Viewshed analysis is of great interest to location optimization, environmental planning, ecology and tourism. There have been plenty of viewshed analysis methods which are generally time-consuming and among these methods, the XDraw algorithm is one of the fastest algorithms and has been widely adopted in various applications. Unfortunately, XDraw suffers from chunk distortion which greatly lowers the accuracy, which limits the application of XDraw to a certain extent. Previous works failed to remove chunk distortion because they are unaware of the underlying contribution relationship. In this paper, we propose HiXDraw—an improved XDraw algorithm free of chunk distortion. We first uncover the causation of chunk distortion from an innovative contributing perspective. Instead of recording LOS (line-of-sight) height, we use a new auxiliary grid to preserve contributing points. By preventing improper terrain data from contributing to determining the visibility, we significantly improve the accuracy of the outcome viewshed. The experimental results reveal that the error rate largely decreases by 65%. Given the same computing time, HiXDraw is more accurate than previous improvements in XDraw. To validate the removal of chunk distortion, we also present a pillar experiment.

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Buffer analysis, a fundamental function in a geographic information system (GIS), identifies areas by the surrounding geographic features within a given distance. Real-time buffer analysis for large-scale spatial data remains a challenging problem since the computational scales of conventional data-oriented methods expand rapidly with increasing data volume. In this paper, we introduce HiBuffer, a visualization-oriented model for real-time buffer analysis. An efficient buffer generation method is proposed which introduces spatial indexes and a corresponding query strategy. Buffer results are organized into a tile-pyramid structure to enable stepless zooming. Moreover, a fully optimized hybrid parallel processing architecture is proposed for the real-time buffer analysis of large-scale spatial data. Experiments using real-world datasets show that our approach can reduce computation time by up to several orders of magnitude while preserving superior visualization effects. Additional experiments were conducted to analyze the influence of spatial data density, buffer radius, and request rate on HiBuffer performance, and the results demonstrate the adaptability and stability of HiBuffer. The parallel scalability of HiBuffer was also tested, showing that HiBuffer achieves high performance of parallel acceleration. Experimental results verify that HiBuffer is capable of handling 10-million-scale data.

With the advancement of active distribution network construction, to solve the shortcomings of the existing distribution network technology in distribution network perception and control, the relevant technologies of the Wide Area Measurement System (WAMS) in the transmission network have attracted more attention in terms of their usage in the distribution network. Micro Multifunction Phasor Measurement Unit (μMPMU), as an example, is being gradually utilized in the distribution network. However, the existing synchronous phasor transmission protocol is mainly designed for the transmission network, which requires an extension to meet the communication requirements to be directly used in the distribution network. In this work, the requirements of active distribution network communication are analyzed, and trade-offs between National Standard of the People’s Republic of China/Recommended (GB/T) 26865.2-2011 and International Electro technical Commission (IEC) 60870-5-101/104 protocol are compared. An extension method of the communication protocol is proposed, with the benefits of the prioritized transmission of important data, expanded remote control function of μMPMU, increased types of offline files, and reduced amount of network communication and data storage. The method is built upon the existing GB/T 26865.2-2011 protocol, and refers to the Application Service Data Unit (ASDU) of IEC 60870-5-101/104 to add an application extension frame. Application extension frames are used to transmit telemetry data, telesignalization, partial commands, and partial offline files. Finally, an experimental environment is set up, which includes a phasor measurement unit (PMU) Emulator, distribution network phasor data concentrator (PDC), and main station emulator to implement the standard GB/T 26865.2-2011 protocol and extension protocol. The feasibility and effectiveness of the method are confirmed by the superior performance of the extended protocol compared with the standard protocol.

Buffer and overlay analysis are fundamental operations which are widely used in Geographic Information Systems (GIS) for resource allocation, land planning, and other relevant fields. Real-time buffer and overlay analysis for large-scale spatial data remains a challenging problem because the computational scales of conventional data-oriented methods expand rapidly with data volumes. In this paper, we present HiBO, a visualization-oriented buffer-overlay analysis model which is less sensitive to data volumes. In HiBO, the core task is to determine the value of pixels for display. Therefore, we introduce an efficient spatial-index-based buffer generation method and an effective set-transformation-based overlay optimization method. Moreover, we propose a fully optimized hybrid-parallel processing architecture to ensure the real-time capability of HiBO. Experiments on real-world datasets show that our approach is capable of handling ten-million-scale spatial data in real time. An online demonstration of HiBO is provided (http://www.higis.org.cn:8080/hibo).

In the big data era, rapid visualization of large-scale vector data has become a serious challenge in Geographic Information Science (GIS). To fill the gap, we propose HiIndex, a spatial index that enables real-time and interactive visualization of large-scale vector data. HiIndex improves the state of the art with its low memory requirements, fast construction speed, and high visualization efficiency. In HiIndex, we present a tile-quadtree structure (TQ-tree) which divides the global geographic range based on the quadtree recursion method, and each node in the TQ-tree represents a specific and regular spatial range. In this paper, we propose a quick TQ-tree generation algorithm and an efficient visualization algorithm. Experiments show that the HiIndex is simple in structure, fast in construction, and less in memory occupation, and our approach can support interactive and real-time visualization of billion scale vector data with negligible pre-treatment time.

As the dramatical improvement of Global Position System (GPS) sensors in recent years, the research of trajectory dataset has become a hotspot in the field of geographic information systems (GIS). Pretreatment is very important for extracting useful information from massive trajectory dataset. One of key problems is trajectory data compression. Aiming at preserving crucial feature of trajectories while compressing, this paper puts forward a method for compressing trajectory data that combines distance, angle, and velocity while maintaining the contour of the trajectory, especially the turning corners and U-turns in the compressed trajectory and the original trajectory. So, the compressed trajectory can be very useful for trajectory mining and road network update. The new method also shows applicability and stability through experiments on different datasets.

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