Robust inferences of travel paths from GPS trajectories

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.     

人类活动研究的新支点：Wi-Fi数据的特点、研究现状与应用前景

把握人类活动的时空特征是地理学研究中探究人地关系、提升人类福祉的重要基础和核心内容,日益普及的Wi-Fi网络能够为此提供可靠的数据支持。为明确Wi-Fi数据融入地理学研究的切入点和发展方向,论文通过与GPS、手机信令、蓝牙等位置感应数据的比较,认为Wi-Fi数据具有更高的采样精度和更强的采样代表性,能够获取个体在室内外各类城市空间的连续活动轨迹,支撑精细尺度下的人类活动研究。通过系统梳理人群活动状态监测、个体间的社会关系识别、建筑物的功能识别和降低隐私泄露风险等方面的研究进展,认为Wi-Fi数据将会在基于实时动态人口数据的城市功能设施规划、融合多源数据的人地关系探究、以居民福祉为导向的宜居城市建设等方面具有应用前景,有望成为地理学研究人类活动的新支点。     

Automatic change detection in lane-level road networks using GPS trajectories

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%.     

Near real-time geoprocessing on the grid: A scalable approach to road traffic monitoring

The geospatial sensor web is set to revolutionise real-time geospatial applications by making up-to-date spatially and temporally referenced data relating to real-world phenomena ubiquitously available. The uptake of sensor web technologies is largely being driven by the recent introduction of the OpenGIS Sensor Web Enablement framework, a standardisation initiative that defines a set of web service interfaces and encodings to task and query geospatial sensors in near real time. However, live geospatial sensors are capable of producing vast quantities of data over a short time period, which presents a large, fluctuating and ongoing processing requirement that is difficult to adequately provide with the necessary computational resources. Grid computing appears to offer a promising solution to this problem but its usage thus far has primarily been restricted to processing static as opposed to real-time data sets. A new approach is presented in this work whereby geospatial data streams are processed on grid computing resources. This is achieved by submitting ongoing processing jobs to the grid that continually poll sensor data repositories using relevant OpenGIS standards. To evaluate this approach a road-traffic monitoring application was developed to process streams of GPS observations from a fleet of vehicles. Specifically, a Bayesian map-matching algorithm is performed that matches each GPS observation to a link on the road network. The results show that over 90% of observations were matched correctly and that the adopted approach is capable of achieving timely results for a linear time geoprocessing operation performed every 60 seconds. However, testing in a production grid environment highlighted some scalability and efficiency problems. Open Geospatial Consortium (OGC) data services were found to present an IO bottleneck and the adopted job submission method was found to be inefficient. Consequently, a number of recommendations are made regarding the grid job-scheduling mechanism, shortcomings in the OGC Web Processing Service specification and IO bottlenecks in OGC data services.     

西南极菲尔德斯半岛地壳形变监测的数据处理与分析

为了研究南极现代地壳运动,中国在西南极菲尔德斯海峡地区布设了形变监测网,并用ＤＩ－２０测距仪和ＧＰＳ定位仪对该网进行了监测。同时,中国也参加了ＳＣＡＲ组织的全南极ＧＰＳ联测。本文讨论了将形变参数纳入误差方程的水平形变数据处理方法,并对刚体平移、旋转、均匀应变几种典型形变模型在测边网平差中的运用进行了讨论。通过对经典自由网与秩亏自由网的基准分析,提出对形变参数以及其它附加参数和点位参数分别给定参考基准的方法。相应于上述方法,编制了一系列数据处理程序并将之应用于对西南极菲尔德斯海峡形变监测网的数据分析。本文还利用监测网应变分析原理,对ＧＰＳ监测数据进行了讨论和分析,结果表明,菲尔德斯断裂地区存在微小的断裂剪切运动,但位移量不大。     

Fast map matching,an algorithm integrating hidden Markov model with precomputation

