Spatial object aggregation based on data structure,local triangulation and hierarchical analyzing method

This paper focuses on the methods and process of spatial aggregation based on semantic and geometric characteristics of spatial objects and relations among the objects with the help of spatial data structure (Formal Data Structure), the Local Constrained Delaunay Triangulations and semantic hierarchy. The adjacent relation among connected objects and unconnected objects has been studied through constrained triangle as elementary processing unit in aggregation operation. The hierarchical semantic analytical matrix is given for analyzing the similarity between objects types and between objects. Several different cases of aggregation have been presented in this paper.     

A Multiscale Approach for Spatio-Temporal Outlier Detection

A spatial outlier is a spatially referenced object whose thematic attribute values are significantly different from those of other spatially referenced objects in its spatial neighborhood. It represents an object that is significantly different from its neighbourhoods even though it may not be significantly different from the entire population. Here we extend this concept to the spatio‐temporal domain and define a spatial‐temporal outlier (ST‐outlier) to be a spatial‐temporal object whose thematic attribute values are significantly different from those of other spatially and temporally referenced objects in its spatial or/and temporal neighbourhoods. Identification of ST‐outliers can lead to the discovery of unexpected, interesting, and implicit knowledge, such as local instability or deformation. Many methods have been recently proposed to detect spatial outliers, but how to detect the temporal outliers or spatial‐temporal outliers has been seldom discussed. In this paper we propose a multiscale approach to detect ST‐outliers by evaluating the change between consecutive spatial and temporal scales. A four‐step procedure consisting of classification, aggregation, comparison and verification is put forward to address the semantic and dynamic properties of geographic phenomena for ST‐outlier detection. The effectiveness of the approach is illustrated by a practical coastal geomorphic study.     

RS与GIS一体化数据结构的研究

详细阐述了RS与GIS一体化的概念 ,通过对RS与GIS一体化方面的研究与分析 ,进一步明确RS与GIS一体化对空间数据存储结构的要求 ,着重探讨了几种典型的用于RS与GIS一体化的数据结构 ,针对现有数据结构存在的问题与不足 ,提出了一种具有普遍适用价值的基于语义网络的空间数据存储结构 ,并给出一个应用实例     

土地利用数据综合中的聚合与融合

针对土地利用图中多边形地块具有全覆盖、无重叠、语义上多层次的特点对土地利用数据综合中的地块合并给出了多边形聚合与多边形融合两种操作；前者针对具有同属性的语义邻近地块的合并，后者针对不同属性的拓扑邻近地块的合并；两种操作的区分是基于同时顾及空间、语义特征的邻近分析，算法的实现均建立在Delaunay三角网模型上由骨架线支持；详细讨论了两种操作的算法过程并给出了实际数据的实验结果。     

Database structure for the integration of RS with GIS based on semantic network

The integration of remote sensing (RS) with geographical information system (GIS) is a hotspot in geographical information science. A good database structure is important to the integration of RS with GIS, which should be beneficial to the complete integration of RS with GIS, able to deal with the disagreement between the resolution of remote sensing images and the precision of GIS data, and also helpful to the knowledge discovery and exploitation. In this paper, the database structure storing the spatial data based on semantic network is presented. This database structure has several advantages. Firstly, the spatial data is stored as raster data with space index, so the image processing can be done directly on the GIS data that is stored hierarchically according to the distinguishing precision. Secondly, the simple objects are aggregated into complex ones. Thirdly, because we use the indexing tree to depict the relationship of aggregation and the indexing pictures expressed by 2-D strings to describe the topology structure of the objects, the concepts of surrounding and region are expressed clearly and the semantic content of the landscape can be illustrated well. All the factors that affect the recognition of the objects are depicted in the factor space, which provides a uniform mathematical frame for the fusion of the semantic and non-semantic information. Lastly, the object node, knowledge node and the indexing node are integrated into one node. This feature enhances the ability of system in knowledge expressing, intelligent inference and association. The application shows that this database structure can benefit the interpretation of remote sensing image with the information of GIS.     

DATABASE STRUCTURE FOR THE INTEGRATION OF RS WITH GIS BASED ON SEMANTIC NETWORK

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Ontology‐supported Querying of Geographical Databases

Querying geographical information systems has been recognized as a difficult task for non‐expert users. Furthermore, user queries are often characterized by semantic aspects not directly managed by traditional spatial databases or GIS. Examples of such semantic geospatial queries are the use of implicit spatial relations between objects, or the reference of domain concepts not explicitly represented in data. To handle such queries, we envisage a system that translates natural language queries into spatial SQL statements on a database, thus improving standard GIS with new semantic capabilities. Within this general objective, the contribution of this article is to introduce a methodology to handle semantic geospatial queries issued over a spatial database. This approach captures semantics from an ontology built upon the spatial database and enriched by domain concepts and properties specifically defined to represent the localization of objects. Some examples of the use of the methodology in the urban domain are presented.     

