面状居民地匹配骨架线傅里叶变化方法

大比例尺城市居民地是变化最为活跃的要素之一,因其形态复杂多样,数据量密集,匹配过程复杂,成为空间数据匹配的重点。面状居民地匹配骨架线傅里叶变化方法首先把大比例尺面状居民地转化为能够反映其主要轮廓特征的骨架线;其次,把骨架线转化为更易于表达其形态特征的几何形态数据,并对其进行插值计算;第三,对几何形态数据采用傅里叶变换,获取匹配双方骨架线之间的相关系数;最后,通过相关系数来判断双方骨架线之间是否满足匹配条件,从而得到骨架线所对应居民地的匹配结果。通过等级化处理,把2维面状居民地转化为1维骨架线,有效降低了空间数据的复杂性,并可把许多线要素匹配的方法引入进来;把骨架线转化为几何形态数据,并采用傅里叶变换进行形态计算,线要素的几何形态相似性分析得到显著增强,提高了数据匹配的准确率。通过试验验证及对比分析,证明了本方法的有效性和科学性。     

基于力图投影的面状居民地匹配方法

作为空间数据库更新与数据融合的关键内容之一,空间数据匹配越来越受到重视。城市居民地是空间数据变化最为活跃的要素之一,成为空间数据库更新的主要内容。不同于已有面状居民地的匹配方法,根据力与多边形之间的作用关系,提出了基于力图投影的面状居民地匹配方法,即通过居民地对应力图投影来实现对面状居民地的相似性度量,从而达到面状居民地之间匹配的目的。并通过试验验证该方法的可行性和准确性。     

利用骨架线端点匹配进行面状要素渐变变换

面向空间数据连续地图综合问题,提出了一种基于骨架线端点匹配的面状要素渐变方法,通过在两个关键表达之间进行尺度内插,实时、动态地派生任意中间比例尺地图数据。首先,对面状要素在大小比例尺下的两重表达分别进行约束Delaunay三角网剖分并提取各自的骨架线特征;然后,使用最优子序双射优化技术对骨架端点进行匹配获得多边形边界上相对应的特征点序列;最后,在剖分边界的基础上进行分段常规线性内插,获得面状要素介于始末尺度之间的多尺度表达。实验结果表明,该算法充分顾及了空间数据弯曲结构特征,对于光滑边界面状要素的渐变变换具有良好的渐变效果,可用于空间数据的连续地图综合和多尺度表达。     

同名边界点的面状居民地要素匹配

针对空间数据集成与地图增量更新过程中的面实体匹配环节,该文提出利用同名边界点集进行面状居民地要素匹配的方法。该方法从边界点的相似性考虑面状居民地要素的相似性,通过计算候选匹配要素上边界点在位置、转角、关联边等方面的一致性,把面实体相似性的比较转换为同名要素边界点集相似性的比较,简化了面状居民地实体匹配的复杂度。在面状居民地要素的匹配过程中,该文方法可以处理一对一、一对多和多对一的匹配关系。实验证明,该方法在匹配面状居民地要素时,准确率可以达到98%。     

同名边界点的面状居民地要素匹配

针对空间数据集成与地图增量更新过程中的面实体匹配环节,该文提出利用同名边界点集进行面状居民地要素匹配的方法。该方法从边界点的相似性考虑面状居民地要素的相似性,通过计算候选匹配要素上边界点在位置、转角、关联边等方面的一致性,把面实体相似性的比较转换为同名要素边界点集相似性的比较,简化了面状居民地实体匹配的复杂度。在面状居民地要素的匹配过程中,该文方法可以处理一对一、多对一和一对多的匹配关系。实验证明,该方法在匹配面状居民地要素时,准确率可以达到98%。     

同名边界点的面状居民地要素匹配

针对空间数据集成与地图增量更新过程中的面实体匹配环节,该文提出利用同名边界点集进行面状居民地要素匹配的方法。该方法从边界点的相似性考虑面状居民地要素的相似性,通过计算候选匹配要素上边界点在位置、转角、关联边等方面的一致性,把面实体相似性的比较转换为同名要素边界点集相似性的比较,简化了面状居民地实体匹配的复杂度。在面状居民地要素的匹配过程中,该文方法可以处理一对一、多对一和一对多的匹配关系。实验证明,该方法在匹配面状居民地要素时,准确率可以达到98%。     