Wide deployment of global positioning system (GPS) sensors has generated a large amount of data with numerous applications in transportation research. Due to the observation error, a map matching (MM) process is commonly performed to infer a path on a road network from a noisy GPS trajectory. The increasing data volume calls for the design of efficient and scalable MM algorithms. This article presents fast map matching (FMM), an algorithm integrating hidden Markov model with precomputation, and provides an open-source implementation. An upper bounded origin-destination table is precomputed to store all pairs of shortest paths within a certain length in the road network. As a benefit, repeated routing queries known as the bottleneck of MM are replaced with hash table search. Additionally, several degenerate cases and a problem of reverse movement are identified and addressed in FMM. Experiments on a large collection of real-world taxi trip trajectories demonstrate that FMM has achieved a considerable single-processor MM speed of 25,000–45,000 points/second varying with the output mode. Investigation on the running time of different steps in FMM reveals that after precomputation is employed, the new bottleneck is located in candidate search, and more specifically, the projection of a GPS point to the polyline of a road edge. Reverse movement in the result is also effectively reduced by applying a penalty.     

Data processing and analysis of crustal deformation monitoring in the Fildes region,West Antarctica

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Map-matching algorithm for large-scale low-frequency floating car data

Large-scale global positioning system (GPS) positioning information of floating cars has been recognised as a major data source for many transportation applications. Mapping large-scale low-frequency floating car data (FCD) onto the road network is very challenging for traditional map-matching (MM) algorithms developed for in-vehicle navigation. In this paper, a multi-criteria dynamic programming map-matching (MDP-MM) algorithm is proposed for online matching FCD. In the proposed MDP-MM algorithm, the MDP technique is used to minimise the number of candidate routes maintained at each GPS point, while guaranteeing to determine the best matching route. In addition, several useful techniques are developed to improve running time of the shortest path calculation in the MM process. Case studies based on real FCD demonstrate the accuracy and computational performance of the MDP-MM algorithm. Results indicated that the MDP-MM algorithm is competitive with existing algorithms in both accuracy and computational performance.     

北极考察与GPS定位研究初探

本文叙述了作者 1 996年参加“北极追踪”科学考察队进行首次北极测绘科学考察期间 ,使用 GPS全球定位观测系统 ,沿雷索柳特 ( Resolute)—夸那 ( Qaanaaq)—卡波郁科 ( Kap Yok)—尤里科 ( Eureke)—北极点 ( North Pole)—尤里科—雷索柳特的考察路线 ,进行了冰海考察路线导航、寻找北极点、夸那及雷索柳特定点观测。事后采用高精度 GPS数据处理科研软件 GAMIT对采集得到的数据进行了处理、分析 ,得到了观测点的地心及大地坐标和各点到北京的空间基线长。结果表明 ,利用 GPS定位系统在北极地区进行大规模范围内、高精度监测地壳运动和环境动态变化是完全可行的。     

Privacy and spatial pattern preservation in masked GPS trajectory data

Personal trajectory data are increasingly collected for a variety of academic and recreational pursuits. As access to location data widens and locations are linked to other information repositories, individuals become increasingly vulnerable to identification. The quality and precision of spatially linked attributes are essential to accurate analysis; yet, there is a trade-off between privacy and geographic data resolution. Obfuscation of point data, or masking, is a solution that aims to protect privacy and maximize preservation of spatial pattern. Trajectory data, with multiple locations recorded for an entity over time, is a strong personal identifier. This study explores the balance between privacy and spatial pattern resulting from two methods of obfuscation for personal GPS data: grid masking and random perturbation. These methods are applied to travel survey GPS data in the greater metropolitan regions of Chicago and Atlanta. The rate of pattern correlation between the original and masked data sets declines as the distance thresholds for masking increase. Grid masking at the 250-m threshold preserves route anonymity better than other methods and distance thresholds tested, but preserves spatial pattern least. This study also finds via linear regression that median trip speed and road density are significant predictors of trip anonymity.     

