Definitions of natural-language spatial relations: Combining topology and directions

Because SQL for querying data from spatial databases is ineffective, the query based on natural or visual language becomes an attractive research field gradually. However, how to define and represent natural languages related to spatial data are still gigantic problems. Because existing models of direction relations can't describe by use of some common concepts. First of all, detailed direction relations are proposed to describe the directions related to the interior of spatial objects, such as “east part of a region”, “east boundary of a region”, and so on. Secondly, by integrating the detailed directions with exterior direction relations and topological relations, several NLSRs are defined, such as “a road goes across the east part of a lake”, “a river goes along the east boundary of a province”, etc. Finally, based on the NLSRs abovementioned, a natural spatial query language (NSQL) is formed to retrieve data from spatial databases.     

Analysis of the relations among spatial tessellations

A spatial tessellation is a set of regions that are collectively exhaustive and mutually exclusive except for the boundaries. In geographical analysis, it may represent such administrative units as census tracts, postal zones, and electoral or school districts. Spatial tessellations of a certain area are often closely related to each other. Areas of local communities are related to school districts, market areas of retail stores, and administrative units. Postal zones and census tracts are determined by collecting or dividing administrative units. Analysis of such relations among tessellations often reveals their underlying spatial phenomena. To this end, this paper proposes a new exploratory method for analyzing the relations among spatial tessellations. It aims to detect spatial patterns, especially those with a hierarchical structure, and to provide a tessellation classification scheme. Topological relations and similarity measures are introduced to evaluate the relations between tessellation pair. For more tessellations, tree representations are proposed. These not only visualize relations, but also provide a means of classifying tessellations. The method is applied to the analysis of two sets of spatial tessellations: one with five hypothetical tessellations, and another with 34 candidate plans for the new Doshusei administrative system in Japan. The application reveals the properties of the method and quantitative measures used in analysis.     

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.     

空间查询中自然语言空间关系与度量空间关系的转换方法研究:以面目标为例

以面目标为例,首先探讨度量空间关系的描述方法,即拓扑谓词+度量参数,建立拓扑谓词与度量参数之间的对应关系;然后从人的认知角度,分析空间关系的自然语言描述,即拓扑谓词+量词,区分模糊量词和临界量词两类量词,并分别用来描述邻近拓扑谓词相互转化过程中的定量变化和定性变化;最后,分析度量参数与量词之间的关联关系,试图建立空间查询中度量空间关系与自然语言空间关系之间的联系,从而更好地应用于空间查询.

Abstract：

Spatial relations between spatial entities can be obtained by two means. One is computed and obtained by spatial data, and the other is obtained by human spatial cognition. So, they are named as metric spatial relations and natural-language spatial relations, respectively. This paper is focused on filling the gap between these two kinds of spatial relations. For this purpose, regions are taken as example, and three steps are included. Metric spatial relations ore first depicted by combining topological predicates with metric parameters, where a mapping is built between the topological predicates and the metric parameters. Second, natural-language spatial relations are represented by combining topological predicates with quantifiers, where quantifiers are differentiated into two types:vague quantifiers and critical quantifiers. They are respectively used to describe quantitative and qualitative change in the process of the transformation between neighboring topological predicates. Finally, the association between metric parameters and quantifiers is further illustrated and analyzed by a questionnaire. With these three steps, the linkage can be built between metric spatial relations and natural-language spatial relations. The proposed methods have been proven to be rational by the performances of spatial query.     

带多个空洞的面对象间拓扑关系的层次组合模型

空间拓扑关系描述是空间关系的主要内容,是与人类的认知概念一致的,在空间数据查询与挖掘等方面有重要应用。很多学者研究了不带空洞的面对象间的拓扑关系,但对于带空洞的面对象间的拓扑关系研究甚少。首先回顾了现有模型,并指出了各模型的优缺点,然后根据简单面对象的8种基本空间拓扑关系,对带多个空洞的面对象的拓扑关系进行了层次组合分析,提出了一种能描述带多个空洞的复杂面对象间的拓扑关系的层次组合模型。该模型能描述带多个空洞的复杂面对象间的所有拓扑关系,而且不因面对象中空洞的编号顺序不同导致模型所描述的结果不同,同时也弥补了4-4ID模型只能描述带一个空洞的面对象的不足。     

