一种集成R树、哈希表和B*树的高效轨迹数据索引方法

为兼顾时空索引方法的空间利用率、时间效率和查询种类,提出了一种新的轨迹数据索引方法——HBSTR树。其基本思想是:轨迹采样点以轨迹节点的形式成组集中管理,哈希表用于维护移动目标的最新轨迹节点,轨迹节点满后作为叶节点插入时空R树,另外采用B*树对轨迹节点构建一维索引,既有利于提升索引创建效率,又同时满足时空条件搜索和特定目标轨迹搜索等多种查询类型。为提升时空查询效率,提出了新的时空R树评价指标和节点选择子算法改进时空R树插入算法,同时提出了一种时空R树的数据库存储方案。试验结果表明,HBSTR树在创建效率、查询效率和支持查询类型等方面综合性能优于现有方法,支持大规模实时轨迹数据库的动态更新和高效访问。     

基于快照-增量的时空索引机制研究

已有的时空索引是基于时间或空间索引的扩展,将相应的空间或时间成分作为属性,难以同时顾及时间查询和空间查询的效率.分析基于版本-增量的时空数据模型,提出基于快照-增量的时空数据索引机制.该索引将时间和空间作为同等重要的维,满足时空联合查询的效率.     

基于分层子网的时空索引机制

目前,已有的时空索引机制主要考虑时空对象,缺乏对显式表达的时空关系的索引,不便于因果关系查询,降低了图论时空模型的实用性。这里扩展了图的数学概念,提出了时空图的分割策略,构建了基于分层子网的时空索引机制,实现了时空对象与时空关系索引的一体化,增强了基于图论的时空数据库的灵活性,有利于因果关系的查询。     

利用Hilbert曲线与Cassandra技术实现时空大数据存储与索引

随着越来越多的轨迹数据被记载,各种应用场景下的海量、复杂数据需要高效的存储与索引。传统的关系型数据库难以满足海量轨迹数据的存储、扩展及特定的查询需求,而具有扩展简单、读写快速、成本低廉特点的非关系型数据库为此提供了一种可行的解决方案。设计并实现了一种基于Cassandra数据库的数据降维及键值存储、索引方法,可对时空轨迹数据进行高效管理。为进一步提高效率,融合了Hilbert曲线编码技术将空间分割成小单元,并将轨迹数据映射到不同单元中。充分利用时空局部性原理,为不同应用场景下的轨迹数据设计并实现了对应的分区键与聚簇键,实现轨迹对象时空近邻存储,令数据查询更为有效。基于实际应用场景的实验结果表明,所提出的方法能有效支撑海量轨迹数据的存储与索引,并在数据的插入、查询及存储结构可扩展性等方面优于其他时空大数据索引和查询方法。     

基于分层子网的时空索引机制

目前,已有的时空索引机制主要考虑时空对象,缺乏对显式表达的时空关系的索引,不便于因果关系查询,降低了图论时空模型的实用性.这里扩展了图的数学概念,提出了时空图的分割策略,构建了基于分层子网的时空索引机制,实现了时空对象与时空关系索引的一体化,增强了基于图论的时空数据库的灵活性,有利于因果关系的查询.     

多级格网时空索引

在时空数据库中,地理实体模型包括地理对象空间信息和时态信息。为了快速查询实体的空间和时间信息,这就需要一个高效的时空索引机制。本文在分析和参考目前几种时空索引方法的基础上提出了一种新的时空索引方法———多级格网时空索引,并介绍了多级格网时空索引的算法。     

时空信息云平台下数据管理及可视化方法

针对智慧城市时空信息云平台中海量时空数据的管理和可视化问题,该文提出了一种时空索引建立及时空数据可视化方法。时空索引机制将时间、空间与专题属性作为同等重要的维度,兼顾了三者的查询效率,实现对时空数据的快速有效提取。时空数据可视化表达方法提出了时间轴动画、多时态对比、对象状态回溯等可视化方式,实现时空数据的动态交互式表达。该方法在"智慧常州时空信息云平台"项目中进行了实现,证明这种时空数据组织管理方法可较高效地实现数据的检索调度,且具有较强的可操作性;基于此的时空数据可视化方法亦具备较佳的时空对象动态表达效果。     

顾及轨迹压缩的车辆路径查询算法

基于位置服务技术的迅猛发展,产生了巨量车辆轨迹数据。为了有效压缩并查询大规模车辆轨迹数据,本文提出一种面向压缩车辆轨迹的路径空间查询算法。本文算法基于Stroke道路层次结构压缩轨迹空间数据,提取关键变速点压缩轨迹时间数据,并构建了一种用于建立轨迹空间和时间数据之间联系的哈希编码,从而实现车辆轨迹的时空数据集成压缩。利用后缀数组对车辆轨迹的基于Stroke路段的压缩编码构建空间索引结构,再以此为基础,设计了车辆轨迹所对应路径的点信息查询算法、相同子路径查询算法和相似路径查询算法。试验结果表明,针对原始轨迹点空间数据,本文的压缩编码方法压缩比可以达到97∶1,与常规的基于路段编码方式相比,本文压缩编码在车辆轨迹的点信息路径查询方面,查询效率可以提升约2倍;在车辆轨迹的相同子路径查询方面,查询效率可以提升约8倍;在车辆轨迹的相似路径查询方面,查询耗时增长率减少了50%。本文算法对于大规模车辆轨迹的数据管理具有十分重要的基础性作用。     

