缓冲区方法和轨迹—路网几何特征检测增量轨迹;其次,基于分段—聚类—聚合策略提取更新路段,利用多特征融合密度聚类算法与最小外包矩形骨架线法提取增量道路中心线;最后,基于拓扑规则完成道路更新。以广州市共享单车轨迹为例,将该方法与传统栅格细化法进行实验对比,结果表明:该方法能有效更新道路网络,且在2 m和5 m精细尺度范围内提取的新增道路覆盖精度提升14%左右;在7 m尺度下精度达90%以上,在10 m尺度下精度达96%以上。 相似文献
9.
武汉都市圈城际联系通达性的测度与分析 总被引：9，自引：2，他引：7
空间- 距离- 通达性已经成为城市区域一体化联系与发展的先决条件。当前都市圈城际联 系发展与交通网络建设存在明显的不同步现象, 矛盾解决的关键是优化其路网通达性空间格局。 以武汉都市圈为实证对象, 构建最短距离矩阵, 引入时间、空间通达性模型, 建立高等级路网发育 评价指标体系, 从节点体系与网络体系两个角度, 定量分析武汉都市圈城际通达性变化及其空间 格局, 揭示出: 圈域城镇( 节点) 体系通达性空间差异明显, 与城市自身交通区位、经济发展水平密 切相关, 其空间格局与城镇等级规模呈共轭协同关系, 不同空间等级节点形成以武汉为中心的同 心圈层与“轴—辐”网络空间格局; 快速交通干道网络( 高速公路、铁路等) 是城市通达性空间演变 的重要推动力, 使其空间收敛减速, 形成显著的带状分异格局, 初步形成沪蓉东西向、京珠南北向 的两大城市经济联系交通走廊; 圈域城际交通干网发育程度偏低, 处于回路网络水平, 高等级路 网扩展潜力巨大。 相似文献
10.
多中心化是分散城市人口,疏解交通拥堵,调节职住失衡,应对“大城市病”的重要手段。针对轨迹大数据,先利用词向量描述其空间特征和行为规律,再结合数据场理论表达城市区域对轨迹的吸引强度,并完成多中心识别,最后借鉴复杂网络理论对多中心空间交互规律进行探索和挖掘。结果表明：① 郑州市轨迹吸引强度呈核心强、外围弱、沿线蔓延的圈层空间分布形态,识别出的21个多中心轨迹引力差异较大,区域吸引能力不均衡;② 外围次级中心的区域引力强度和交互频次低,交互方向主要指向一级中心,呈现出外溢型多中心结构,为了实现其应有的分散疏解作用,还需加强统筹规划,带动其科学发展。提出基于词向量数据场轨迹引力的多中心识别分析方法,对于轨迹隐含的出行规律描述更加完整,对轨迹引力的表达更准确,从流动角度呈现了多中心的演化机理,为城市规划实践提供了新思路。 相似文献
11.
武汉都市圈路网空间通达性分析 总被引：20，自引：1，他引：19
以武汉都市圈为例.通过距离算法、拓扑算法和空间句法模型,构建系列通达性数理模型.定量分析武汉都市圈路网发育的空间结构性规律:武汉都市圈路网整体发育水平和通达性格局保持高度相关性和一致性.空间差异显著;通达性遵循距离衰减律,空间收敛整体效应明显.呈现三大等级圈层和"中心-外围"结构:高等级路网发育不均衡.引起时空距离通达性圈发生"摄动"变形,呈西北-东南向倾斜的"Y"字形结构:拓扑连接等通达性圈更是出现"破碎化",交通轴线网络呈"轴一辐"式和"鱼骨刺"状空间伸展序:同时,路网发育的等级差异性也导致整个网络伺服效率和应对"拥堵"能力的低下,并形成沿长江东西向、沿京广南北向两条带状集成核.成为整个路网的第一等级交通轴线,控制整个都市圈网络连接性,强化交通轴线交汇处-武汉市的中心性优势:路网通达性这种等级空间格局与圈域城镇体系、交通设施和社会经济发展状况密切相关.尤其是与高速公路为代表的高等级路网发育水平,表现出复杂的共轭协调关系. 相似文献
12.