Spatial Planning on the Semantic Web

Land use regulations are an important but often underrated legal domain. In densely populated regions such as the Netherlands, spatial plans have a profound impact on both (local) governments and citizens. This article describes our work on a ‘Legal Atlas’. Using Semantic Web technology we combine distributed geospatial data, textual data and controlled vocabularies to support users in answering questions such as: “What activity is allowed here?” Spatial norms are represented using OWL 2 in a way that enables intuitive visualisation of their effects: map‐based legal case assessment. Users can represent a (simple) case by selecting or drawing an area on the map. Given a designation for that area, the system can assess whether this is allowed or not. The same solution also enables the comparison of two or more sets of spatial norms that govern the same region. We discuss the advantages and drawbacks of a number of alternative solutions for representing and integrating metadata of spatial plans, and the representation of normative conflicts and exceptions between norms.     

基于拓扑关系的不确定区域方向关系推理

利用宽边界区域对多种来源的不确定性数据建模,用确定区域的拓扑和方向关系组合描述不确定区域的拓扑和方向关系。根据拓扑关系和方向关系间内在规律,直接从不确定区域的拓扑符号描述中推理出方向关系的符号描述,是对已有推理方法的有益补充。     

一种个人地理标记数据的可视化方法

个人地理标记数据是个人通过笔记本、平板电脑或者手机等设备发布的包含地理位置且与个人相关的文本、照片和视频等信息。本文针对个人地理标记数据的特点,提出了一种适用于地理标签数据的可视化方法——个人地理标记数据拓扑图,并设计和实现了核心算法。为了比较和评估该方法的效能,对"文本列表""普通地图"和"标记拓扑图"3种用户界面进行了可用性测试,并对测试数据进行了方差分析。测试结论表明,3种不同用户界面在查找个人地理标记数据的效率方面存在显著性差异,其中文本列表和标记拓扑图均优于普通地图,文本列表和标记拓扑图在查找时间上的差异并不显著,标记拓扑图在查找时间均值上略优于文本列表。     

Topological relations between spherical spatial regions with holes

ABSTRACT

There is growing interest in globally modelling the entire planet. Although topological relations between spherical simple regions and topological relations between regions with holes in the plane have been investigated, few studies have focused on the topological relations between spherical spatial regions with holes. The 16-intersection model (16IM) is proposed to describe the topological relations between spatial regions with holes. A total of 25 negative conditions are proposed to eliminate the impossible topological relations between spherical spatial regions with holes. The results show that (1) 3 disjoint relations, 3 meet relations, 66 overlap relations, 7 cover relations, 3 contain relations, 1 equal relation, 7 coveredBy relations, 3 inside relations, 1 attach relation, 52 entwined relations, and 28 embrace relations can be distinguished by the 16IM and that (2) the formalisms of attach, entwined, and embrace relations between the spherical spatial regions without holes based on the 9IM and that between the spherical spatial regions with holes based on the simplified 16IM are different, whereas the formalisms of other types of relations between spherical spatial regions without holes based on the 9IM and that between the spherical spatial regions with holes based on a simplified 16IM are the same.     

利用灰集进行空间区域拓扑关系不确定性定量分析

针对不确定性空间区域对象间拓扑关系不确定性的定量分析问题,提出了一种具有双隶属度函数的灰集表示模型,利用双隶属度函数的截集将不确定性空间区域对象转化为确定性区域对,借用相关的不确定性空间拓扑关系定性分析模型,将不确定性空间对象间拓扑关系的不确定性量化为一个可信度区间。     

Quantitative fuzzy topological relations of spatial objects by induced fuzzy topology

This paper presents a study on the modeling of fuzzy topological relations between uncertain objects in Geographic Information Systems (GIS). Based on the recently developed concept of computational fuzzy topological space, topological relations between simple fuzzy spatial objects are modeled. The fuzzy spatial objects here cover simple fuzzy region, simple fuzzy line segment and fuzzy point. To compute the topological relations between the simple spatial objects, intersection concepts and integration methods are applied and a computational 9-intersection model are proposed and developed. There are different types of intersection, and we have proposed different integration methods for computation in different cases. For example, surface integration method is applied to the case of the fuzzy region-to-fuzzy region relation, while the line integration method is used in the case of fuzzy line segment-to-fuzzy line segment relation. Moreover, this study has discovered that there are (a) sixteen topological relations between simple fuzzy region to line segment; (b) forty-six topological relations between simple fuzzy line segments; (c) three topological relations between simple fuzzy region to fuzzy point; and (d) three topological relations between simple fuzzy line segment to fuzzy point.     

