Large Vector Data Research Articles

Route selection for road vehicle real-driving emissions test using GIS

The European Commission has developed a Real-Driving Emissions (RDE) test for road vehicles that complies with the urban, rural and motorway criteria to ensure the exhaust emission produced could be accurately evaluated. Therefore, careful measures are taken in selecting the best routes to ensure the testing fulfils the targeted criteria. As there is no common method exist to select the testing route, analysis on the testing route selection was implemented using Geographic Information System (GIS) platform that is capable to deal with large vector data. Thus, the proposed framework facilitates the testing route selection process which is difficult to determine without a proper spatial analysis of network data. Specific route information comprises of road categories, route speed range and route classes were collected from the Open StreetMap (OSM) database. The generated route density and the topological route network structure were used to further analyse the suitability route as the requirement of Real-Driving Emissions test. As a result, five candidates of Real-Driving Emissions test route have been selected in Malaysia as a case study using GIS platform.

A feature selection approach towards progressive vector transmission over the Internet

WebGIS has been applied for visualizing and sharing geospatial information popularly over the Internet. In order to improve the efficiency of the client applications, the web-based progressive vector transmission approach is proposed. Important features should be selected and transferred firstly, and the methods for measuring the importance of features should be further considered in the progressive transmission. However, studies on progressive transmission for large-volume vector data have mostly focused on map generalization in the field of cartography, but rarely discussed on the selection of geographic features quantitatively. This paper applies information theory for measuring the feature importance of vector maps. A measurement model for the amount of information of vector features is defined based upon the amount of information for dealing with feature selection issues. The measurement model involves geometry factor, spatial distribution factor and thematic attribute factor. Moreover, a real-time transport protocol (RTP)-based progressive transmission method is then presented to improve the transmission of vector data. To clearly demonstrate the essential methodology and key techniques, a prototype for web-based progressive vector transmission is presented, and an experiment of progressive selection and transmission for vector features is conducted. The experimental results indicate that our approach clearly improves the performance and end-user experience of delivering and manipulating large vector data over the Internet.

An efficient data organization and scheduling strategy for accelerating large vector data rendering

AbstractRendering large volumes of vector data is computationally intensive and therefore time consuming, leading to lower efficiency and poorer interactive experience. Graphics processing units (GPUs) are powerful tools in data parallel processing but lie idle most of the time. In this study, we propose an approach to improve the performance of vector data rendering by using the parallel computing capability of many‐core GPUs. Vertex transformation, largely a mathematical calculation that does not require communication with the host storage device, is a time‐consuming procedure because all coordinates of each vector feature need to be transformed to screen vertices. Use of a GPU enables optimization of a general‐purpose mathematical calculation, enabling the procedure to be executed in parallel on a many‐core GPU and optimized effectively. This study mainly focuses on: (1) an organization and storage strategy for vector data based on equal pitch alignment, which can adapt to the GPU's calculating characteristics; (2) a paging‐coalescing transfer and memory access strategy for vector data between the CPU and the GPU; and (3) a balancing allocation strategy to take full advantage of all processing cores of the GPU. Experimental results demonstrate that the approach proposed can significantly improve the efficiency of vector data rendering.

An Efficient Parallel Map Visualization Framework for Large Vector Data

With the tremendous development of surveying and mapping technologies, the volume of vector data is becoming larger. For mapping workers and other GIS scientists, map visualization is one of the most common functions of GIS software. But it is also a time-consuming process when processing massive amounts of vector data. Especially in an Internet map service environment, large numbers of concurrent users can cause major processing delays. In order to address this issue, this paper develops an efficient parallel visualization framework for large vector data sets by leveraging the advantages and characteristics of graphics cards, focusing on storage strategy and transfer strategy. The test results demonstrate that this new approach can reduce the computing times for visualizing large vector maps.

An efficient rendering method for large vector data on large terrain models

This paper presents an efficient way to render large-scale vector maps on level-of-detail (LOD) digital elevation models (DEMs). By using the frame buffer and Voronoi diagram, we achieve a rapid simplification of large-scale vector maps while keeping their original topological relationships. With the simplified maps, we establish level-of-detail vector map models. In the detailed level, we use the stencil shadow volume approach to render the map accurately, and in the coarse level we use substitute techniques to render the map approximately yet more quickly. The method proposed in this paper is universally applicable to rendering vector maps on various LOD terrain models, and the overlaying performance is independent of the complexity of underlying terrain surfaces. By use of the view frustum culling and sub-region index techniques, the impact of complexity of vector maps is reduced, and the rendering time is restricted to a certain scope. Thereby, we can achieve seamless and rapid rendering of large-scale vector maps on LOD terrain surfaces.

Extensions of GAP‐tree and its implementation based on a non‐topological data model

This paper discusses extensions of GAP‐trees from three aspects and its implementation based on non‐topological structure in order to enhance access to large vector data sets. First of all, we apply cartographic generalization rules to build a generalization procedure of the GAP‐tree, which makes coarse representations more consistent with human cognition. Second, we replace the three‐dimensional (pseudo‐) Reactive‐tree index with a 2D R‐tree index and a B‐tree index to improve the system efficiency. Finally, we compress a binary GAP‐tree into multi‐way GAP‐trees in order to reduce data redundancy. The shallower multi‐way GAP‐trees not only eliminate redundant data but also accelerate the system's response time. The extensions have been successfully implemented in PostgreSQL. A test of Beijing's land‐use data at the 1:10 000 scale demonstrates that the extended GAP‐trees are efficient, compact, and easy to implement.