城镇交通网络信息图谱研究刍议

研究了地学信息图谱的概念及其与城镇交通网络共有的基本特性,探讨了既有交通网络中已经运用到的地学信息图谱概念的情形,拓展了基于地理信息图谱概念,综合现代RS、GIS、GPS、ITS等技术,科学研究、系统改进交通网络中地学信息应用的可能。在此基础上,预测了未来地理信息图谱理念的深入应用将可能大力改进交通网络的几个方向。     

Identifying spatial concentrations of surnames

Surnames (family names) have been overlooked as a valuable source of spatially referenced population data. Presented here is a methodology, based on kernel density estimation, which is used to identify the areas of Great Britain where any surname is most concentrated. This not only indicates a surname's geographic origin in the country but also its current spatial extent and spatial relationship with other surnames and place names. We argue that such analysis can provide baseline and change measures, and an empirical basis to change forecasting. Such analysis offers valuable insights into national, regional and local changes in population structure, and testimony to the relevance of GIScience to population genetics, historical geography and genealogy.     

磁暴期间南极South Pole站和McMurdo站电离层闪烁与GPS TEC时空变化相关性研究

目前,对电离层闪烁特性的研究大多集中在低纬度地区,而在极区,特别是在南极地区,由于测量数据稀少,所以研究十分有限。借助安装在南极South Pole站和Mc Murdo站的GPS闪烁监测仪,获取到实测的电离层闪烁数据,同时结合IGS网站提供的同址GPS观测数据,分析了2011年9月24—25日磁暴发生前,9月26日磁暴发生时以及9月27日磁暴发生后GPS L波段信号电离层相位闪烁和GPS TEC时空变化特征。分析显示,这次磁暴对电离层的一个重要的影响是在电离层扰动剧烈期间,相位闪烁活动及其强度在时间和空间分布上都显著增强。研究结果发现,在强电离层闪烁期间,实测的相位闪烁指数σ_Φ与由GPS观测数据推算的TEC变化率指数(ROTI)的变化非常相似,两者之间呈现出良好的相关性。从而证明,在如南极等缺乏独立电离层闪烁观测值的地区,GPS ROTI可以作为表征电离层闪烁的重要可选参数,进而可以借助全球分布的GPS观测数据来分析和研究电离层闪烁特性。     

基于潜在语义信息的城市功能区识别————广州市浮动车GPS时空数据挖掘

随着中国城市化进程的不断推进和深入,城市内部空间结构正发生不断的变化.城市内部形成的不同功能区标识研究,对城市结构理论以及政策制定,资源配置等方面具有非常重要的意义.这些不同的功能区包括住宅区,工业区,教育区以及办公区等.本文以大数据为依托,重点研究城市功能区的特点和分布状态,选取广州市6个区为样本,以最新道路网络为分割依据把研究样本分为439个区域.对历时一周的海量浮动车(GPS)数据以及兴趣点数据采用时空语义挖掘方法,建立潜在的狄利克雷模型(LDA)以及狄利克雷多项式回归模型(DMR);通过OPTICS聚类方法对不同模型的结果进行聚类,进而利用POI类别密度,居民出行特征等方法进行分区结果识别.同时,参考百度地图的地理信息,将研究得到的广州市功能分区结果与广州市城镇用地现状图,居民日常出行特征进行对比验证分析.研究表明,该方法基本能识别出具明显特征的城市功能区,如成熟居住区,科教文化区,商业娱乐区,开发区等.识别出的广州市不同类型的功能区呈现了以居住区和商业区为主导,其他类型功能区围绕其展开的特点.研究证明,利用大规模,高质量的个体时空数据开展人们移动行为和日常活动组织及社会空间的研究,能从一个新的视角揭示城市功能区的形成及其机制.     

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。     

基于定位视频的车辆导航原型系统设计与关键技术研究

基于电子地图的导航系统相对抽象且缺乏沉浸感,不方便用户判别。为使导航效果更加直观和生动,该文提出基于定位视频的车辆导航思路,对车辆导航原型系统进行总体设计与实现,并探讨其关键技术。核心思想是建立道路定位视频(Geo-video)数据库,利用移动终端和固定目标的位置信息对定位视频数据库进行空间检索,将相应位置的视频图像传输给移动终端并实现路线和目标指引。试验证明该方法在技术上具有可行性。     

