计算机科学 ›› 2020, Vol. 47 ›› Issue (9): 117-122.doi: 10.11896/jsjkx.190800121
马梦宇, 吴烨, 陈荦, 伍江江, 李军, 景宁
MA Meng-yu, WU Ye, CHEN Luo, WU Jiang-jiang, LI Jun, JING Ning
摘要: 对大规模地理矢量要素进行实时可视化是当今地理信息科学领域面临的一个严峻挑战。在现有地理矢量要素可视化方法中,随着数据规模的增长,计算规模也急剧扩大,这导致尽管使用了高性能计算技术,仍很难应对大规模地理矢量要素的实时可视化。基于此,文中提出了一种基于显示导向型计算的地理矢量要素可视化技术。该技术从显示角度出发,将每个用于屏幕显示的像素点作为独立的计算单元,根据用户浏览地理矢量要素时屏幕显示的区域及分辨率确定待计算的像素点范围,通过直接计算每个像素点的值来生成最终的显示结果。该技术使得可视化的计算规模仅依赖于屏幕显示的像素数量,具有对数据规模不敏感的优点,可用于支持大规模地理矢量要素的实时可视化。实验结果表明,显示导向型地理矢量可视化技术可用于支持亿级矢量数据的实时可视化绘制。
中图分类号:
[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. |
[1] | 陈慧嫔, 王琨, 杨恒, 郑智捷. 蓝舌病毒基因组序列多元概率特征可视化分析 Visual Analysis of Multiple Probability Features of Bluetongue Virus Genome Sequence 计算机科学, 2022, 49(6A): 27-31. https://doi.org/10.11896/jsjkx.210300129 |
[2] | 陈鑫, 李芳, 丁海昕, 孙唯哲, 刘鑫, 陈德训, 叶跃进, 何香. 面向国产异构众核架构的CFD非结构网格计算并行优化方法 Parallel Optimization Method of Unstructured-grid Computing in CFD for DomesticHeterogeneous Many-core Architecture 计算机科学, 2022, 49(6): 99-107. https://doi.org/10.11896/jsjkx.210400157 |
[3] | 骆菁菁, 唐卫贞, 丁继婷. 基于皮尔逊系数的管制仿真训练数据独立化与因子分析下的数据可视化研究 Research of ATC Simulator Training Values Independence Based on Pearson Correlation Coefficient and Study of Data Visualization Based on Factor Analysis 计算机科学, 2021, 48(6A): 623-628. https://doi.org/10.11896/jsjkx.210200021 |
[4] | 傅天豪, 田鸿运, 金煜阳, 杨章, 翟季冬, 武林平, 徐小文. 一种面向构件化并行应用程序的性能骨架分析方法 Performance Skeleton Analysis Method Towards Component-based Parallel Applications 计算机科学, 2021, 48(6): 1-9. https://doi.org/10.11896/jsjkx.201200115 |
[5] | 何亚茹, 庞建民, 徐金龙, 朱雨, 陶小涵. 基于神威平台的Floyd并行算法的实现和优化 Implementation and Optimization of Floyd Parallel Algorithm Based on Sunway Platform 计算机科学, 2021, 48(6): 34-40. https://doi.org/10.11896/jsjkx.201100051 |
[6] | 冯凯, 马鑫玉. (n,k)-冒泡排序网络的子网络可靠性 Subnetwork Reliability of (n,k)-bubble-sort Networks 计算机科学, 2021, 48(4): 43-48. https://doi.org/10.11896/jsjkx.201100139 |
[7] | 鄂海红, 张田宇, 宋美娜. 基于Web的数据可视化图表渲染优化方法 Web-based Data Visualization Chart Rendering Optimization Method 计算机科学, 2021, 48(3): 119-123. https://doi.org/10.11896/jsjkx.200600038 |
[8] | 胡蓉, 阳王东, 王昊天, 罗辉章, 李肯立. 基于GPU加速的并行WMD算法 Parallel WMD Algorithm Based on GPU Acceleration 计算机科学, 2021, 48(12): 24-28. https://doi.org/10.11896/jsjkx.210600213 |
[9] | 陈国良, 张玉杰. 并行计算学科发展历程 Development of Parallel Computing Subject 计算机科学, 2020, 47(8): 1-4. https://doi.org/10.11896/jsjkx.200600027 |
[10] | 阳王东, 王昊天, 张宇峰, 林圣乐, 蔡沁耘. 异构混合并行计算综述 Survey of Heterogeneous Hybrid Parallel Computing 计算机科学, 2020, 47(8): 5-16. https://doi.org/10.11896/jsjkx.200600045 |
[11] | 冯凯, 李婧. k元n方体的子网络可靠性研究 Study on Subnetwork Reliability of k-ary n-cubes 计算机科学, 2020, 47(7): 31-36. https://doi.org/10.11896/jsjkx.190700170 |
[12] | 杨宗霖, 李天瑞, 刘胜久, 殷成凤, 贾真, 珠杰. 基于Spark Streaming的流式并行文本校对 Streaming Parallel Text Proofreading Based on Spark Streaming 计算机科学, 2020, 47(4): 36-41. https://doi.org/10.11896/jsjkx.190300070 |
[13] | 邓定胜. 一种改进的DBSCAN算法在Spark平台上的应用 Application of Improved DBSCAN Algorithm on Spark Platform 计算机科学, 2020, 47(11A): 425-429. https://doi.org/10.11896/jsjkx.190700071 |
[14] | 汪洋, 李鹏, 季一木, 樊卫北, 张玉杰, 王汝传, 陈国良. 高性能计算与天文大数据研究综述 High Performance Computing and Astronomical Data:A Survey 计算机科学, 2020, 47(1): 1-6. https://doi.org/10.11896/jsjkx.190900042 |
[15] | 徐传福,王曦,刘舒,陈世钊,林玉. 基于Python的大规模高性能LBM多相流模拟 Large-scale High-performance Lattice Boltzmann Multi-phase Flow Simulations Based on Python 计算机科学, 2020, 47(1): 17-23. https://doi.org/10.11896/jsjkx.190500009 |
|