一种基于关键点的轨迹-区域拓扑过程模型

定位技术的广泛应用带来了铺天盖地的移动数据,为诸如时空查询和数据挖掘等各种时空的研究及应用提供了重要素材,使得对于轨迹数据的研究成为当前的一个热点。当前,无论是对于原始轨迹数据的研究,还是对语义化轨迹数据的研究,都较少考虑轨迹移动过程中所潜藏的拓扑不变量。本文提出二维空间上基于关键点的轨迹-区域拓扑过程模型,以矩阵描述轨迹与区域的14种基本点集拓扑交叠类型,既而组织交叠序列描述轨迹和区域对象间的拓扑关联关系。模型不仅描述了轨迹与区域之间的拓扑不变量,而且结合轨迹特有行为的语义关联模型,描述轨迹相对区域的复杂拓扑过程。同时,本文还以模型中相邻两次交叠的相接交叠模式,探讨了区域间拓扑关系对于轨迹移动描述的约束。     

Extracting spatial patterns in bicycle routes from crowdsourced data

Much is done nowadays to provide cyclists with safe and sustainable road infrastructure. Its development requires the investigation of road usage and interactions between traffic commuters. This article is focused on exploiting crowdsourced user‐generated data, namely GPS trajectories collected by cyclists and road network infrastructure generated by citizens, to extract and analyze spatial patterns and road‐type use of cyclists in urban environments. Since user‐generated data shows data‐deficiencies, we introduce tailored spatial data‐handling processes for which several algorithms are developed and implemented. These include data filtering and segmentation, map‐matching and spatial arrangement of GPS trajectories with the road network. A spatial analysis and a characterization of road‐type use are then carried out to investigate and identify specific spatial patterns of cycle routes. The proposed analysis was applied to the cities of Amsterdam (The Netherlands) and Osnabrück (Germany), proving its feasibility and reliability in mining road‐type use and extracting pattern information and preferences. This information can help users who wish to explore friendlier and more interesting cycle patterns, based on collective usage, as well as city planners and transportation experts wishing to pinpoint areas most in need of further development and planning.     

基于GPS时空轨迹的路网拓扑自动变化检测

充分利用出租车GPS时空轨迹数据分布广和时效性强的特点,提出一种基于车载GPS轨迹数据的路网拓扑自动变化检测新方法。该方法首先利用向量相似性度量模型,度量GPS轨迹向量与路网局部拓扑向量之间的相似性,检测疑似道路拓扑变化点,然后通过比较疑似道路拓扑变化点与路网拓扑关系,完成新增、废弃、改建等道路变化,实现基于车载GPS轨迹的路网拓扑自动变化检测。实验结果表明,该方法不仅有效地检测出道路新增、道路废弃与道路改扩建等变化,而且能利用出租车实时和大范围分布特点来实现城市路网大范围实时变化检测。     

面状目标之间空间拓扑关系的组合式分类

在空间目标拓扑关系组合式描述的基础上,分析了基本空间拓扑关系的组合方法,并根据基本空间拓扑关系,提出了面状目标之间空间拓扑关系的两种分类体系,详细绘制了相应的空间拓扑关系图。     

线与面的空间拓扑关系组合推理

在原先所提出的空间拓扑关系组合描述的基础上，进一步完善了利用基本空间拓扑关系进行组合推理的方法，并建立了推理表，详细绘制了线与面的所有空间拓扑关系图。     

Analytical queries on semantic trajectories using graph databases

This article studies the analysis of moving object data collected by location‐aware devices, such as GPS, using graph databases. Such raw trajectories can be transformed into so‐called semantic trajectories, which are sequences of stops that occur at “places of interest.” Trajectory data analysis can be enriched if spatial and non‐spatial contextual data associated with the moving objects are taken into account, and aggregation of trajectory data can reveal hidden patterns within such data. When trajectory data are stored in relational databases, there is an “impedance mismatch” between the representation and storage models. Graphs in which the nodes and edges are annotated with properties are gaining increasing interest to model a variety of networks. Therefore, this article proposes the use of graph databases (Neo4j in this case) to represent and store trajectory data, which can thus be analyzed at different aggregation levels using graph query languages (Cypher, for Neo4j). Through a real‐world public data case study, the article shows that trajectory queries are expressed more naturally on the graph‐based representation than over the relational alternative, and perform better in many typical cases.     

A Spatio‐Temporal Graph Model for Marine Dune Dynamics Analysis and Representation

Defining a model for the representation and the analysis of spatio‐temporal dynamics remains an open domain in geographical information sciences. In this article we investigate a spatio‐temporal graph‐based model dedicated to managing and extracting sets of geographical entities related in space and time. The approach is based on spatial and temporal local relations between neighboring entities during consecutive times. The model allows us to extract sets of connected entities distant in time and space over long periods and large spaces. From GIS concepts and qualitative reasoning on space and time, we combine the graph model with a dedicated spatial database. It includes information on geometry and geomorphometric parameters, and on spatial and temporal relations. This allows us to extend classical measurements of spatial parameters, with comparisons of entities linked by complex relations in space and time. As a case study, we show how the model suggests an efficient representation of dunes dynamics on a nautical chart for safe navigation.     