集聚外部性、网络外部性与城市创新发展

随着高速交通技术和移动基础设施的迅速发展,城市创新活动已经不再局限于特定的地理空间,在网络空间中彼此远离但有着较强经济活动关联的城市之间是否也可以实现协同创新,目前仍缺乏经验证据。基于2001—2016年中国289个地级市宏观面板数据和微观层面上市公司数据,采用社会网络分析法、工具变量法以及空间杜宾模型等方法,定量研究了集聚外部性与网络外部性对于城市创新发展的影响。结果显示：创新要素依旧存在着向头部企业和中心城市集中的趋势,且正是这种集中所带来的集聚外部性促进了城市的创新发展;城市可通过融入经济关联网络,借助于网络外部性来提高自身创新水平;就集聚外部性与网络外部性促进城市创新发展的传导机制来看,虽然政府科教支出水平、城市基础设施状况以及高铁网络的建设是集聚外部性与网络外部性发挥的重要条件,但经济活动密度的提升所带来的集聚外部性还可以强化网络外部性所带来的创新效应,而外商直接投资活动所分享的先进技术和管理经验则帮助网络外部性突破了地理空间的限制。因此,政府在探索城市创新发展路径的过程中,就无需囿于创新要素的空间集聚这一条路径,积极融入城市群内的国际科技创新中心建设,凭借网络外部性所分享的新知识与新技术,同样也能实现创新发展。     

基于GPS的北极冰川表面地形测量与制图

自2005年以来,我国科考队员利用双频GPS在北极黄河站附近的Austre Lovénbreen 和 Pedersenbreen两条冰川上每年一次开展高精度的冰川运动观测,获取了冰川表面监测标杆的精确位置和运动速度。2009年4月,我国考察队员在这两条冰川上开展了密集的GPS点位数据采集,藉此开展北极两条冰川的冰面地形测量。在分析单频GPS动态单点定位数据用于冰面地形测量的可行性基础上,经过平差计算获得了两条冰川的冰面地形数据,进而生成冰面DEM和等高线,制作冰面地形图。经与高精度控制点比较,冰面DEM高程的误差为0.78m,在冰川季节性高程波动和年消融的变化范围之内。由于SMART-V1型GPS设备是当前冰川研究工作中应用较多的pulseEKKO型探地雷达配套的一个重要部件,本文的结论对于同类仪器开展冰川测量工作具有参考价值,对基于高密度的GPS动态单点定位测量方法用于冰面地形测量的数据处理具有指导意义。     

武汉地区地基GPS遥感水汽与气象因子的相关性分析

地基GPS可以适时准确地反演大气可降水含量,而常规气象观测站点一般具有长时期的历史观测数据。若将这两种数据融合,可以加强数值天气预报的准确性,因此需要探讨二者之间的相关性。通过处理2006年、2007年全球卫星导航服务组织(IGS)提供的武汉站地基GPS观测数据,计算武汉地区上空日平均水汽含量。利用一元和多元回归分析GPS遥感水汽与地面气象观测因子之间的关系,发现武汉地区GPS遥感水汽含量同包括气温、气压等在内的多种气象因子都有一定程度的相关性,其中与气温的相关性最大,且武汉地区上空的大气水汽含量的季节性变化大,在夏季其日平均变化十分明显。     

An extension of GIS-based least-cost path modelling to the location of wide paths

The computation of least-cost paths over a cost surface is a well-known and widely used capability of raster geographic information systems (GISs). It consists in finding the path with the lowest accumulated cost between two locations in a raster model of a cost surface, which results in a string-like, thin and long sequence of cells. In this article, a new extension of raster-based least-cost path modelling is proposed. The new modelling approach allows the computation of paths or corridors with a fixed width, larger than one cell. These swaths are called wide paths and may be useful in circumstances where the detail level of the raster cost surfaces is higher than the width of the desired path or corridor. The wide path model presented in the article is independent of the choice of least-cost algorithms, because the transformation from regular to wide paths is applied to the construction of nodes and edges of an induced graph. The article gives the foundations and discusses the particularities of such paths, regardless of the imposed width, and explores the difference from the usual least-cost path model. Test cases were included, one hypothetical and the other with real data. The results are coherent and indicative of the applicability of wide paths.