一种面向道路网3维数据的空间索引方法

根据数据沿道路呈线性分布,道路相互连通的特点,提出连通拓扑和动态分段相结合的混合索引机制,分两步来实现查询过程:第一步通过连通索引来进行粗略查询;第二步根据粗略查询结果,利用动态分段索引完成精确查询。以此建立的道路网及沿线3维数据的空间索引具有很高的查询速度,能确保数据的快速动态装载,可满足道路网3维可视化的要求。最后通过实验对算法进行实现,并在空间效率和时间效率上与R树索引进行了比较。     

对等网络下自适应层级的矢量数据时空索引构建方法

时空索引是时空数据存储和管理的关键技术之一,基于空间填充曲线(space filling curve,SFC)的索引方法近年来受到了广泛关注。然而对于矢量数据,现有索引方法多侧重于空间索引的实现,难以同时顾及时间查询和空间查询的效率,且对于非点要素(线要素与面要素),确定最优的索引级别一直是难点所在。为此,本文面向对等网络环境,提出一种自适应层级的时空索引构建方法。首先提出了基于分区键和分区内排序键组合策略的时空信息联合编码,然后据此设计了点要素、非点要素的时空表达结构,最后设计了多层级树结构以构建时空索引MLS3(multi-level sphere 3),并基于地理实体时间粒度及空间密度等特征自适应确定其最优索引层级。利用轨迹(点要素)、公路(线要素)和建筑物(面要素)实际数据进行了试验。试验结果表明,相比GeoMesa提出的XZ3时空索引,本文索引方法可有效解决非点要素的时空表达及层级划分问题,在避免存储热点的同时实现更为高效的时空检索。     

网络中移动对象的2维时空数据模型

提出一种新的2维网络中移动对象的时空数据模型2-Dimensional Spatio-Temporal data model for Mov-ing Objects in Network(2DSTMON)。2DSTMON时空数据模型基于线性参考思想,将3维空间中的轨迹数据转换到2维空间中进行存储和管理,并采用运动矢量的数据更新方式,具有较小的数据量和较低的更新代价。最后,利用ESRI的ArcEngine实现并验证2DSTMON时空数据模型。     

Indexing and querying moving objects with uncertain speed and direction in spatiotemporal databases

Efficient processing of spatiotemporal queries over moving objects with uncertainty has become imperative due to the increasing need for real-time information in highly dynamic environments. Most of the existing approaches focus on designing an index structure for managing moving objects with uncertainty and then utilize it to improve the query performance. All the proposed indexes, however, have their own limitations. In this paper, we devote to developing an efficient index, named the R ^lsd -tree, to index moving objects with uncertain speed and direction varying within respective known ranges. We design several pruning criteria combined with the R ^lsd -tree to answer the probabilistic range queries. Moreover, two models, the sampling-based probability model and the ER-based probability model, are proposed to quantify the possibility of each object being the query result. Finally, a thorough experimental evaluation is conducted to show the merits of the proposed techniques.     

三维虚拟地球中移动对象的时空数据组织方法

针对三维虚拟地球中实时GIS数据组织、管理与动态可视化的要求,设计了三维虚拟地球中移动对象的时空数据组织方法。提出了基于HR-tree扩展的时空索引方法,实现了对虚拟地球中移动对象的检索与查询,并基于三维虚拟地球平台对本文方法进行了实验,结果验证了本文方法的有效性和可行性。     

Modeling spatiotemporal topological relationships between moving object trajectories along road networks based on region connection calculus

Considering the attempts to model spatiotemporal topological relationships between moving object trajectories, the conceptual and computational framework for moving objects along a road network has not received much attention. This paper aims to draw an improved model based on Region Connection Calculus (RCC) theory to represent the spatiotemporal topological relationships between moving object trajectories along road networks. This paper first uses a dimension reduction method based on a linear-reference transformation to model the moving object trajectories segments, and then defines new time–connection and space–connection relations between two trajectory segments. On this basis, the paper proposes an extension to the RCC-based spatiotemporal binary relationship set so that the combined semantics of the spatiotemporal predicates can be described completely. A case study was carried out using Floating Car Data in Guangzhou city. The computational results show that in a real application, the occurrence frequencies of the RCC-based binary relationships are distributed nonuniformly and the semantics of some binary relationships with the highest occurrence are coarse. Therefore, the partition of the spatiotemporal connection relations and the finer aspects of the spatiotemporal relationship model may require further research work.     

