Computer Science ›› 2020, Vol. 47 ›› Issue (9): 117-122.doi: 10.11896/jsjkx.190800121

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Display-oriented Data Visualization Technique for Large-scale Geographic Vector Data

MA Meng-yu, WU Ye, CHEN Luo, WU Jiang-jiang, LI Jun, JING Ning   

  1. College of Electronic Science and Technology,National University of Defense Technology,Changsha 410073,China
  • Received:2019-08-23 Published:2020-09-10
  • About author:MA Meng-yu,born in 1992,Ph.D.His main research interests include GIS,geo-computation methods,high performance parallel computing,spatial data analysis and visua-lization.
    JING Ning,born in 1962,Ph.D,professor,Ph.D supervisor,is a senior fellow of China Computer Federation.His main research interests include geographical information systems,database systems,spatial data analysis,and visua-lization.
  • Supported by:
    National Natural Science Foundation of China (41471321,41871284).

Abstract: Rapid visualization of large-scale geographic vector data remains a challenging problem in geographic information scien-ce.In existing visualization methods,the computational scales expand rapidly with data volumes,leading to the result that it is difficult to provide real-time visualization for large-scale geographic vector data,though parallel acceleration technologies are adop-ted.This paper presents a display-oriented data visualization method for large-scale geographic vector data.Different from traditional methods,the core task of the display-oriented method is to determine the pixel range according to the screen display and then calculate the value of each pixel in the range.As the number of pixels for display is stable,the display-oriented data visualization method is less sensitive to data volumes and can be used to provide real-time data visualization for large-scale geographic vector data.Experiments show that our approach is capable of handling 100-million-scale geographic vector data.

Key words: Data visualization, Spatial big data, Display-oriented computing, Parallel computing, Real-time

CLC Number: 

