A spatially adaptive decomposition approach for parallel vector data visualization of polylines and polygons

With the wide adoption of big spatial data and the emergence of CyberGIS, the nontrivial computational intensity introduced by massive amount of data poses great challenges to the performance of vector map visualization. The parallel computing technologies provide promising solutions to such problems. Evenly decomposing the visualization task into multiple subtasks is one of the key issues in parallel visualization of vector data. This study focuses on the decomposition of polyline and polygon data for parallel visualization. Two key factors impacting the computational intensity were identified: the number of features and the number of vertices of each feature. The computational intensity transform functions (CITFs) were constructed based on the linear relationships between the factors and the computing time. The computational intensity grid (CIG) can then be constructed using the CITFs to represent the spatial distribution of computational intensity. A noninterlaced continuous space-filling curve is used to group the lattices of CIG into multiple sub-domains such that each sub-domain entails the same amount of computational intensity as others. The experiments demonstrated that the approach proposed in this paper was able to effectively estimate and spatially represent the computational intensity of visualizing polylines and polygons. Compared with the regular domain decomposition methods, the new approach generated much more balanced decomposition of computational intensity for parallel visualization and achieved near-linear speedups, especially when the data is greatly heterogeneously distributed in space.     

矢量空间数据渐进传输研究进展

渐进传输被认为是解决目前海量空间数据传输与实时用户体验之间矛盾的有效方法。栅格数据渐进传输的相关研究比较成熟,但矢量数据的渐进传输理论和技术还存在问题。为了推进矢量数据渐进传输的相关研究,该文对与矢量数据渐进传输密切相关的二维矢量数据、三维表面模型两种数据的多分辨率表达和渐进传输的研究现状进行归纳与总结,指出相关研究的发展方向,为海量空间数据适用于分布式网络传输提供参考依据。     

Curvedness feature constrained map matching for low-frequency probe vehicle data

Map matching method is a fundamental preprocessing technique for massive probe vehicle data. Various transportation applications need map matching methods to provide highly accurate and stable results. However, most current map matching approaches employ elementary geometric or topological measures, which may not be sufficient to encode the characteristic of realistic driving paths, leading to inefficiency and inaccuracy, especially in complex road networks. To address these issues, this article presents a novel map matching method, based on the measure of curvedness of Global Positioning System (GPS) trajectories. The curvature integral, which measures the curvedness feature of GPS trajectories, is considered to be one of the major matching characteristics that constrain pairwise matching between the two adjacent GPS track points. In this article, we propose the definition of the curvature integral in the context of map matching, and develop a novel accurate map matching algorithm based on the curvedness feature. Using real-world probe vehicles data, we show that the curvedness feature (CURF) constrained map matching method outperforms two classical methods for accuracy and stability under complicated road environments.     

Terrain data compression using wavelet-tiled pyramids for online 3D terrain visualization

Last years have witnessed the widespread use of online terrain visualization applications. However, the significant improvements achieved in sensing technologies have allowed an increasing size of the terrain databases. These increasing sizes represent a serious drawback when terrain data must be transmitted and rendered at interactive rates. In this paper, we propose a novel wavelet-tiled pyramid for compressing terrain data that replaces the traditional multiresolution pyramid usually used in wavelet compression schemes. The new wavelet-tiled pyramid modifies the wavelet analysis and synthesis processes, allowing an efficient transmission and reconstruction of terrain data in those applications based on multiresolution tiled pyramids. A comparative performance evaluation with the currently existing techniques shows that the proposed scheme obtains a better compression ratio of the terrain data, reducing the storage space and transmission bandwidth required, and achieving a better visual quality of the virtual terrain reconstructed after data decompression.     

A vector field model to handle the displacement of multiple conflicts in building generalization

In map generalization, the displacement operation attempts to resolve proximity conflicts to guarantee map legibility. Owing to the limited representation space, conflicts may occur between both the same and different features under different contexts. A successful displacement should settle multiple conflicts, suppress the generation of secondary conflicts after moving some objects, and preserve the distribution patterns. The effect of displacement can be understood as a force that pushes related objects away with properties of propagation and distance decay. This study borrows the idea of vector fields from physics discipline and establishes a vector field model to handle the displacement of multiple conflicts in building generalization. A scalar field is first constructed based on a Delaunay triangulation skeleton to partition the buildings being examined (e.g., a street block). Then, we build a vector field to conduct displacement measurements through the detection of conflicts from multiple sources. The direction and magnitude of the displacement force are computed based on an iso-line model of vector field. The experiment shows that this global method can settle multiple conflicts and preserve the spatial relations and important building patterns.     