基于轨迹数据场的热点区域提取及空间交互分析——以深圳市为例 总被引：2，自引：0，他引：2
以深圳市出租车GPS数据为基础,运用时空拓展的轨迹数据场聚类方法提取城市交通热点区域,结合城市POI(Point of Interest)数据和地理实况对热点区域加以理解和分析。基于复杂网络的视角,计算交互分析指标并可视化热点区域的空间交互网络,探究城市交通和居民出行的时空规律。结果表明:1)交通枢纽(机场、火车站和口岸)、综合性商圈、城市重要主干道周边和城市商务中心在节假日和工作日均表现为持续热点区域;2)节假日热点区域分布较"发散",主要反映了居民个性化出行需求;3)工作日热点区域分布较"收敛",主要表现为职住分离的通勤模式;4)不同热点区域在空间交互网络中的重要性存在明显差异,其空间交互体现了距离衰减效应和局部抱团现象,居民出行的热点区域网络本身具有小世界效应和无标度特征。 相似文献
13.
本文以我国典型快速城市化地区深圳市为例,综合使用GIS技术、道路网络结构特征分析、景观格局分析和相关分析方法研究其道路网络结构特征的成因及其景观生态效应。在确定了24个独立的空间研究单元的基础上,重点分析了深圳市道路网络结构特征的相关关系、城市化水平差异对道路网络结构特征的影响和道路格局特征的景观整体及重要组分的格局效应。结果表明:城市建设用地密度的增加导致交通用地密度、节点和廊道储量增加,道路网络结构复杂程度、格局指数降低;资源条件、环境和生态保护约束是导致道路网络复杂性增加、结构发育水平下降、网络格局指数不断降低的主要原因;深圳市的道路网络格局特征对全市景观整体格局没有表现显著的约束性影响,对建设用地显示出环境保护约束和空间吸引两个方面的综合效应,对于林地则表现出生态保护约束、空间排斥和物理分割三个方面的综合效应。 相似文献
14.
通过调研获取皖江城市带各市区内公路客运联系数据,从社会网络视角,分析皖江城市带区内公路交通联系的网络特征,并结合各市区内相互作用强度的现状及历年的变化,预测其今后经济联系的主导方向,为区内公路交通联系方向的预测提供参考,从而提出区内公路交通空间组织的优化建议。结果显示:皖江城市带区内公路交通网络密度较高;根据区内相互作用强度现状,形成了合肥市主中心,芜湖市副中心和安庆市区域性中心及"东西轴线"和"南北轴线"的经济联系格局;城市间的相互作用强度不断增长,但增速不一,总体位序变化较小;今后区内公路交通空间组织方向是沿"东西轴线"和"南北轴线"发展、围绕区域中心完善并加强"两翼"建设。 相似文献
15.
Hai Huang 《International journal of geographical information science》2013,27(12):2075-2094
This paper presents an original approach to dynamic anomalous behavior detection in individual trajectory using a recursive Bayesian filter. The anomalous pattern detection is of great interest for navigation, driver assistance systems, surveillance as well as crisis management. In this work, we focus on the GPS trajectories of automobiles finding where the driver’s behavior shows anomalies. Such anomalous behaviors can happen in many cases, especially when the driver encounters orientation problems, i.e., taking a wrong turn, performing a detour, or losing the way. First, three high-level features, i.e., turns and their density, detour factor, and route repetition are extracted from the given trajectory geometry, for which a long-term perspective is required to observe data sequences of a significant length instead of individual time stamps. We therefore employ high-order Markov chains with a ‘dynamic memory’ to model the trajectory integrating these long-term features. The Markov model is processed by a proposed recursive Bayesian filter to infer an optimal probability distribution of the potential anomalous driving behaviors dynamically over time. The filter performs unsupervised detection in single trajectories based on local features only. No training process is required to characterize the anomalous behaviors. By analyzing the detection results of individual trajectories, collective behaviors can be derived indicating traffic issues such as congestions and turn restrictions. Experiments are performed on volunteered geographic information (VGI) data, self-acquired trajectories, and open trajectory datasets to demonstrate the potential of the proposed approach. 相似文献
16.
