计算机科学 ›› 2021, Vol. 48 ›› Issue (6A): 552-557.doi: 10.11896/jsjkx.200900127

• 交叉&应用 • 上一篇    下一篇

基于气象因子的气候区划可视分析系统

姚林, 王翔坤, 贾钰沛, 耿仕洪, 朱敏   

  1. 四川大学计算机学院 成都610065
  • 出版日期:2021-06-10 发布日期:2021-06-17
  • 通讯作者: 朱敏(zhumin@scu.edu.cn)
  • 作者简介:yforests@163.com
  • 基金资助:
    四川大学-泸州市战略合作项目(2017CDLZ-S29)

Visual Analysis System of Climatic Regionalization Based on Meteorological Factors

YAO Lin, WANG Xiang-kun, JIA Yu-pei, GENG Shi-hong, ZHU Min   

  1. College of Computer Science,Sichuan University,Chengdu 610065,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:YAO Lin,born in 1997,postgraduate,is a member of China Computer Federation.His main research interests include visual analytics and bioinformatics.
    ZHU Min,born in 1971,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.Her main research interests include information visualization,visual analytics and bioinformatics.
  • Supported by:
    Sichuan University-Luzhou City Project for Strategic Cooperation(2017CDLZ-S29).

摘要: 水文勘测、环境监测和农业生产等领域的研究人员,需要将地理区域按气象因子划分为若干子区域,用于抽样和对比等后续分析研究。目前,基于气象因子的区域划分方法存在缺乏交互手段、输出形式和结果单一等问题。文中设计并实现了基于气象因子的气候区划可视分析系统,提供堆叠柱状图、雷达图、平行坐标系等视图,以及点选、悬浮等丰富的交互手段,允许专家通过聚类评估指标、气候地理分布、点簇关系以及自身领域知识来确定气候区划方案。同时,系统可展示气候区划的时序演化关系,验证代表站点与所属区域的属性匹配度,提高区划方案的解释性。最后,基于西南5省近50年的气象数据,通过探索区域划分方案、推演气候区划的时序变化等两个实际案例,验证了系统的有效性。

关键词: 聚类评估, 可视分析, 气候区划, 气象因子

Abstract: Researchers in the fields of hydrographic investigation,environmental monitoring and agricultural production need to divide geographical areas into several sub-areas according to meteorological factors for subsequent analysis and research,such as sampling and comparison.At present,climatic regionalization based on meteorological factors has some problems,such as lack of interactive means and single output of form and result.In this paper,a visual analysis system of climate regionalization based on meteorological factors is designed and implemented.The system provides views such as stacked histogram,radar map,parallel coordinate system,as well as rich interactive means such as clicking,hovering and so on.Experts can determine climate regionalization scheme through clustering quality metrics,geographical distribution of climate,point-cluster relationships and domain know-ledge.At the same time,the system can show the time series evolution of climate regionalization,represent the matching of the attributes of the site and the area to which it belongs,and improve the interpretability of regionalization schemes.Finally,based on the meteorological data of five provinces in southwest China in the past 50 years,the effectiveness of the system is verified by exploring the climatic regionalization scheme and deducing the time series change of regionalization.

Key words: Climatic regionalization, Cluster evaluation, Meteorological factors, Visual analysis

中图分类号: 

