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].https://mapnik.org.
[22] YOUNGBLOOD B.GeoServer [OL].http://geoserver.org.
[23] KROPLA B.MapServer [OL].https://mapserver.org.
[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.
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