通达性被认为是评价交通网络的方法中一项综合的、直观的评价指标,并越来越多地被应用到城市规划、区域空间结构与区域经济发展等多种领域。以山东半岛蓝色经济区陆域范围为研究区,通过运用空间句法模型和网络分析算法,获取路网集成度和等时圈数据并进行GIS可视化表达,定量分析研究区路网发育的空间结构性规律。研究结果表明：①蓝色经济区内路网体系发育较为成熟,路网线段集聚明显;线段式空间分布格局呈“点-轴”状发散,轴线式空间分布格局呈“干-枝”状发散,形成了区域内部的核心圈与外围圈的互连互通;②城镇区域可达性在较大程度上取决于区域中心性和周边路网发达程度,而青岛市和潍坊市位于区域的核心位置,通达性好且对整个区域路网的控制作用较为突出。 相似文献
17.
目前,被称为"无烟工业"的旅游业正在迅速发展,山东省地处中国的东部沿海,交通便利,旅游资源丰富,这就为山东省旅游业的发展提供了良好的基础。根据山东省2006～2010年的国内旅游收入数据,运用线性回归分析和灰色关联分析相结合的方法,选取旅游经济支持、生态环境质量、旅游交通、旅游服务、社会文明程度和居民生活水平6个方面14个指标,对影响山东省国内旅游收入的相关因素及各因素的重要程度进行了分析。结果表明,国内旅游收入与居民生活水平联系最为密切,与交通因素关联性最弱。 相似文献
18.
河流洪涝对城市公共安全应急响应能力的影响研究——以上海市外环以内中心城区为例 总被引：1，自引：0，他引：1
以上海市外环以内中心城区作为研究区域,采用洪涝情景模拟与GIS网络分析相结合的研究方法,评估了当前以及未来不同重现期河流洪涝情景下城市公共安全（110）应急响应能力。研究结果表明：在洪涝情景下,部分城市路网瘫痪、交通中断,应急车辆无法通行,公安应急服务空间可达性范围较正常情况明显变小,应急响应能力降低;由于高脆弱性区域（棚户区）主要位于黄浦江沿岸地区,江水漫溢导致淹没路段较多,因此部分棚户区的救援时间会出现延迟甚至失去应急救援服务。通过对河流洪涝情景下城市公共安全（110）应急响应能力的评估研究,可为城市洪涝灾害应急响应部门制定预防与应对措施提供理论和科学依据,具有重要的现实意义。 相似文献
19.
Yibin Ren Yang Zhang 《International journal of geographical information science》2019,33(9):1894-1912
Recently, researchers have introduced deep learning methods such as convolutional neural networks (CNN) to model spatio-temporal data and achieved better results than those with conventional methods. However, these CNN-based models employ a grid map to represent spatial data, which is unsuitable for road-network-based data. To address this problem, we propose a deep spatio-temporal residual neural network for road-network-based data modeling (DSTR-RNet). The proposed model constructs locally-connected neural network layers (LCNR) to model road network topology and integrates residual learning to model the spatio-temporal dependency. We test the DSTR-RNet by predicting the traffic flow of Didi cab service, in an 8-km2 region with 2,616 road segments in Chengdu, China. The results demonstrate that the DSTR-RNet maintains the spatial precision and topology of the road network as well as improves the prediction accuracy. We discuss the prediction errors and compare the prediction results to those of grid-based CNN models. We also explore the sensitivity of the model to its parameters; this will aid the application of this model to network-based data modeling. 相似文献
20.
基于路网相关性的分布式增量交通流大数据预测方法 总被引：2，自引：1，他引：1
针对城市道路拥堵问题的日益加剧的问题,智能化城市交通管理平台是缓解拥堵问题的有效方法,利用交通流大数据预测结果进行交通诱导,能够指导用户调整出行方案,有效缓解交通压力。研究了交通流大数据的分布式增量聚合方法,对海量交通流数据进行清洗统计,为交通流预测提供数据基础,基于交通流在路网中上下游路段的相关性分析,利用路口转弯率多阶分配将该相关性量化,构建基于路网相关性的空间权重矩阵,完成对于STARIMA模型的改进。通过应用试验证明,该方法能更准确的进行交通流预测,为交通诱导信息发布提供依据。 相似文献