Sketch maps for searching in spatial data

Much research has been conducted on the use of sketch maps to search in spatial databases, nevertheless, they have faced challenges, such as modeling of the data abstraction level, aggregated features in sketches, modeling of semantic aspects of data, data redundancy, and evaluation of the results. Considering these challenges, in this article a new solution is presented for searching in databases based on data matching. The main difference between this solution and the other approaches lies in the parameters introduced to match data and how to solve the matching problem. Using geometrical, topological, and semantic parameters in the matching, as well as performing the matching process in the two phases of partial and global, has resulted in an of about 78%. The evaluation process is performed based on the matching parameters and the matching procedure; finally, the result is acceptable compared to previous implementations.     

Robust abnormality detection methods for spatial search of radioactive materials

Radiological dirty bombs and improvised nuclear devices pose a significant threat to both public health and national security. Growing networks of radiation sensors have been deployed by a number of offices within the U.S. and international agencies. Detecting such threats while minimizing false alarm rates presents a considerable challenge to homeland security and public health. This research aims to achieve a higher probability of detection with a lower probability of false alarms. It focuses on the local spatial instability of radiation levels in order to detect radioactive materials based on robust outlier detection methods. Our approach includes a three‐step abnormality detection method consisting of one‐dimensional robust outlier detection for all gamma‐ray counts, a density‐based clustering analysis, and a two‐dimensional robust outlier detection method using a bagplot, based on spatial associations. The effectiveness of the method proposed is demonstrated through a case study, wherein radioactive materials are detected in urban environments, and its performance is compared with alternative methods employing a k‐sigma approach, local Getis–Ord () statistic, and the goodness of fit of the Poisson distribution.     

Geometric Algebra Model for Geometry‐oriented Topological Relation Computation

Classical topological relation expressions and computations are primarily based on abstract algebra. In this article, the representation and computation of geometry‐oriented topological relations (GOTR) are developed. GOTR is the integration of geometry and topology. The geometries are represented by blades, which contain both algebraic expressions and construction structures of the geometries in the conformal geometric algebra space. With the meet, inner, and outer products, two topology operators, the MeetOp and BoundOp operators, are developed to reveal the disjoint/intersection and inside/on‐surface/outside relations, respectively. A theoretical framework is then formulated to compute the topological relations between any pair of elementary geometries using the two operators. A multidimensional, unified and geometry‐oriented algorithm is developed to compute topological relations between geometries. With this framework, the internal results of the topological relations computation are geometries. The topological relations can be illustrated with clear geometric meanings; at the same time, it can also be modified and updated parametrically. Case studies evaluating the topological relations between 3D objects are performed. The result suggests that our model can express and compute the topological relations between objects in a symbolic and geometry‐oriented way. The method can also support topological relation series computation between objects with location or shape changes.     

Contour line simplification method based on the two‐level Bellman–Ford algorithm

The contour line is one of the basic elements of a topographic map. Existing contour line simplification methods are generally applied to maps without topological errors. However, contour lines acquired from a digital elevation model (DEM) may contain topological errors before simplification. Targeted at contour lines with topological errors, a progressive simplification method based on the two‐level Bellman–Ford algorithm is proposed in this study. Simplified contour lines and elevation error bands were extracted from the DEM. The contour lines of the elevation error bands were initially simplified with the Bellman–Ford (BF) algorithm. The contour lines were then segmented using the vertices of the initial simplification result and connected curves with the same bending direction were merged into a new curve. Subsequently, various directed graphs of the merged curves were constructed and a second simplification was made using the BF algorithm. Finally, the simplification result was selected based on the similarity between several simplification results and adjacent contour lines. The experimental results indicate that the main shapes of the contour groups can be maintained with this method and original topological errors are resolved.     

Stroke特征约束的树状河系层次关系构建及简化方法

树状河系作为地图骨干要素之一,其简化效果直接决定地图综合的质量。树状河系简化需要考虑其语义、几何、拓扑和结构等多种特征,而现有方法大多只注重了长度、角度和属性等约束性量化指标,致使简化后的空间分布特征容易被破坏。本文首先研究基于树状河系有向拓扑树（DTT）的特征智能识别方法,然后依据Paiva提出的"180°假设"和"锐角假设",从河口出发,自下游向上游建立顾及河流语义、长度、角度约束的树状河系stroke连接,并据此判断树状河系层次关系,最后提出河系整体选取数量确定方法和顾及密度差异的河系分层剔除选取算法,实现树状河系自动化简化。经样本数据测试,验证了该方法的可靠性,同时经实际数据测试,验证了该方法在树状河系简化中的合理性和有效性。     