Ontologies and representation spaces for sketch map interpretation

In this paper, we present a systematic approach to sketch map interpretation. The method decomposes the elements of a sketch map into a hierarchy of categories, from the material sketch map level to the non-material representational sketch map level, and then interprets the sketch map using the five formal representation spaces that we develop. These spaces (set, graph, metric and Euclidean) provide a tiered formal representation based on standard mathematical structures. We take the view that a sketch map bears information about the physical world and systematises this using extensions of existing formal ontologies. The motivation for this work is the partially automatic extraction and integration of information from sketch maps. We propose a set of ontologies and methods as a first step in the direction of a formalisation of partially automatic extraction and integration of sketch map content. We also see this work as a contribution to spatial cognition, where researchers externalise spatial knowledge using sketch mapping. The paper concludes by working through an example that demonstrates the sketch map interpretation at different levels using the underlying method.     

基于GA-SVM封装算法的高光谱数据特征选择

封装型的特征选择算法相对于过滤算法而言更有助于提高分类精度,因此在当前计算技术及效率快速发展的背景下必将成为未来之趋势。本文以支持向量机(SVM)为分类器,遗传算法(GA)为特征子集的搜索算法,构建了封装型的特征选择算法GA-SVM,并用ENVI/IDL语言编程实现,最后以HYPERION高光谱数据为例对算法予以应用。结果表明,GA-SVM算法可从196个波段中选择出13个波段,同时分类精度较不做特征选择时提高了约4%。由此可见,GA-SVM封装型特征选择算法具有较好的同时优化特征子集和SVM核函数的性能,可为当前高光谱数据的特征选择提供一个较好的算法。     

湖南省城镇空间时空压缩特征及其可视化表达——基于时空图分析模型

本文构建了一个基于“时间-空间图(Time-Space Map)”的技术方法模型,用于分析交通网络建设给地理空间带来的时空压缩效应.现有基于可达性评价模型的“空间格局分析法”只能描述网络整体效率变化,而“等时圈分析法”局限于节点分析,两者都无法完整展现区域时空压缩.本文集成了网络大数据抓取技术、统计分析技术和可视化技术,通过绘制“时空图”实现区域时空压缩的可视化.首先,该方法利用网络大数据抓取技术,通过网络地图路径导航服务获取距离数据矩阵;然后,运用多尺度分析方法(Multidimensional Scaling),用通行时间(距离)取代欧氏距离计算求得最佳拟合空间,并对拟合误差进行估算和检验.最后,将拟合空间与地理空间在三维空间中叠加,观察和分析拟合空间的拉伸、延展、扭曲效果,总结区域时空压缩整体特点.在此基础上,以湖南省为案例绘制出了各地县级城市在现状公路网联系下的通行距离和通行时间时空图.研究验证了时空图在区域时空压缩格局可视化上的有效性和直观性,并在解读时空图集聚、偏移和皱起的基础上,提出改善省内公路网络可达性均衡的政策建议.     

Automatic alignment of contemporary vector data and georeferenced historical maps using reinforcement learning

ABSTRACT

With large amounts of digital map archives becoming available, automatically extracting information from scanned historical maps is needed for many domains that require long-term historical geographic data. Convolutional Neural Networks (CNN) are powerful techniques that can be used for extracting locations of geographic features from scanned maps if sufficient representative training data are available. Existing spatial data can provide the approximate locations of corresponding geographic features in historical maps and thus be useful to annotate training data automatically. However, the feature representations, publication date, production scales, and spatial reference systems of contemporary vector data are typically very different from those of historical maps. Hence, such auxiliary data cannot be directly used for annotation of the precise locations of the features of interest in the scanned historical maps. This research introduces an automatic vector-to-raster alignment algorithm based on reinforcement learning to annotate precise locations of geographic features on scanned maps. This paper models the alignment problem using the reinforcement learning framework, which enables informed, efficient searches for matching features without pre-processing steps, such as extracting specific feature signatures (e.g. road intersections). The experimental results show that our algorithm can be applied to various features (roads, water lines, and railroads) and achieve high accuracy.     