同名边界点的面状居民地要素匹配

针对空间数据集成与地图增量更新过程中的面实体匹配环节,该文提出利用同名边界点集进行面状居民地要素匹配的方法。该方法从边界点的相似性考虑面状居民地要素的相似性,通过计算候选匹配要素上边界点在位置、转角、关联边等方面的一致性,把面实体相似性的比较转换为同名要素边界点集相似性的比较,简化了面状居民地实体匹配的复杂度。在面状居民地要素的匹配过程中,该文方法可以处理一对一、多对一和一对多的匹配关系。实验证明,该方法在匹配面状居民地要素时,准确率可以达到98%。     

利用空白区域骨架线网眼匹配多源面状居民地

多源大比例尺城市地图中,同名居民地数据间往往存在较大几何位置偏差,从而增加了居民地匹配的难度和不确定性。针对这一问题,本文提出了一种利用空白区域骨架线网眼进行居民地匹配的新方法。首先,提取空白区域骨架线,并建立空白区域骨架线网眼和居民地之间的一一映射关系,将居民地匹配转换为骨架线网眼匹配;然后,根据骨架线网眼之间的相接拓扑关系构建对偶图,计算对偶图中每个节点的各项中心性指标,并利用极化变换和层次分析法建立骨架线网眼匹配模型,获取骨架线网眼匹配结果;最后,将骨架线网眼匹配结果按照映射关系进行传递,从而得到居民地匹配结果。将居民地匹配转换为空白区域骨架线网眼匹配,并对骨架线网眼进行对偶图构建和极化变换,为匹配增加拓扑约束和相对位置约束,从而弥补几何位置的较大偏差对匹配造成的影响。对比试验及分析表明本方法能够有效解决大比例尺城市地图中几何位置偏差较大的面状居民地的匹配问题。     

中误差和邻近关系的多尺度面实体匹配算法研究

地图目标匹配作为空间数据整合和更新的一个不可缺少的过程,有重要的研究意义。中误差是一种衡量地图精度和质量的数值指标,其范围作为制图和综合的重要的标准之一,常用其大小评价空间数据的质量,不同比例尺或来源的地图数据均有不同的中误差大小和阈值。面状要素在很多地图中占有很大的比例,本文将中误差引入面实体匹配的过程,结合相邻面实体邻近聚集算法,提出一种基于中误差和邻近关系的面实体匹配算法,可以有效解决多尺度空间数据匹配的阈值大小和多对多关系难确定的问题,实验结果表明该方法具有良好的稳定性和可靠性。     

利用城市骨架线网的道路和居民地联动匹配方法

同名道路或者居民地数据间由于数据一致性程度不高,往往存在较大的几何位置偏差,当对道路或者居民地单独进行匹配时,不利于提高匹配正确率和效率。针对这一问题,本文提出了一种利用城市骨架线网的道路和居民地联动匹配方法。联动匹配即模仿人在读图时通过特征地物和空间关联寻找目标地物的思维过程,将匹配看作是一种特征目标寻找、信息关联传递的推理过程。首先,利用约束Delaunay三角网对地图构建城市骨架线网。然后,通过道路、骨架线、骨架线网眼和居民地之间的拓扑关系建立道路和居民地之间的匹配传递模型。最后,根据该传递模型实现通过道路匹配带动居民地匹配或者通过居民地匹配带动道路匹配的联动匹配。该方法优势在于只要有一种要素的数据一致性比较好,就能带动另一种要素取得很好的匹配效果,同时符合人类进行匹配时的认知过程。     

Extracting invariant characteristics of sketch maps: Towards place query‐by‐sketch

In geography, invariant aspects of sketches are essential to study because they reflect the human perception of real‐world places. A person's perception of a place can be expressed in sketches. In this article, we quantitatively and qualitatively analyzed the characteristics of single objects and characteristics among objects in sketches and the real world to find reliable invariants that can be used to establish references/correspondences between sketch and world in a matching process. These characteristics include category, shape, name, and relative size of each object. Moreover, quantity and spatial relationships—such as topological, ordering, and location relationships—among all objects are also analyzed to assess consistency between sketched and actual places. The approach presented in this study extracts the reliable invariants for query‐by‐sketch and prioritizes their relevance for a sketch‐map matching process.     

基于几何元素的三维景观实体建模研究

在分析已有国内外研究成果的基础上 ,提出了基于几何元素的 3DCM空间数据模型。实验证明 ,该模型能较精确地表达 3DCM中各类景观实体及其空间关系。     

一种应用三角形划分的空间对象形状匹配方法

为解决现有空间对象形状相似性匹配准确率较低的问题,提出一种应用三角形划分的形状相似性匹配方法。该方法按形状主方向对面状空间对象进行分割,按串联、并联和组合形式对空间对象进行三角形划分,准确描述面状空间对象的形状特征,度量空间对象间的形状相似性。通过形状数据集匹配、不同年份面状水系图层匹配和矢量地图草图检索,测试本方法的形状检索性能,并和其他空间对象形状匹配方法进行对比。实验结果表明,本方法具有更高的形状检索准确率。三角形划分形状匹配方法具有平移、旋转、尺度不变性和较强的形状描述识别能力。     

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.     