Spatiotemporal retrieval of dynamic video object trajectories in geographical scenes

Current studies on video trajectory retrieval focus on the retrieval and analysis of image content, neglecting the gap between the spatiotemporal continuity of retrieval conditions and the spatiotemporal discontinuity of multi‐camera video trajectories. In this study, we propose a method for the spatiotemporal retrieval of dynamic video object trajectories in geographic scenes. Based on the camera calibration, the proposed method organizes the scene, cameras, and trajectories, constructs the spatiotemporal constraints, and queries the trajectories using two measures: camera‐by‐camera retrieval and global trajectory retrieval. The proposed method was verified through experiments, and the results demonstrate that both measures can query trajectories effectively and reduce the spatiotemporal video review range under different spatiotemporal constraints. Furthermore, compared with camera‐by‐camera retrieval, global trajectory retrieval can reduce the spatiotemporal video review range further and return more accurate results. The proposed method may provide support for the spatial analysis and understanding of surveillance video data.     

A spatiotemporal algebra in Hadoop for moving objects

Spatiotemporal data represent the real-world objects that move in geographic space over time. The enormous numbers of mobile sensors and location tracking devices continuously produce massive amounts of such data. This leads to the need for scalable spatiotemporal data management systems. Such systems shall be capable of representing spatiotemporal data in persistent storage and in memory. They shall also provide a range of query processing operators that may scale out in a cloud setting. Currently, very few researches have been conducted to meet this requirement. This paper proposes a Hadoop extension with a spatiotemporal algebra. The algebra consists of moving object types added as Hadoop native types, and operators on top of them. The Hadoop file system has been extended to support parameter passing for files that contain spatiotemporal data, and for operators that can be unary or binary. Both the types and operators are accessible for the MapReduce jobs. Such an extension allows users to write Hadoop programs that can perform spatiotemporal analysis. Certain queries may call more than one operator for different jobs and keep these operators running in parallel. This paper describes the design and implementation of this algebra, and evaluates it using a benchmark that is specific to moving object databases.     

Use of a Three-Domain Repesentation to Enhance GIS Support for Complex Spatiotemporal Queries

As the development of Geographic Information Systems (GIS) proceeds to advanced scientific and societal applications, there is an emerging need to enhance GIS support for complex spatiotemporal queries. Dynamic GIS representations (as opposed to static, map-based representations) that can integrate proper data elements in the production of geographic information are required. This paper demonstrates the use of a three-domain representation that facilitates compilation of higher-level information (such as frequency and rate) from preliminary data records (such as time and location) stored in a database. The three-domain representation is compared with snapshot, space-time composite, and spatiotemporal object models using a sample data set for forest transitions. While the three-domain representation is a normalization of these data models, it offers a conceptual alternative that enables GIS to represent spatiotemporal behaviors of geographic entities, in addition to entities as well as histories at locations as emphasized in most GIS data models. The comparison shows that the three-domain representation has combined the strengths of the space-time composite and spatiotemporal object models. Moreover, it enables aggregations of analytical use along with dynamic mappings between geographic concepts and locations, a distinct capability that takes GIS query processing beyond the level of information support offered by static map-based data models.     

基于历史拓扑和描述子的时空数据模型

针对已有时空数据模型在表达时空信息上存在的问题,提出基于一个新的历史拓扑和描述子的时空数据模型STORM.STORM采用结合显式表达和隐式表达的混合型方法来表示时空信息,其中历史拓扑显式表达时空对象间的历史关联,而描述子隐式表达单个时空对象的内部属性变化以及时空对象间的空间拓扑关系.该模型可以同时表达时空信息的静态语义和动态语义,并可通过扩展的关系结构和关系代数操作进行表示和查询.     

实时GIS时空数据模型

为满足动态目标与传感器等实时观测数据获取、存储、管理、分析与可视化的要求,需要发展一种新型地理信息系统—实时GIS。本文根据实时GIS中各种地理要素的特点以及存贮管理要求,提出了一种面向动态地理对象与动态过程模拟的实时GIS时空数据模型,它将时空过程、地理对象、事件、事件类型、状态、观测等相关要素整合在一个时空数据模型中。基于该模型研发了新一代实时GIS,并以四种动态地理对象（包括移动对象、原位传感器对象、视频对象和过程模拟对象）的时空数据的实时接入、存储与可视化为例,验证的模型的可行性。     

基态修正模型的时空数据组织和快照查询方法研究

基态修正模型是目前应用较广的一种时空数据模型。本文分析了基态修正模型中的时空数据特点,采用shapefile文件作为基态数据文件,自主设计差文件格式来存储和组织变化数据。在此基础上设计了快照查询的算法、流程和查询结果的显示方法。为了给用户提供更直观、更充分的时空信息,本文提出了一种双屏幕多视图的时空数据显示模式。采用VC．NET从底层开发了一个时态地理信息系统平台,并以中南大学主校区的时空数据为实验数据对上述算法和模式进行了检验。实验表明,本文所设计的算法可行,快照显示模式能够提供更直观、更丰富、对比性强的信息内容,是时空信息显示的一种可行模式。