在图形简化中面状目标间拓扑关系渐进式转换的研究

拓扑关系是空间关系中最为重要的关系,在空间抽象中,拓扑关系会发生变化,如何控制这种变化?如何在更抽象的层次上维护空间拓扑关系的一致性,就是一个非常重要的问题。本文以拓扑关系成分抽象的转换方法为基础,研究了面之间拓扑关系的抽象规则,并详细探讨了这些拓扑关系的渐进式转换方法,绘制了相应的面之间基本拓扑关系渐进式转换图。     

Homological relations: A methodology for the certification of irregular tessellations

In GIS, spatial analysis is based on the use of spatial operations such as testing the spatial relations between features. Often, such tests are invalidated by errors in datasets. It is a very common experience that two bordering regions which should obey the topological relation “meet” fall instead in the “overlap” category. The situation is exacerbated when applying topological operators to regions that come from different datasets, where resolution and error sources are different. Despite the problem being quite common, up to now no standard approach has been defined to deal with spatial relations affected by errors of various origins. Referring to topological relations, we define a model to extend the eight Egenhofer relations between two simple regions: we call them homological relations (H‐relations). We discuss how exact topological relations can be extracted from observed relations and discuss the case of irregular tessellations, where errors have the most impact on vector data. In the proposed case study within the domain of geographic crowdsourced data, we propose algorithms for identifying homological regions and obtaining a corrected tessellation. This methodology can be considered as a step for quality control and the certification of irregular tessellations.     

Topological relations between a directed line and a directed region

Representing the topological relations between directed spatial objects has gained increasing attention in recent years. Although topological relations between directed lines and other types of spatial objects, such as regions and bodies, have been widely investigated, few studies have focused on the topological relations between directed lines and directed regions. This research focuses on the representation and application of directed line–directed region (DLDR) topological relations, and may contribute to spatial querying and spatial analyses related to directed spatial objects or time‐varying objects. Compared with other topological relation models, a DLDR model that considers the starting and ending points of the directed line and the front and back faces of directed regions is proposed in this research to describe the topological relations between directed lines and directed regions. DLDR topological relations are presented, the completeness of the 111 DLDR topological relations is proved, and the topological relations based on the 9‐intersection model (9IM), 9⁺‐intersection model (9⁺‐IM), and DLDR model are compared. The formalism of the DLDR model and the corresponding geometric interpretations of the 111 DLDR topological relations are presented, seven propositions are stated to prove the completeness of the 111 DLDR topological relations, and the case study shows that more detailed topological relation information can be obtained based on the DLDR model.     

移动目标空间拓扑关系的度量描述

针对传统9交模型对移动目标空间拓扑关系表达及量化描述的不足，基于格网化思想，提出了度量参数量化描述的方法。首先对移动目标和参考目标进行格网化，划分为固定大小的格网阵列；然后利用9交模型确定空间目标间拓扑关系的形式化描述；最后引入内部分量、边界分量、外部分量3种度量参数对移动目标空间拓扑关系进行度量化描述。试验证明，该方法计算简单、直观，能更加有效地度量移动目标间的拓扑关系。     

Polygonal Clustering Analysis Using Multilevel Graph‐Partition

Existing methods of spatial data clustering have focused on point data, whose similarity can be easily defined. Due to the complex shapes and alignments of polygons, the similarity between non‐overlapping polygons is important to cluster polygons. This study attempts to present an efficient method to discover clustering patterns of polygons by incorporating spatial cognition principles and multilevel graph partition. Based on spatial cognition on spatial similarity of polygons, four new similarity criteria (i.e. the distance, connectivity, size and shape) are developed to measure the similarity between polygons, and used to visually distinguish those polygons belonging to the same clusters from those to different clusters. The clustering method with multilevel graph‐partition first coarsens the graph of polygons at multiple levels, using the four defined similarities to find clusters with maximum similarity among polygons in the same clusters, then refines the obtained clusters by keeping minimum similarity between different clusters. The presented method is a general algorithm for discovering clustering patterns of polygons and can satisfy various demands by changing the weights of distance, connectivity, size and shape in spatial similarity. The presented method is tested by clustering residential areas and buildings, and the results demonstrate its usefulness and universality.     