  • TP391
[1] HILL S,MARKRAM H.The Blue Brain Project [C]//International Conference of the IEEE Engineering in Medicine & Biology Society.IEEE,2006.
[2] FAGHMOUS J H,KUMAR V.Spatio-temporal Data Miningfor Climate Data:Advances,Challenges,and Opportunities [M]//Data Mining and Knowledge Discovery for Big Data.Springer Berlin Heidelberg,2014.
[3] ATEFEH F,KHREICH W.A Survey of Techniques for Event Detection in Twitter [J].Computational Intelligence,2013,31(1):132-164.
[4] ELDAWY A,MOKBEL M F,JONATHAN C.HadoopViz:AMapReduce framework for extensible visualization of big spatial data [C]//IEEE International Conference on Data Engineering.IEEE,2016:601-612.
[5] JIA Y,ZONGSI Z,MOHAMED S.GeoSparkViz:a scalable geospatial data visualization framework in the apache spark ecosystem [C]//ACM International Conference on Scientific and Statistical Database Management.ACM,2018:15.
[6] ZHANG S,HAN J,LIU Z,et al.SJMR:Parallelizing spatial join with MapReduce on clusters[C]//2009 IEEE International Conference on Cluster Computing and Workshops.IEEE,2009.
[7] LU W,SHEN Y,CHEN S,et al.Efficient processing of k nearest neighbor joins using MapReduce[J].Proceedings of the VLDB Endowment,2012,5(10):1016-1027.
[8] AJI A,WANG F,VO H,et al.Hadoop-GIS:A High-Performance Spatial Data Warehousing System over MapReduce[J].Proceedings Vldb Endowment,2013,6(11):1009-1020.
[9] NISHIMURA S,DAS S,AGRAWAL D,et al.MD-HBase:design and implementation of an elastic data infrastructure for cloud-scale location services[J].Distributed and Parallel Databases,2013,31(2):289-319.
[10] SHEN J X,CHEN L,WU Y,et al.Approach to Accelerating Dissolved Vector Buffer Generation in Distributed In-Memory Cluster Architecture[J].ISPRS International Journal of Geo-Information,2018,7(1):26.
[11] FAN J,JI M,GU G,et al.Optimization approaches to mpi and area merging-based parallel buffer algorithm[J].Boletim de Ciências Geodésicas,2014,20:237-256.
[12] HUANG X.Parallel Buffer Generation Algorithm for GIS[J].J.Geol.Geosci.,2013,2:115.
[13] WANG T D,ZHAO L J,WANG L Z,et al.Parallel research and opitmization of buffer algorithm based on equivalent arc partition[J].Remote Sensing Information,2016:147-152.
[14] BATTLE L,STONEBRAKER M,CHANG R.Dynamic reduction of query result sets for interactive visualizaton[C]//IEEE International Conference on Big Data.IEEE,2013.
[15] JUGEL U,JERZAK Z,HACKENBROICH G,et al.M4:A Visualization-Oriented Time Series Data Aggregation[J].Procee-dings of the Vldb Endowment,2014,7(10):797-808.
[16] WESLEY R,ELDRIDGE M,TERLECKI P T.An analytic data engine for visualization in tableau [C]//ACM Sigmod International Conference on Management of Data.ACM,2011.
[17] WICKHAM H.Bin-summarise-smooth:a framework for visualising large data.Technical report[R].RStudio.2013.
[18] WU E,BATTLE L,MADDEN S R.The case for data visualization management systems[J].PVLDB 2014,7(10):903-906.
[19] YAO X,ZHU D,YUN W,et al.A WebGIS-based decision support system for locust prevention and control in China [J].Computers and Electronics in Agriculture,2017,140:148-158.
[20] YAO X,YANG J,LI L,et al.LandQv1:A GIS cluster-basedmanagement information system for arable land quality big data [C]//International Conference on Agro-geoinformatics.IEEE,2017.
[21] PAVLENKO A.Mapnik [OL].
[22] YOUNGBLOOD B.GeoServer [OL].
[23] KROPLA B.MapServer [OL].
[24] GUO M,GUAN Q,XIE Z,et al.A spatially adaptive decomposition approach for parallel vector data visualization of polylines and polygons [J].International Journal of Geographical Information Science,2015,29(8):1419-1440.
[25] LIN W,ZHOU H,XIA P.An effective NoSQL-based vectormap tile management approach [J].ISPRS International Journal of Geo-Information,2016,5(11):1-25.
[26] JINZHU G A,CHAOLI W B,LIYA L B,et al.A Parallel Multiresolution Volume Rendering Algorithm for Large Data Visualization [J].Parallel Computing,2008,31(2):185-204.
[27] LI J,WU H,YANG C,et al.Visualizing dynamic geosciencesphenomena using an octree-based view-dependent LOD strategy within virtual globes [J].Computers & Geosciences,2011,37(9):1295-1302.
[28] TANG W.Parallel construction of large circular cartograms using graphics processing units [J].International Journal of Geographical Information Science,2013,27(11):2182-2206.
[29] GHOSH S,ELDAWY A,JAIS S.AID:An Adaptive Image Data Index for Interactive Multilevel Visualization [C]//IEEE International Conference on Data Engineering.IEEE,2019:1594-1597.
[1] LUO Xiang-yu, XU Hang-na, ZENG Hao-cheng, CHEN Zu-xi, YANG Fan. Symbolic Model Checking for Discrete Real-time Linear Dynamic Logic [J]. Computer Science, 2020, 47(9): 204-212.
[2] CHEN Guo-liang, ZHANG Yu-jie, . Development of Parallel Computing Subject [J]. Computer Science, 2020, 47(8): 1-4.
[3] YANG Wang-dong, WANG Hao-tian, ZHANG Yu-feng, LIN Sheng-le, CAI Qin-yun. Survey of Heterogeneous Hybrid Parallel Computing [J]. Computer Science, 2020, 47(8): 5-16.
[4] WANG Liang, ZHOU Xin-zhi, YNA Hua. Real-time SIFT Algorithm Based on GPU [J]. Computer Science, 2020, 47(8): 105-111.
[5] YANG Zong-lin, LI Tian-rui, LIU Sheng-jiu, YIN Cheng-feng, JIA Zhen, ZHU Jie. Streaming Parallel Text Proofreading Based on Spark Streaming [J]. Computer Science, 2020, 47(4): 36-41.
[6] DENG Ding-sheng. Application of Improved DBSCAN Algorithm on Spark Platform [J]. Computer Science, 2020, 47(11A): 425-429.
[7] WANG Yang, LI Peng, JI Yi-mu, FAN Wei-bei, ZHANG Yu-jie, WANG Ru-chuan, CHEN Guo-liang. High Performance Computing and Astronomical Data:A Survey [J]. Computer Science, 2020, 47(1): 1-6.
[8] XU Chuan-fu,WANG Xi,LIU Shu,CHEN Shi-zhao,LIN Yu. Large-scale High-performance Lattice Boltzmann Multi-phase Flow Simulations Based on Python [J]. Computer Science, 2020, 47(1): 17-23.
[9] XU Lei, CHEN Rong-liang, CAI Xiao-chuan. Scalable Parallel Finite Volume Lattice Boltzmann Method Based on Unstructured Grid [J]. Computer Science, 2019, 46(8): 84-88.
[10] GENG Hai-jun, YIN Xia. Efficient Intra-domain Routing Protection Algorithm Based on i-SPF [J]. Computer Science, 2019, 46(8): 116-120.
[11] ZHANG Shu-yu, DONG Da, XIE Bing, LIU Kai-gui. Bus Short-term Dynamic Dispatch Algorithm Based on Real-time GPS [J]. Computer Science, 2019, 46(6A): 497-501.
[12] ZHENG Hong-bo, WU Bin, XU Fei, ZHANG Mei-yu, QIN Xu-jia. Visualization of Solid Waste Incineration Exhaust Emissions Based on Gaussian Diffusion Model [J]. Computer Science, 2019, 46(6A): 527-531.
[13] MENG Zhi-qing, XU Wei-wei. Temporal Text Data Stream Feature Trend Model and Algorithm [J]. Computer Science, 2019, 46(6A): 417-422.
[14] SHU Na,LIU Bo,LIN Wei-wei,LI Peng-fei. Survey of Distributed Machine Learning Platforms and Algorithms [J]. Computer Science, 2019, 46(3): 9-18.
[15] QU Jia-bo, QIN Bo. Real-time Detection and Recognition Algorithm of Traffic Signs Based on ST-CNN [J]. Computer Science, 2019, 46(11A): 309-314.
Full text