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.     

不确定拓扑关系模糊推理

针对定性空间推理难以处理不确定空间拓扑关系推理的缺憾,将确定拓扑关系复合表推理方法扩展到模糊拓扑空间,建立了基于拓扑关系复合表的不确定拓扑关系模糊推理模型,设计了基于RCC5的拓扑关系复合表的模糊推理规则库和推理的方法流程,并结合具体计算实例对模糊推理模型进行了实验研究,推理结果验证了模型的认知合理性和可行性。     

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。     

带空洞的复杂面域间拓扑关系的形式化描述

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合及其分量集合拓扑特性变化基础之上的。对于两个简单面域间的空间拓扑关系描述研究已经很多,而对于带空洞的复杂面域间的空间拓扑关系的描述却相对较少。本文利用Egenhofer等提出的描述带空洞的面域间空间拓扑关系描述框架,在四交差模型的基础上,提出一种能描述带空洞的复杂面域间拓扑关系的扩展模型———D-4 ID模型,并用该模型推导了一个简单面域和一个带空洞的复杂面域间有意义的23种拓扑关系。     

基于粗集的多尺度空间拓扑关系不确定性定量评价模型

空间拓扑关系不确定性的定量评价可为多尺度拓扑关系一致性的自动评价、空间推理与空间查询等应用的可靠性提供依据。定义了基于几何度量的拓扑距离,构建了拓扑关系不确定性的粗集表达模型;提出了不确定性粗集表达中拓扑距离的量化方法;进而提出了基于粗集的多尺度空间拓扑关系不确定性度量指标。实例研究证明了本文提出模型的科学性与合理性,该方法可用于多尺度表达过程中引起的拓扑关系不确定性的定量评价。     

不确定性线状目标之间拓扑关系的描述与判别

总结了常见的不确定性线状目标描述模型以及确定性线状目标之间拓扑关系的描述模型，并在此基础上提出了一种定量化分析方法，对不确定性线状目标之间的拓扑关系进行了描述和判别。     

基于拓扑约束的方向关系定性描述模型

针对原有方向关系矩阵模型对于参考目标MBR区域的方向描述缺陷问题,本文将拓扑约束引入方向关系定性描述,构建基于拓扑参考的方向关系定性描述模型,实现了MBR区域方向关系的有效表达。新模型首先将参考目标的MBR区域划分为不同的拓扑区域,提出方向关系拓扑参考定义;基于拓扑参考,分别对不同拓扑区域定义相应的方向关系矩阵;最后,根据参考目标与源目标间的不同拓扑关系,提出不同情况下方向关系分层定性描述策略。实验结果表明,新模型充分反映了拓扑关系对方向关系描述的约束关系,能有效提高方向关系表达的准确性和精确性。     

Definitions of Natural-Language Spatial Relations： Combining Topology and Directions

Introduction Inmanyapplications(CADandgeographical informationsystem,GIS),dataaremanagedby spatialdatabases,whichstorepoint,line,region objectsandspatialrelationsbetweenthem.Spa tialrelations(topologicalrelations,directionre lationsandapproximatedistancer…     

带孔洞面域间的拓扑关系的组合推理

空间对象间拓扑关系是GIS中空间要素间最基本也是最重要的关系之一,是进行空间查询和分析的基础,因而空间对象间拓扑关系一直是研究的热点之一。目前,对拓扑关系模型的研究主要集中在简单对象间拓扑关系方面,而对于带空洞的复杂面域间的空间拓扑关系的研究则相对较少,因而对它的进一步研究具有较重要的理论意义。本文在文献[11]的基础上,根据点集拓扑学理论,对带孔面域进行了定义。通过分析简单对象间拓扑关系的演变过程,提出一种能描述带一个孔的面域间的空间拓扑关系的方法,并用该方法详细推导了带一个孔的面域间有意义的拓扑关系。通过实验验证,证明该方法在理论上是可行的,对提高GIS对现实世界的建模和分析能力可提供一定的理论依据。