矢量数据在多尺度栅格化中的精度损失模型探讨

在进行空间分析时,由于栅格数据便于空间分析,因而通常将矢量数据转化成栅格数据进行空间分析。在转化过程中,采用不同尺度的栅格大小会造成怎样的精度损失?精度损失、栅格大小和平均斑块大小之间的关系是否可以用模型来表达?本文正是针对这样的问题,以重庆市1∶10万的土地利用矢量数据为例,探讨了在不同尺度栅格大小(从30m×30m到1000m×1000m)的情况下,各种土地利用类型在转化过程中的精度损失情况,对精度损失与栅格大小和平均斑块大小之间的关系进行了定量分析。研究表明,精度损失与地类的平均斑块大小和栅格尺度之间的关系可以用模型来表达。该模型为:Y=5.366-0.179X-0.978ln(S)+0.0348Xln(S)。模型中Y为精度损失,S为地类的平均斑块大小,X表示栅格的大小。该模型的复相关系数为0.93。     

基于词向量数据场轨迹引力的多中心识别和空间交互分析

多中心化是分散城市人口,疏解交通拥堵,调节职住失衡,应对"大城市病"的重要手段.针对轨迹大数据,先利用词向量描述其空间特征和行为规律,再结合数据场理论表达城市区域对轨迹的吸引强度,并完成多中心识别,最后借鉴复杂网络理论对多中心空间交互规律进行探索和挖掘.结果表明:①郑州市轨迹吸引强度呈核心强、外围弱、沿线蔓延的圈层空间...     

NDVI changes in China between 1989 and 1999 using change vector analysis based on time series data

1 Introduction The land surface has considerable control on the planet抯 energy balance, biogeochemical cycles and hydrologic cycle, which in turn significantly influences the climate system. Therefore, the global environmental change community has paid great attention to the land use/cover change (LUCC). Many researchers have focused on the land cover classification and change by using remotely sensed data. Changes in land-cover are driven by four categories of causes[1]: (1) long-term nat…     

Quasi indicatrix approach for distortion visualization and analysis for map projections

Tissot’s indicatrix or ellipse of distortion is a diagram that is the projection of an infinitesimal circle on the original surface. It is normally an ellipse of which elongation depends on the amount of distortion caused by map projection. It provides a medium for analyzing existing projections and developing new ones. The ellipse can be scaled and depicted on the map for visualization purposes. This paper presents an alternative approach, in which the projection of a finite small circle on the sphere is used. Its projection is normally an ellipse that can be very close to Tissot’s indicatrix, and is called quasi indicatrix, here. Its parameters can be derived from the forward projection equations without using partial derivatives. Therefore, it is a useful and practical approach from a programmer’s point of view. The quasi indicatrix approach is also numerically tested on Aitoff–Hammer projection with a set of points. The indicatrix parameters obtained by using this approach deviate 0.5% from the ground truths at most, being the average less than 0.2%.     

NDVI changes in China between 1989 and 1999 using change vector analysis based on time series data

Change vector analysis (CVA) and principal component analysis in NDVI time-trajectories space are powerful tools to analyze land-cover change. The magnitude of the change vector indicates amplitude of the change, while its direction indicates the nature of the change. CVA is applied to two remotely sensed indicators of land surface conditions, NDVI and spatial structure, in order to improve the capability to detect and categorize land-cover change. The magnitude and type of changes are calculated in China from 1989 to 1999. Through the research, the main conclusions are drawn as follows: 1) The changes of NDVI are quite different between eastern China and western China, and the change range in the east is bigger than that in the west. The trend in NDVI time series is smoothly increasing, the increases happen mostly in Taiwan, Fujian, Sichuan and Henan provinces and the decreases occur in Yunnan and Xinjiang. 2) The spatial structure index can indicate changes in the seasonal ecosystem dynamics for spatially heterogeneous landscapes. Most of spatial structure changes, which occurred in southern China, correlated with vegetation growth processes and strike of mountains.     

A metaheuristic approach for efficient and effective sketch-to-metric map alignment

Sketching as a natural mode for human communication and creative processes presents opportunities for improving human–computer interaction in geospatial information systems. However, to use a sketch map as user input, it must be localized within the underlying spatial data set of the information system, the base metric map. This can be achieved by a matching process called qualitative map alignment in which qualitative spatial representations of the two input maps are used to establish correspondences between each sketched object and one or more objects in the metric map. The challenge is that, to the best of our knowledge, no method for matching qualitative spatial representations suggested so far is applicable in realistic scenarios due to excessively long runtimes, incorrect algorithm design or the inability to use more than one spatial aspect at a time. We address these challenges with a metaheuristic algorithm which uses novel data structures to match qualitative spatial representations of a pair of maps. We present the design, data structures and performance evaluation of the algorithm using real-world sketch and metric maps as well as on synthetic data. Our algorithm is novel in two main aspects. Firstly, it employs a novel system of matrices known as local compatibility matrices, which facilitate the computation of estimates for the future size of a partial alignment and allow several types of constraints to be used at the same time. Secondly, the heuristic it computes has a higher accuracy than the state-of-the-art heuristic for this task, yet requires less computation. Our algorithm is also a general method for matching labelled graphs, a special case of which is the one involving complete graphs whose edges are labelled with spatial relations. The results of our evaluation demonstrate practical runtime performance and high solution quality.     