Classification of topological relations between spatial objects in two‐dimensional space within the dimensionally extended 9‐intersection model

As an important topological relation model, the dimensionally extended 9‐intersection model (DE‐9IM) has been widely used as a basis for standards of queries in spatial databases. However, the negative conditions for the specification of the topological relations within the DE‐9IM have not been studied. The specification of the topological relations is closely related to the definition of the spatial objects and the topological relation models. The interior, boundary, and exterior of the spatial objects, including the point, line, and region, are defined. Within the framework of the DE‐9IM, 43 negative conditions are proposed to eliminate impossible topological relations. Configurations of region/region, region/line, line/line, region/point, line/point, and point/point relations are drawn. The mutual exclusion of the negative conditions is discussed, and the topological relations within the framework of 9IM and DE‐9IM are compared. The results show that: (1) impossible topological relations between spatial objects can be eliminated by the application of 43 negative conditions; and (2) 12 relations between two regions, 31 relations between a region and a line, 47 relations between two lines, three relations between a region and a point, three relations between a line and a point, and two relations between two points can be distinguished by the DE‐9IM.     

基于线段的基本线/线拓扑关系计算

空间拓扑关系是空间数据建模、空间查询、分析、推理、制图综合、数据质量控制、数据更新等的基础。目前空间拓扑关系研究的主要成果仍然集中在拓扑关系的描述方面,在计算方面的阐述都非常薄弱,不足以指导系统开发人员编程实现。本文研究了IR2中两个简单线目标间拓扑关系的计算方法,重点分析了线/线拓扑关系计算的特点,提出了一种基于线段的线/线拓扑关系计算方法,并用VC＋＋采用底层开发模式实现了基本线/线拓扑关系的计算。     

GIS面目标间拓扑关系的形式化模型

拓扑关系的描述和区分是建立在空间目标相互作用过程中目标集及其分量集合拓扑特性变化基础之上的.建立了GIS中拓扑关系形式化描述和区分的一种广义模型,并与已有的形式化模型进行了比较分析,结果发现现有的形式化方法和模型是广义模型的一些特例.在此基础上,进一步提出了面目标间拓扑关系形式化描述的基本模型,并根据定义的拓扑距离和拓扑复杂性概念,建立了一个新的拓扑关系概念邻域图.     

基于GIS与旅行商问题的自驾游路径设计

自驾游以自主性、灵活性、选择性以及多样性等内在特点吸引着许多人,而它的线路设计质量直接影响自驾游者的心理满意度。通过收集、梳理河南省优秀旅游资源的空间分布、景区详情、交通道路等信息,依据旅游学中旅游行为空间模式、数学中图论和旅行商问题、地理信息系统(GIS)等科学理论,设计河南省自助游的最佳旅游线路。本研究以具有河南代表性的旅游景区为实际空间数据源,以ArcGIS系统为空间分布、交通等属性信息的可视化工具,以图论和旅行商问题为路线设计的数学基础,构建出自驾游线路设计的模式。本研究方法简单科学,为广大自驾游者规划旅游线路提供了有实际意义的参考。     

基于V9I的空间关系映射与操作

利用V9I模型中目标的边界、内部和Voronoi区域均可量测及易于操作的特点 ,研究建立底层数据结构与空间关系语义层之间的V9I映射机制 ,在Voronoi的动态栅格生成算法的基础上 ,构建空间关系的基本操作。最后 ,以VC 为开发工具并采用面向对象的技术 ,设计了基于V9I的空间关系操作工具原型VTKit ,并给出部分操作实例     

基于拓扑联动的增量更新方法研究——以地籍数据库为例

针对GIS数据库的联动更新及其拓扑一致性维护困难的问题,提出一种基于拓扑联动的增量更新方法,其是针对不同目标类型,分析归纳出相应的拓扑联动类型及其细分类型;对不同目标发展根据其语义特点、拓扑一致性约束条件及变化前后目标间的拓扑关系来推断实体变化类型的规则,并以此为基础分析或推断出每种拓扑联动类型中原关联目标和新生目标的变化情况,进而设计和执行相应的更新操作实现数据库的局部联动更新及其拓扑一致性维护.全文以地籍数据库更新为例,将地籍变更分为地块合并、分割、公共边界调整、结点移动、复合分并5种基本联动类型,并对地块合并、分割、公共边界调整进行了细分,共分为17种细分类型;归纳出地块目标的变化类型推断规则,用实际与模拟数据对本文所提出的方法进行实验验证.本文所提出的方法为此类系统的设计与开发提供了一条新的思路.     

基于矢量数据模型的模糊地理对象建模

研究了模糊地理对象建模的空间建模方法，首先以对象建模方法定义模糊地理对象，以矢量数据模型为基础，用UML设计模糊对象类和模糊地理对象类，然后以统一的UML图表示基本模糊地理对象的概念模型，尤其是模糊拓扑关系，最后将UML图直接导入通用关系数据库，完成数据库的设计。