Morse理论支持下的建筑物点云特征提取

针对传统特征提取算法的结果存在交叉紊乱、不连续、缺少拓扑关系等问题,本文提出了基于Morse理论的建筑物点云特征提取算法。首先定义三维表面模型上顶点的Morse函数指标;然后采用邻点比较法自动提取特征点;最后针对Morse-Smale复形的对偶性在建筑物拓扑特征中已无实际意义的问题,提出了单复形拓扑模型的提取与简化算法。试验结果表明,该算法能够获得清晰、连续、完整的建筑物特征线,实现对建筑物模型表面的完全分割;简化算法在保证建筑物特征线拓扑一致性的前提下,可以获取不同层次的建筑物拓扑特征,为建筑物模型的重建与可视化提供了保障。     

Reconstructing facade semantic models using hierarchical topological graphs

Semantic information in 3D building models is of vital importance for various applications in terms of smart cities. To infer the semantic information and localize the components on building facades, this article proposes a novel approach to model facades with semantics by constructing hierarchical topological graphs. This method utilizes the topological characteristics of building facades. In the first‐layer layout graph, the algorithm takes the nearest cluster as the vertex and the distance between components as the edge. Thus, a topology graph is generated for the facade. The proposed algorithm is divided into three steps. First, the topology graph is obtained by calculating the spacing between the components. It is reasonable to calculate the topological graph by encoding the topological edges. If this calculation is not effective, the topology is justified by adjusting the spacing between components. Finally, the vertices in the graph are used to repair the occluded parts of the facade. In the second‐layer graph, a grid is constructed according to the first‐layer graph. Then, the attributes of the nodes are used to reconstruct the facade. The experimental results show that this method has a high accuracy of 90% and that the average time consumption is 6 s.     

Stroke构造、移位一体化的道路网示意化方法

针对当前常用示意性地图生成方法中往往存在简化程度不够、未考虑长度信息以及时间效率低等问题,提出了stroke构造、移位一体化的道路网示意化方法。该方法在对道路网进行stroke划分构造的同时,直接对其进行渐进式的移位示意化及拓扑检查。同时本文还提出利用相似分形维数来定量比较并验证不同示意化方法的有效性。试验表明,本算法在考虑原始线形的基础上,示意化过程简单,时间效率较高,减少了拓扑冲突问题,保证了拓扑一致性及路网的均衡分布,具有较好的清晰度和认知度。     

顾及三维形态特征的河流曲线化简方法

鉴于常规曲线化简方法应用于河流曲线化简时难以顾及河流要素的三维特征及其拓扑结构,提出了一种顾及三维形态特征的河流曲线化简方法。该方法利用河流曲线上散点的三维特征对散点进行选取进而实现河流曲线化简。在三维Douglas-Peucker（3D D-P）算法的基础上提出一种三维散点排队法,根据散点的三维特征对河流曲线的离散点集进行排队,并通过初始排队、"3合1"队列合并及约束点位置调整3个过程建立散点队列,然后根据压缩比从队列尾部删除相应比例的点数获得散点综合结果,将综合后的散点按照河流曲线的原始次序重构出化简后的河流曲线。实验结果表明,该方法既能最大程度地保留河流的三维形态特征,又能保证河流曲线之间的拓扑结构一致性。     

利用Snake移位模型构建中心型地图

中心型地图可表示空间各点到中心点的时间距离,能直观反映地理分布因交通系统影响而产生的相近性变化。其构建核心是依据控制点的位置移动确定非控制点的新位置,因此,将中心型地图的构建过程建模为地图目标的移位问题,以相对邻近图表示点之间的邻近关系,并基于控制点的位置移动计算点的初始受力,应用Snake移位方法迭代计算各点的新位置生成中心型地图,同时利用后处理解决潜在拓扑错误。利用所提方法和最小二乘方法可视化武汉市到其他各市的旅行时间,并定量、定性地进行对比分析。结果表明,所提方法能更好地避免拓扑错误,且局部形态保持更好。     

A spatial contextual immune genetic algorithm to building cartographic displacement

In map generalization, displacement is the most frequently used operator to reduce the proximity conflicts caused by reducing scales or other generalization operations. Building displacement can be formalized as a combinatorial optimization problem, and a heuristic or intelligent search algorithm can be borrowed to obtain the solution. In this way, we can explicitly resolve minimum distance conflicts and control positional accuracy during the displacement. However, maintaining spatial relations and patterns of buildings can be challenging. To address spatial conflicts as well as preserve the significant spatial relations and patterns of buildings, we propose a new spatial contextual displacement algorithm based on an immune genetic algorithm. To preserve important spatial relations and global patterns of map objects and avoid topology errors, displacement safety zones are constructed by overlapping the Voronoi tessellation and buffer areas of the buildings. Additionally, a strategy to shift the buildings in a building group synchronously is used to maintain local building patterns. To demonstrate the effectiveness of our algorithm, two data sets with different building densities were tested. The results indicate that the new algorithm has obvious advantages in preventing topology errors and preserving spatial relations and patterns.     

