面向特征的网络空间点群要素自动综合方法

网络空间信息可视化对揭示网络空域规律、促进网络空间认知具有重要意义。将网络空间节点与拓扑关系直接可视化的视图中存在大量的点重合和线交叉,目前已有的网络节点布局算法、集束边技术、骨干网提取和网络路由拓扑多尺度表达等方法能够优化视图效果,但在网络的微观结构上,对保持网络空间点群要素的特征信息关注不够。通过分析并量化网络空间点群要素的各类特征信息,提出了一种基于层次聚类的要素聚合方法和一种基于节点重要性度量的要素选取方法,以自动综合的方式对网络空间点群要素进行综合。实验结果表明,该方法能够保持网络空间点群要素的空间特征,为定量表达网络空间特征、加速生成视觉效果良好的网络空间地图提供基础数据综合方法。     

Linear feature conflation: An optimization-based matching model with connectivity constraints

Geospatial data conflation is the process of combining multiple datasets about a geographic phenomenon to produce a single, richer dataset. It has received increased research attention due to its many applications in map making, transportation, planning, and temporal geospatial analyses, among many others. One approach to conflation, attempted from the outset in the literature, is the use of optimization-based conflation methods. Conflation is treated as a natural optimization problem of minimizing the total number of discrepancies while finding corresponding features from two datasets. Optimization-based conflation has several advantages over traditional methods including conciseness, being able to find an optimal solution, and ease of implementation. However, current optimization-based conflation methods are also limited. A main shortcoming with current optimized conflation models (and other traditional methods as well) is that they are often too weak and cannot utilize the spatial context in each dataset while matching corresponding features. In particular, current optimal conflation models match a feature to targets independently from other features and therefore treat each GIS dataset as a collection of unrelated elements, reminiscent of the spaghetti GIS data model. Important contextual information such as the connectivity between adjacent elements (such as roads) is neglected during the matching. Consequently, such models may produce topologically inconsistent results. In this article, we address this issue by introducing new optimization-based conflation models with structural constraints to preserve the connectivity and contiguity relation among features. The model is implemented using integer linear programming and compared with traditional spaghetti-style models on multiple test datasets. Experimental results show that the new element connectivity (ec-bimatching) model reduces false matches and consistently outperforms traditional models.     

潜在连接点集下拓扑推进三维建模算法研究

通过三维激光扫描仪可以获取到表示空间对象的点云数据。通过设置仪器的采样间隔可以获取到表示对象不同精密程度的点集。但是由于离散点之间缺乏相应的拓扑关系,限制了以点为基本图元的模型的应用。以空间离散特征点集为研究对象,研究了一种三维建模算法。算法基于距离较近的点之间比距离较远的点之间存在拓扑连接的可能性更大的前提,对点集进行预处理,然后在此基础上进行快速建模,最终获取到以三角形为基本面片的格网模型。所建立的模型易于进行各项空间分析和操作。该算法也能够有效地应用于更为复杂的建模任务中,以达到一体化建模的目的。     

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.     

面向拓扑的地理空间数据模型

本文在分析了目前常见空间数据模型的基础上,提出了一种面向拓扑的地理空间数据数据模型.该模型将实体的几何信息和拓扑信息紧密联系在一起,具有较强的空间表现力,能支持GIS数据和制图数据的一体化生产,并能够实现空间数据的几何、属性和拓扑关系一致性的实时维护.实践表明,该模型能有效地提高空间数据生产的质量和效率.     

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.     

时空拓扑关系的集成表达

针对地理实体之间的时空拓扑关系,阐述了当前被普遍接受的空间和时态拓扑关系模型、基于点集和逻辑谓词集的描述方法。基于8种时态和空间拓扑关系逻辑谓词,提出时空数据库中时空拓扑关系集成表达(或称联合表达)的64种情况,分别利用英文缩写字母和关系图2种形式对其进行了描述。最后,通过示例的应用说明时空拓扑关系集成表达的具体情形。     

空间体对象间三维拓扑构建研究

根据三维拓扑的研究现状以及特定应用领域对三维拓扑的需求,分析了这些特定应用领域的拓扑关系,提出了两种三维拓扑构建方法。这两种方法在兼顾内拓扑的同时主要构建体之间的外拓扑关系。第一种方法是在体单独构建完毕后建立体之间的拓扑关系;第二种方法考虑到当前成熟三维建模软件或CAD软件中的数据大多以离散面方式组织,设计了自动寻体算法,同时构建体之间的外拓扑关系。利用深圳典型地籍数据和建筑设计图生成的三维数据进行实验,验证了此算法的可行性。     

A Space-Time GIS Approach to Exploring Large Individual-based Spatiotemporal Datasets

The increasing number of large individual-based spatiotemporal datasets in various research fields has challenged the GIS community to develop analysis tools that can efficiently help researchers explore the datasets in order to uncover useful information. Rooted in Hägerstrand's time geography, this study presents a generalized space-time path (GSTP) approach to facilitating visualization and exploration of spatiotemporal changes among individuals in a large dataset. The fundamental idea of this approach is to derive a small number of representative space-time paths (i.e. GSTPs) from the raw dataset by identifying spatial cluster centers of observed individuals at different time periods and connecting them according to their temporal sequence. A space-time GIS environment is developed to implement the GSTP concept. Different methods of handling temporal data aggregation and the creation of GSTPs are discussed in this article. Using a large individual-based migration history dataset, this study successfully develops an operational space-time GIS prototype in ESRI's ArcScene and ArcMap to provide a proof-of-concept study of this approach. This space-time GIS system demonstrates that the proposed GSTP approach can provide a useful exploratory analysis and geovisualization environment to help researchers effectively search for hidden patterns and trends in such datasets.     