Data matching of building polygons at multiple map scales improved by contextual information and relaxation

The aim of matching spatial data at different map scales is to find corresponding objects at different levels of detail (LODs) that represent the same real-world phenomena. This is a prerequisite for integrating, evaluating and updating spatial data collected and maintained at various scales. However, matching spatial data is not straightforward due to the ambiguities caused by problems like many-to-many correspondence, non-systematic displacement and different LODs between data sets. This paper proposes an approach to matching areal objects (e.g. buildings) based on relaxation labeling techniques widely applied in pattern recognition and computer vision. The underlying idea is to utilize contextual information (quantified by compatibility coefficient) in an iterative process, where the ambiguities are reduced until a consistent matching is achieved. This paper describes (1) a domain-specific extension to previous relaxation schemes and (2) a new compatibility coefficient that exploits relative relationships between areal object pairs in spatial data. Our approach were validated through extensive experiments using building data sets at 1:10k and 1:50k as an example. Our contextual approach showed superior performance against a non-contextual approach in general and especially in ambiguous situations. The proposed approach can also be applied to matching other areal features and/or for a different scale range.     

基于约束Delaunay结构的街道中轴线提取及网络模型建立

从街区多边形提街道中轴线并在此基础上建立街道网络模型是城市空间分析及街区地图综合的基础问题,本文基于约束Ｄｅｌａｕｎａｙ三角网结构提出了在邻近街区边界之间的三角形元上提取中轴线从而建立街道网络图模型的方法,区分三种不同三角形元进行中轴线的连接,通过网络图的顶点、边完备地表达出街道、街区、街道交叉口之间的空间关系,并建立了街道中轴线与左右两侧街区多边形边界弧段间的匹配,从而使本文提出的混合数据模型将街道网络结构与街区多边形结构统一起来。     

顾及拓扑关系的立体影像直线特征可靠匹配算法

针对单直线匹配过程中缺乏考虑邻近直线特征之间关系,纹理断裂处单一直线描述符的弱可靠性,提出了一种顾及拓扑关系的立体影像直线特征可靠匹配算法。该算法首先根据直线间距离、角度等基本拓扑关系对参考影像、搜索影像上提取的直线进行编组;然后将编组得到的直线组作为匹配基元,充分利用直线特征组内的拓扑关系,依次采用核线约束、单应矩阵约束、象限约束、不规则三角形区域灰度相关约束对其进行匹配;最后将同名直线组分裂为两对同名单直线、并对分裂后的结果进行整合、拟合、检核等后处理,得到"一对一"的同名直线。选取典型纹理特征的航空影像和近景影像进行参数分析及直线匹配试验,结果表明,本文算法能获取可靠的直线匹配结果。     

Using Topological Relationships to Inform a Data Integration Process

When spatial datasets are overlaid, corresponding features do not always coincide. This may be a result of the datasets having differing quality characteristics, being captured at different scales or perhaps being in different projections or datums. Data integration methods have been developed to bring such datasets into alignment. Although these methods attempt to maintain topological relationships within each dataset, spatial relationships between features in different datasets are generally not considered. The preservation of inter‐dataset topology is a research area of considerable current interest. This research addresses the preservation of topology within a data integration process. It describes the functional models established to represent a number of spatial relationships as observation equations. These are used to provide additional information concerning the relative positions of features. Since many topological relationships are best modelled as inequalities, an algorithm is developed to accommodate such relationships. The method, based on least squares with inequalities (LSI), is tested on simulated and real datasets. Results are presented to illustrate the optimal positioning solutions determined using all of the available information. In addition, updated quality parameters are provided at the level of the individual coordinate, enabling communication of local variation in the resultant quality of the integrated datasets.     

Assessing Data Completeness of VGI through an Automated Matching Procedure for Linear Data

New, free and fast growing spatial data sources have appeared online, based on Volunteered Geographic Information (VGI). OpenStreetMap (OSM) is one of the most representative projects of this trend. Its increasing popularity and density makes the study of its data quality an imperative. A common approach is to compare OSM with a reference dataset. In such cases, data matching is necessary for the comparison to be meaningful, and is usually performed manually at the data preparation stage. This article proposes an automated feature‐based matching method specifically designed for VGI, based on a multi‐stage approach that combines geometric and attribute constraints. It is applied to the OSM dataset using the official data from Ordnance Survey as the reference dataset. The results are then used to evaluate data completeness of OSM in several case studies in the UK.