  • TP391
[1] MA B,ZHANG B,ZHOU D,et al.Analysis of drought characteristics of the east china monsoon area based on standardized precipitation evapotranspiration index[J].Journal of Natural Resources,2016,31(7):1185-1197.
[2] WANG D,ZHANG B,AN M L,et al.Temporal and spatial distributions of drought in southwest china over the past 53 years based on standardized precipitation evapotranspiration index[J].Journal of Natural Resources,2014,29(6):1003-1016.
[3] FU B J,CHEN L D,LIU G H.The objectives,tasks and characteristics of china ecological regionalization[J].Acta Ecologica Sinica,1999(5):3-5.
[4] SUN R H,LI Z,CHEN L D.Review of ecological regionalization and classification in China:ecological patterns,functions,and ecosystem services[J].Acta Ecologica Sinica,2018,38(15):5271-5278.
[5] GUAN J,LIANG C,ZHAO L,et al.Analysis on Characteristics of Temporal-spatial Solar Radiation Distribution in Northwest China Based on Cloud Model[J].Transactions of the Chinese Society for Agricultural Machinery,2018,49(12):226-235.
[6] LAGUARDA A,ALONSO-SUAREZ R,TERRA R.Solar irradiation regionalization in Uruguay:Understanding the interannual variability and its relation to El Nio climatic phenomena[J].Renewable Energy,2020,158:444-452.
[7] PENG J,MAO Q,DU Y Y,et al.Research frontier and challenges of terrestrial system regionalization in China[J].Progress in Geography,2018,37(1):121-129.
[8] ZHENG C,WANG Q.Spatiotemporal variations of reference evapotranspiration in recent five decades in the arid land of Northwestern China[J].Hydrological Processes,2014,28(25):6124-6134.
[9] LI Y,LIANG K,BAI P,et al.The spatiotemporal variation of reference evapotranspiration and the contribution of its climatic factors in the Loess Plateau,China[J].Environmental Earth Sciences,2016,75(4):354.
[10] DINPASHOH Y,FAKHERI-FARD A,MOGHADDAM M,et al.Selection of variables for the purpose of regionalization of Iran's precipitation climate using multivariate methods[J].Journal of hydrology,2004,297(1-4):109-123.
[11] SHI J,YANG L.A Climate Classification of China through k-Nearest-Neighbor and Sparse Subspace Representation[J].Journal of Climate,2020,33(1):243-262.
[12] DENG Z,WENG D,CHEN J,et al.AirVis:Visual Analytics of Air Pollution Propagation[J].IEEE Transactions on Visualization and Computer Graphics,2019,26(1):800-810.
[13] GONG C,CHEN L,ZHU Z.A visualization system for calibrating multimodel ensembles in weather forecast[J].Journal of Visualization,2016,19(4):769-782.
[14] LIU L,PADILLA L,CREEM-REGEHR S H,et al.Visualizing uncertain tropical cyclone predictions using representative samples from ensembles of forecast tracks[J].IEEE Transactions on Visualization and Computer Graphics,2018,25(1):882-891.
[15] GOTZ D,ZHANG J,WANG W,et al.Visual analysis of high-dimensional event sequence data via dynamic hierarchical aggregation[J].IEEE Transactions on Visualization and Computer Graphics,2019,26(1):440-450.
[16] MA B,ENTEZARI A.An interactive framework for visualiza-tion of weather forecast ensembles[J].IEEE Transactions on Visualization and Computer Graphics,2018,25(1):1091-1101.
[17] KWON B C,EYSENBACH B,VERMA J,et al.Clustervision:Visual supervision of unsupervised clustering[J].IEEE Transactions on Visualization and Computer Graphics,2017,24(1):142-151.
[18] LIU Y,LI Z,XIONG H,et al.Understanding of internal clustering validation measures[C]//2010 IEEE International Conference on Data Mining.IEEE,2010:911-916.
[19] GIONIS A,MANNILA H,TSAPARAS P.Clustering aggregation[J].ACM Transactions on Knowledge Discovery from Data (TKDD),2007,1(1):4-33.
[20] CARUANA R,ELHAWARY M,NGUYEN N,et al.Meta clustering[C]//Sixth International Conference on Data Mining (ICDM'06).IEEE,2006:107-118.
[21] PARSONS L,HAQUE E,LIU H.Subspace clustering for high dimensional data:a review[J].Acm Sigkdd Explorations Newsletter,2004,6(1):90-105.
[22] SONG H,SZAFIR D A.Where's my data? evaluating visualizations with missing data[J].IEEE Transactions on Visualization and Computer Graphics,2018,25(1):914-924.
[23] MO C X,LIU P,ZHU X R,et al.The analysis on climatic factors duration spatial and temporal variations of Guangxi in recent 59 years[J].South-to-North Water Transfers and Water Science & Technology,2019,17(1):46-53,69.
[24] LIU X G,LENG X X,SUN G Z,et al.Assessment of Drought Characteristics in Yunnan Province Based on SPI and SPEI from 1961 to 2100[J].Transactions of the Chinese Society for Agricultural Machinery,2018,49(12):236-245,299.
[25] NIU K J,LIANG C,ZHAO L,et al.Temporal and spatial variation of drought in southwest china[J].Journal of Irrigation and Drainage,2014,33(3):1-6.
[26] KOZAK M.“A Dendrite Method for Cluster Analysis” byCaliński and Harabasz:A Classical Work that is Far Too Often Incorrectly Cited[J].Communications in Statistics-Theory and Methods,2012,41(12):2279-2280.
[27] ROUSSEEUW J P J.A graphical aid to the interpretation and validation of cluster analysis[J].Journal of Computational Application Math,1987,20:53-65.
[28] DAVIES D L,BOULDIN D W.A cluster separation measure[J].IEEE transactions on pattern analysis and machine intelligence,1979(2):224-227.
[1] 温啸林, 李长林, 张馨艺, 刘尚松, 朱敏.
基于DPoS共识机制的区块链社区演化的可视分析方法
Visual Analysis Method of Blockchain Community Evolution Based on DPoS Consensus Mechanism
计算机科学, 2022, 49(1): 328-335. https://doi.org/10.11896/jsjkx.201200118
[2] 罗月童, 汪涛, 杨梦男, 张延孔.
基于历史行车轨迹集的车辆行为可视分析方法
Historical Driving Track Set Based Visual Vehicle Behavior Analytic Method
计算机科学, 2021, 48(9): 86-94. https://doi.org/10.11896/jsjkx.200900040
[3] 白雪, 努尔布力, 王亚东.
网络安全态势感知研究现状与发展趋势的图谱分析
Map Analysis for Research Status and Development Trend on Network Security Situational Awareness
计算机科学, 2020, 47(6A): 340-343. https://doi.org/10.11896/JsJkx.190500169
[4] 饶永明, 张延孔, 谢文军, 刘璐, 刘新月, 罗月童.
交通事故时空模式可视分析方法
Visual Analysis Method of Traffic Accident Spatial-Temporal Pattern
计算机科学, 2019, 46(4): 14-21. https://doi.org/10.11896/j.issn.1002-137X.2019.04.003
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!