用贝叶斯分类方法和本体实现空间信息语义互操作

构建了异构空间信息系统语义互操作的框架，通过基于本体的语义异构空间信息的概念级匹配机制，并利用贝叶斯分类方法完成空间信息实例级的重分类，实现了语义互操作。     

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。     

面向空间要素基元对象--关系模式的新型GIS软件技术研究

面向图层处理单元的GIS数据模型、数据处理模式已不再适应大规模海量空间数据组织、处理以及网络分发的需要。文章提出以空间要素基元处理取代传统的面向图层处理的模式,并在对象-关系数据库(ORDBMS)统一框架下构筑、组织、存储、处理空间数据,最终形成基于ORDBMS的GIS应用。     

邻接凸多边形方向关系计算及其推理

在对拓拟邻接凸多边形方向关系计算特殊性分析的基础上，提出了一个邻接凸多边形方向关系计算法和二维空间方向关系推理方法。与Voronoi图所表达的邻近拓扑关系相结合，该算法可以用于计算离散二维空间目标之间的方向关系。     

Measurement of similarity for spatial directions between areal objects

Similarity for spatial directions plays an important role in GIS. In this paper, the conventional approaches are analyzed. Based on raster data areal objects, the authors propose two new methods for measuring similarity among spatial directions. One is to measure the similarity among spatial directions based on the features of raster data and the changes of distances between spatial objects, the other is to measure the similarity among spatial directions according to the variation of each raster cell centroid angle. The two methods overcome the complexity of measuring similarity among spatial directions with direction matrix model and solve the limitation of small changes in direction. The two methods are simple and have broader applicability.     

基于语义的多细节层次3维房产模型

针对2维房产管理中的产权重叠、表达不完全和建筑物室内外一体化管理难题,在综合分析3维房产数据的对象类型及其应用特性的基础上,从概念层次提出了一种基于语义的多细节层次3维房产模型。该模型通过空间与产权的语义描述,对3维房产管理对象间的多细节层次关系进行一体化表达,特别是实现了对建筑物内部的房产空间关系表达,有利于明晰内部空间(户)的产权划分及各房产对象间的产权关联,为建立产权明晰与室内外综合管理的真3维房产应用提供了理论依据。     

Measurement of similarity for spatial directions between areal objects

Similarity for spatial directions plays an important role in GIS. In this paper, the conventional approaches are analyzed. Based on raster data areal objects, the authors propose two new methods for measuring similarity among spatial directions. One is to measure the similarity among spatial directions based on the features of raster data and the changes of distances between spatial objects, the other is to measure the similarity among spatial directions according to the variation of each raster cell centroid angle. The two methods overcome the complexity of measuring similarity among spatial directions with direction matrix model and solve the limitation of small changes in direction. The two methods are simple and have broader applicability.     

Consistency among parts and aggregates: A computational model

Heterogeneous geographic databases contain multiple views of the same geographic objects at different levels of spatial resolution. When users perceive geographic objects as one spatial unit, although they are physically separated into multiple parts, appropriate methods are needed to assess the consistency among the aggregate and the parts. The critical aspect is that the overall spatial relationships with respect to other geographic objects must be preserved throughout the aggregation process. We developed a systematic model for the constraints that must hold with respect to other spatial objects when two parts of an object are aggregated. We found three sets of configurations that require increasingly more information in order to make a precise statement about their consistency: (1) configurations that are satisfied by the topological relations between the two parts and the object of interest; (2) configurations that need further information about the topological relation between the object of concern and the connector in order to be resolved unambiguously; and (3) configurations that require additional information about the topological relation between the aggregate's boundary and the boundary or interior of the object of interest to be uniquely described. The formalism extends immediately to relations between two regions with disconnected parts as well as to relations between a region and an arbitrary number of separations.     

2维矢量地图空间目标关系的组合式表达

矢量模式的地图平面空间目标是地图数据处理中常见的,其空间关系的描述与处理非常重要本文首先分析了平面地图上的尺度空间和拓扑空间的统一,以及点和直线段两两相互间的基本空间关系,并以这些基本窨绵组合为基础,试图利用组合式方法区分和描述地图空间点状、线状和面状空间目标两两相互间的空间关系,且得到各类空间关系的种数。     

基于空间语义角色的自然语言空间概念提取

根据空间信息的特点,从定义的空间语义角色入手,通过语义角色标注、短语识别以及概念模式匹配等手段,具体分析了自然语言中的空间实体、实体间空间关系以及空间过程的表达与提取方法。     

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.     

面向对象的遥感影像模糊分类方法研究

传统的基于像素的遥感影像处理方法都是基于遥感影像光谱信息极其丰富,地物间光谱差异较为明显的基础上进行的。对于只含有较少波段的高分辨率遥感影像,传统的分类方法,就会造成分类精度降低,空间数据的大量冗余,并且其分类结果常常是椒盐图像,不利于进行空间分析。本文采用面向对象的影像分类方法,考虑了对象的不同特征值,例如光谱值,形状和纹理,结合上下文关系和语义的信息,这种分类技术不仅能够使用影像属性,而且能够利用不同影像对象之间的空间关系。在对诸多对象进行分类后,再进行精度分析。在此研究提出了一种面向对象的方法结合模糊理论把许多的对象块分成不同的类别。这一过程主要有两个步骤：第一个步骤是分割。图像分割将整个图像分割成若干个对象,在这个过程中,分割尺度的选择会影响到后续的分类结果和精度。第二个步骤是分类。在这个步骤中,特征值的选择和隶属度函数的选择都对分类结果有着至关重要的影响。     

空间自相关支撑下的地类分布模式一致性评价

空间分布模式是否保持一致是土地利用数据综合质量评价的一项重要内容。针对当前的研究缺少量化分析和位置表达的现状,提出了一种新的空间数据特有的自相关性评价方法。首先利用语义距离建立空间权重矩阵,随后通过莫兰指数（Moran’s I）计算数据处理前后全局和局部自相关度,最后利用莫兰（Moran）散点图和空间关联的局部指标（local indicators of spatial association,LISA）集聚图相结合的方法对综合前后的土地利用分布模式进行可视化对比。相较传统评价方法,所提方法顾及数据语义关系,计算可量化聚集程度,以直观可视化方法对比展示,更好地对土地利用数据在综合前后的全局空间分布模式一致性进行了评价。认知实验结果符合人类认知,表明所提方法切实有效。