一种空间交叉异常显著性判别的非参数检验方法

空间异常探测旨在从海量空间数据中挖掘不符合普适性规律、表现出“与众不同”特性的空间实体集合,对于揭示地理现象的特殊发展规律具有重要价值。现有研究在空间异常度量方面取得了重要进展,但多缺乏对空间异常模式显著性的统计判别,且是针对单一类别数据,没有顾及多类别数据间的相互影响。为此,本文基于空间随机过程的思想,针对两种类别空间点数据,提出了一种空间交叉异常显著性判别的非参数检验方法。首先,针对基本数据集实体,采用约束Delaunay三角网,构建合理、稳定的空间邻近域;然后,统计落在基本数据集实体空间参考邻域半径范围内的参考数据集实体的数目,度量初始异常度;进而,采用α-Shape法构建支撑域,以空间随机过程为基础构建零模型,采用蒙特卡洛模拟检验空间异常的显著性;最后,采用生存距离对异常模式的稳定性进行评价分析。通过试验分析与比较发现,该方法能够有效识别具有统计显著性的空间交叉异常。     

基于交通网络几何和语义(交通)规则集成的公交换乘研究

换乘信息特别是基于地理信息系统技术的图文换乘信息服务,已经成为城市公共交通信息服务、线网规划和线路优化调整的重要指标与内容。但是公共交通线网具有特殊的网络特征和拓扑关系,它不同于城市道路网络,因此公共交通换乘不能简单应用于目前的最优路径算法,例如Dijkstra算法。本文将通过对公共交通线网的空间特征和语义(交通)规则分析,建立城市交通网络的几何和语义连通性的集成关系。几何连通性是语义连通性的基础和先决条件,而语义连通性是公共交通网络拓扑的核心。基于语义连通性的公共交通线网拓扑关系提升公共交通换乘算法的效率和信息准确度,任何两个站点之间的最优路径可以被迅速获取而不需要检索整个网络的几何拓扑信息。并且该最优换乘路径考虑到最少换乘次数、出行距离最短、费用最少、途经站点最少和换乘中最短步行距离等多目标换乘。     

Assessing reference dataset representativeness through confidence metrics based on information density

Land cover maps obtained from classification of remotely sensed imagery provide valuable information in numerous environmental monitoring and modeling tasks. However, many uncertainties and errors can directly or indirectly affect the quality of derived maps. This work focuses on one key aspect of the supervised classification process of remotely sensed imagery: the quality of the reference dataset used to develop a classifier. More specifically, the representative power of the reference dataset is assessed by contrasting it with the full dataset (e.g. entire image) needing classification. Our method is applicable in several ways: training or testing datasets (extracted from the reference dataset) can be compared with the full dataset. The proposed method moves beyond spatial sampling schemes (e.g. grid, cluster) and operates in the multidimensional feature space (e.g. spectral bands) and uses spatial statistics to compare information density of data to be classified with data used in the reference process. The working hypothesis is that higher information density, not in general but with respect to the entire classified image, expresses higher confidence in obtained results. Presented experiments establish a close link between confidence metrics and classification accuracy for a variety of image classifiers namely maximum likelihood, decision tree, Backpropagation Neural Network and Support Vector Machine. A sensitivity analysis demonstrates that spatially-continuous reference datasets (e.g. a square window) have the potential to provide similar classification confidence as typically-used spatially-random datasets. This is an important finding considering the higher acquisition costs for randomly distributed datasets. Furthermore, the method produces confidence maps that allow spatially-explicit comparison of confidence metrics within a given image for identification of over- and under-represented image portions. The current method is presented for individual image classification but, with sufficient evaluation from the remote sensing community it has the potential to become a standard for reference dataset reporting and thus allowing users to assess representativeness of reference datasets in a consistent manner across different classification tasks.     