Map-matching algorithm for large-scale low-frequency floating car data

Large-scale global positioning system (GPS) positioning information of floating cars has been recognised as a major data source for many transportation applications. Mapping large-scale low-frequency floating car data (FCD) onto the road network is very challenging for traditional map-matching (MM) algorithms developed for in-vehicle navigation. In this paper, a multi-criteria dynamic programming map-matching (MDP-MM) algorithm is proposed for online matching FCD. In the proposed MDP-MM algorithm, the MDP technique is used to minimise the number of candidate routes maintained at each GPS point, while guaranteeing to determine the best matching route. In addition, several useful techniques are developed to improve running time of the shortest path calculation in the MM process. Case studies based on real FCD demonstrate the accuracy and computational performance of the MDP-MM algorithm. Results indicated that the MDP-MM algorithm is competitive with existing algorithms in both accuracy and computational performance.     

A new pseudocylindrical equal-area projection for adaptive composite map projections

The recently introduced adaptive composite map projection technique changes the projection to the geographic area shown on a map. It is meant as a replacement for the commonly used web Mercator projection, which grossly distorts areas when representing the entire world. The original equal-area version of the adaptive composite map projection technique uses the Lambert azimuthal projection for regional maps and three alternative projections for world maps. Adaptive composite map projections can include a variety of other equal-area projections when the transformation between the Lambert azimuthal and the world projections uses Wagner’s method. To select the most suitable pseudocylindrical projection, the distortion characteristics of a pseudocylindrical projection family are analyzed, and a user study among experts in the area of map projections is carried out. Based on the results of the distortion analysis and the user study, a new pseudocylindrical projection is recommended for extending adaptive composite map projections. The new projection is equal-area throughout the transformation to the Lambert azimuthal projection and has better distortion characteristics then small-scale projections currently included in the adaptive composite map projection technique.     

Voronoi tessellation on the ellipsoidal earth for vector data

Voronoi tessellation, and its dual the Delaunay triangulation, provide a cohesive framework for the study and interpretation of phenomena of geographical space in two and three dimensions. The planar and spherical solutions introduce errors in the positional accuracy of both Voronoi vertices and Voronoi edges due to errors in distance computations and the path connecting two locations with planar lines or great circle arcs instead of geodesics. For most geospatial applications the introduction of the above errors is insignificant or tolerable. However, for applications where the accuracy is of utmost importance, the ellipsoidal model of the Earth must be used. Characteristically, the introduction of any positional error in the delimitation of maritime zones and boundaries results in increased maritime space for one state at the expense of another. This is a situation that may, among others, have a serious impact on the financial activities and the relations of the states concerned. In the context of previous work on maritime delimitation we show that the Voronoi diagram constitutes the ideal solution for the development of an automated methodology addressing the problem in its entirety. Due to lack of a vector methodology for the generation of Voronoi diagram on the ellipsoid, the aforementioned solution was constrained by the accuracy of existing approaches. In order to fill this gap, in this paper we deal with the inherent attributes of the ellipsoidal model of the Earth, e.g. the fact that geodesics are open lines, and we elaborate on a methodology for the generation of the Voronoi diagram on the ellipsoid for a set of points in vector format. The resulting Voronoi diagram consists of vertices with positional accuracy that is only bounded by the user needs and edges that are comprised of geodesics densified with vertices equidistant to their generators. Finally, we present the implementation of the proposed algorithm in the Python programming language and the results of two case studies, one on the formation of closest service areas and one on maritime boundaries delimitation, with the positional accuracy set to 1 cm.     

Selective omission of road features based on mesh density for automatic map generalization

Selection of roads is an intractable generalization operation due to the difficulty in retaining the density difference and connectivity of a road network. This paper proposes a novel approach of selective omission for roads based on mesh density. The density of a road network and its local variations are calculated using meshes as units. Since maps at different scales usually reveal different densities, different density thresholds for road networks are determined on the basis of theoretical analysis and empirical study of mesh densities on maps at different scales. The selection process starts with the identification of the meshes that have a density beyond the threshold. The mesh with the largest density is first treated. Its bounding road segments are ordered according to their relative importance. The least important segment is eliminated. The remaining segments are then merged with the adjacent mesh, thus forming a new mesh. The selection procedure is repeated until none of the meshes has a density beyond the threshold. Such a process of eliminating road segments and merging meshes can ensure the road network connectivity. In this study, the meshes are classified depending on the types of road segment. For the different mesh types, their density thresholds are set to be different, which can be used as an indicator for the preservation of the density difference. This proposed approach considers topological, geometric and semantic properties of the road network. It was applied to two sets of road networks, and the results of selection are convincing. This methodology has now been adopted for the updating of 1:50,000 maps of China.