基于圆增长特征的点状要素群选取算法

控制点、独立地物等在地图上呈点群状表达,如何高效、合理地实现此类要素的自动综合是地图多尺度表达的重要问题。文中在前人研究的基础上,提出一种基于圆增长特征的点状要素群结构化选取算法,实现点状要素群的自动选取。其基本原理是：根据一个点与其周围点重要性程度的比较来确定该点删除与否,从而确保其拓扑关系和几何信息的正确性。实验证明：该算法实用、有效。     

曲线弯曲深度层次结构的二叉树表达

地图综合要顾及目标的几何特征、语义特征和拓扑特征，其中地理意义是控制综合算子系统、参量调整的决定性因素。就线状要素而言，单从角度、距离、矢高等几何特征出发设计的曲线化简算法只能算作对曲线坐标串的几何压缩，不是真正意义上的地图综合。由于曲线的弯曲特征在表达线状地物地理特征上具有重要意义，对弯曲特征的识别、结构描述及操作分析成为目前线要素制图综合的研究热点。本文基于约束Delaunay三角网模型提出一种方法描述曲线弯曲特征在深度上的层次结构，对曲线上的矢量点构建三角网，在三角网覆盖区域里，由外向内进行三角形的“剥皮”操作，根据“剥皮”操作，根据“剥皮”进行过程中遇到的特征三角形构建二叉树，实现大弯曲套小弯曲层次结构的表达。该方法基于Gestalt对称性、连续性原则、对二叉树结点进行考察，可提取认知意义上的真正弯曲。本文同时给出了弯曲特征二叉树在多边形（闭合曲线）综合化简中的算法设计及实验结果。     

Cycle graph analysis for 3D roof structure modelling: Concepts and performance

The paper presents a cycle graph analysis approach to the automatic reconstruction of 3D roof models from airborne laser scanner data. The nature of convergences of topological relations of plane adjacencies, allowing for the reconstruction of roof corner geometries with preserved topology, can be derived from cycles in roof topology graphs. The topology between roof adjacencies is defined in terms of ridge-lines and step-edges. In the proposed method, the input point cloud is first segmented and roof topology is derived while extracting roof planes from identified non-terrain segments. Orientation and placement regularities are applied on weakly defined edges using a piecewise regularization approach prior to the reconstruction, which assists in preserving symmetries in building geometry. Roof corners are geometrically modelled using the shortest closed cycles and the outermost cycle derived from roof topology graph in which external target graphs are no longer required. Based on test results, we show that the proposed approach can handle complexities with nearly 90% of the detected roof faces reconstructed correctly. The approach allows complex height jumps and various types of building roofs to be firmly reconstructed without prior knowledge of primitive building types.     

The use of cartographic control points in the harmonization and revision of MRDBs

The main purpose of the research is to achieve fully automated approach for supplying multi-resolution databases with linear objects in each scale. Moreover, the proposed solutions maintain the repeatability and accuracy of output data wherever possible according to the input scale. These properties are achieved by keeping the minimal object dimensions as well as the appropriate data pre-processing, based on the classification of source points. The classification distinguishes three classes of points: constant (unchangeable), temporary, and inherited. These classes build a structure of cartographic control points. Based on these solutions, the authors proposed an algorithm for linear object simplification based on minimal object dimensions and cartographic control points. It was also confirmed that the simplification between constant points does not cause geometry discrepancies in relation to the global simplification of the whole line.     

矢量地图空间信息度量及其变化分析方法

如何计算地图的空间信息含量是评价制图质量、地图综合算法以及实现空间信息有效传输的重要基础。论文在详细分析现有的空间信息度量方法的基础上,提出了一种空间信息度量的新方法。该方法分别从几何、专题、拓扑以及专题拓扑4个方面来度量地图空间信息。然后,提出利用膨胀和序贯膨胀形态学算子分析几何信息熵、专题信息熵、拓扑信息熵以及专题拓扑信息熵随地图符号影响范嗣不同而引起的变化。通过算例分析发现,利用Voronoi图计算得到的结果是论文方法的一个极值结果（即特例）,并且该方法便于定量分析地图空间信息熵度量随符号影响范围（或大小）的变化情况。     

多边形形状简化及其质量评价

在保证多边形之间拓扑关系完整的基础上,分别使用垂距限值法和Douglas-Peucker算法对多边形形状进行了简化,同时从多边形常规参数以及相似度等方面对简化后多边形的质量进行了评价。实验结果表明Douglas-Peucker算法的简化效果较好。     

线图形简化与移位算子的协同方法

在地图综合过程中,线的图形简化和移位算子通常是分别执行的,图形简化和移位有时都会产生新的空间冲突。本文试图把这两种算子进行协同,避免在地图综合过程中进行空间冲突的多次探测,提高地图综合数据处理的效率。本文通过把线图形简化转换为线上的点移位,并构建邻近地图目标之间的移位传播路径,在考虑空间上下文关系和地图感受规则的前提下,使移位过程能考虑到线图形简化,并尽量保持有关地图目标的空间特征。最后,以道路和其周边的建筑物群为例,验证了该算法的有效性和可行性。     

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。