拓扑和方向空间关系组合描述及其相互约束

提出了一种拓扑关系和方向关系组合描述框架,在统一的框架下研究拓扑和方向关系。采用9交模型描述拓扑关系,方向关系矩阵模型表达方向关系,并给出了有意义的方向片组合,将两者统一到一个框架下进行描述。在统一描述框架下,拓扑关系与方向关系相互约束。阐述了7个定理及其证明,描述了拓扑关系与方向关系之间的相互约束,实现拓扑关系和方向关系有效性的相互检测。拓扑关系和方向关系组合描述能够提高空间关系描述的准确性和有效性。     

一种基于Fréchet距离的复杂线状要素匹配方法

在不同空间数据集中,同名实体往往有不同的空间表现形式,识别多源异构数据集中的同名实体是空间数据集成和应用的关键。集成不同来源的空间数据是提高GIS数据质量的重要方法,识别同名实体是数据集成和分析的先决条件。根据线要素的形状将其分为简单线要素和复杂线要素,针对现有复杂线要素匹配方法中的不足,提出了Fréchet距离的复杂线状要素匹配方法。该方法首先通过曲线要素的几何和拓扑特性获取候选匹配集,然后结合基于Fréchet距离和要素简化方法实现要素的简化。最后提出基于Fréchet距离的要素匹配改进方法,通过引入简化要素的三元组信息来存储简化后的复杂线要素的属性信息,再根据三元组信息选取要素间的匹配对,完成对不同类型匹配对的检测,实现复杂线状要素匹配。试验结果表明,该匹配方法能有效解决复杂线要素的匹配问题,并能够识别1:0、1:N和M:N匹配。     

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.     

空间线群目标相似度计算模型研究

以空间线群目标的空间统计特征为基础,对线群目标的空间关系和几何特征进行了描述。利用拓扑关系概念邻域图定义线群之间的拓扑关系相似度,利用方向均值定义线群之间的方向关系相似度以及利用"环形方差"定义线群目标之间的距离相似度。结合线群的长度和平均长度、线群密度及线群曲折度,建立了线群目标相似度计算模型,对线群目标相似度进行了整体度量。实验结果表明,相似度计算结果与地物特征比较一致,符合人们的直观认知。     

Implementation of novel polygon-based obfuscation methods to improve privacy of agricultural data

Geoprivacy protection is a significant concern when sharing data. To support sustainable land management by leveraging existing agricultural data, research is needed to identify how the polygon nature of static field parcels can be obfuscated to allow data sharing among individuals and organizations. In this study, five adaptive polygon-based obfuscation methods including PN*Rand, PDonut-k, PDensity-k, PAHilb, and PDonut_AHilb methods were developed and applied on the Irish Nutrient Management Planning Online (NMP Online) agricultural dataset. The polygon-based obfuscation methods introduced in this study were designed with the consideration of properties of spatial polygon objects including the spatial coordinates, shape and size of the polygon, topology, and spatial relationship between adjacent polygons that can be used to identify real-world objects. These methods were developed to guarantee that there is no false-identification and non-unique obfuscation which is important for static polygon objects in terms of accuracy and privacy protection. Qualitative approaches were developed to identify the optimal values of inner and outer radii of donut shape based on k-anonymity satisfaction and subsequently obtain the optimal value of k-anonymity. Several evaluation methods were implemented to compare the methods performance. Density-based methods particularly PDonut-AHilb provide the best trade-off between field parcel confidentiality and spatial pattern preservation and should be considered for researchers and practitioners obfuscating polygon data.     

Developments in digital map production and data integration within the British Geological Survey

Abstract

Digital techniques for cartographic data capture and high quality map production have been developed and applied over some 18 years to the mapping of the geoscientific datasets of the British Geological Survey, in particular to the geochemical dataset. Over this period, technological advances and developments in both vector and raster data processing techniques have facilitated high quality map production and the integration and display of multiple datasets. This paper reviews the developments in high quality map production and interpretation of survey information, with particular regard to the Regional Geochemical Atlas Series, through the application of image processing techniques on the display and analysis of multiple datasets.     

多尺度等高线簇拓扑关系定量表达方法研究

等高线拓扑关系定量表达对空间认知、地形特征挖掘、地图综合等至关重要。然而,已有研究多针对等高线树的生成及综合算法,缺乏等高线拓扑关系及其与尺度变化关系的定量表达,不同地貌类型其变化规律是否一致仍未知。为此,通过分带与投影转换、非闭合等高线拓扑检查与闭合及有向等高线树的构建等,发展了一种等高线拓扑关系定量表达方法。采用高山、中山、平原地貌60组多尺度等高线数据集,探究不同地貌类型的多尺度等高线拓扑指标及其随尺度变化规律的一致性。试验结果表明,相邻尺度等高线拓扑指标变化规律符合空间认知与推理,不同地貌类型多尺度等高线拓扑指标与尺度变化间关系可用同一个幂函数定量表达,该结论为基于多尺度空间相似关系等高线全自动综合的实现提供了理论支撑。     

Geographical Linked Data: The Administrative Geography of Great Britain on the Semantic Web

Ordnance Survey, the national mapping agency of Great Britain, is investigating how semantic web technologies assist its role as a geographical information provider. A major part of this work involves the development of prototype products and datasets in RDF. This article discusses the production of an example dataset for the administrative geography of Great Britain, demonstrating the advantages of explicitly encoding topological relations between geographic entities over traditional spatial queries. We also outline how these data can be linked to other datasets on the web of linked data and some of the challenges that this raises.