[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75 .
[2] ZHOU Yan-ping and YE Qiao-lin. L1-norm Distance Based Least Squares Twin Support Vector Machine[J]. Computer Science, 2018, 45(4): 100 -105 .
[3] GENG Hai-jun, SHI Xin-gang, WANG Zhi-liang, YIN Xia and YIN Shao-ping. Energy-efficient Intra-domain Routing Algorithm Based on Directed Acyclic Graph[J]. Computer Science, 2018, 45(4): 112 -116 .
[4] ZHENG Xiu-lin, SONG Hai-yan and FU Yi-peng. Distinguishing Attack of MORUS-1280-128[J]. Computer Science, 2018, 45(4): 152 -156 .
[5] WU Shu, ZHOU An-min and ZUO Zheng. PDiOS:Private API Call Detection in iOS Applications[J]. Computer Science, 2018, 45(4): 163 -168 .
[6] ZHU Shu-qin, WANG Wen-hong and LI Jun-qing. Chosen Plaintext Attack on Chaotic Image Encryption Algorithm Based on Perceptron Model[J]. Computer Science, 2018, 45(4): 178 -181 .
[7] GUO Shuai, LIU Liang and QIN Xiao-lin. Spatial Keyword Range Query with User Preferences Constraint[J]. Computer Science, 2018, 45(4): 182 -189 .
[8] ZHANG Jing and ZHU Guo-bin. Hot Topic Discovery Research of Stack Overflow Programming Website Based on CBOW-LDA Topic Model[J]. Computer Science, 2018, 45(4): 208 -214 .
[9] WEI Qin-shuang, WU You-xi, LIU Jing-yu and ZHU Huai-zhong. Distinguishing Sequence Patterns Mining Based on Density and Gap Constraints[J]. Computer Science, 2018, 45(4): 252 -256 .
[10] CAI Li, LIANG Yu, ZHU Yang-yong and HE Jing. History and Development Tendency of Data Quality[J]. Computer Science, 2018, 45(4): 1 -10 .