Article(id=1233732520190201932, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1233732515798774086, articleNumber=null, orderNo=null, doi=10.12284/hyxb2021067, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1584028800000, receivedDateStr=2020-03-13, revisedDate=1591718400000, revisedDateStr=2020-06-10, acceptedDate=null, acceptedDateStr=null, onlineDate=1772074354455, onlineDateStr=2026-02-26, pubDate=1621872000000, pubDateStr=2021-05-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772074354455, onlineIssueDateStr=2026-02-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772074354455, creator=13701087609, updateTime=1772074354455, updator=13701087609, issue=Issue{id=1233732515798774086, tenantId=1146029695717560320, journalId=1149651085930835976, year='2021', volume='43', issue='5', pageStart='1', pageEnd='144', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772074353408, creator=13701087609, updateTime=1772074353408, updator=13701087609, preIssue=null, nextIssue=null, ext=null, issueFiles=null}, startPage=135, endPage=144, ext={EN=ArticleExt(id=1233732520521551963, articleId=1233732520190201932, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Research on extraction algorithm of critical points of ocean flow field for topological analysis, columnId=1194652705852465724, journalTitle=Haiyang Xuebao, columnName=Article, runingTitle=null, highlight=null, articleAbstract=

The critical point is an important component in the topological structure of the ocean flow field. Feature extraction based on the critical point is of great significance to reveal the topological characteristics of the ocean flow field and carry out the topological analysis of the ocean flow field. In this paper, based on critical point theory and Sperner lemma, the improved bilinear interpolation algorithm and Sperner complete labeling method were integrated to extract the critical point features of ocean flow field data. First of all, we added sliding window to the bilinear interpolation algorithm to filter the candidate grid cells of the critical points, and use the aggregation idea to solve the ambiguity problem of grid interpolation by reducing the grid resolution. At the same time, we considered nine cases of the zero value grid, and used the iterative aggregation idea to slide filter the candidate grid cell, which solves the case that the interpolation grids are all 0. Secondly, the extraction rule of critical points of minimum method based on Sperner complete labeling was proposed, and the grid center with the smallest velocity vector module is taken as the critical point to solve the non-zero critical point extraction in the actual flow field physical scene. By combining and de duplicating the two extraction results, more comprehensive critical point extraction and classification results can be obtained. Finally, through the analysis of the experimental results of the flow field data in multiple sea areas and different depths, the effectiveness and feasibility of the integrated critical point extraction algorithm was proved.

, correspAuthors=Jing Ren, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2021 Pratacultural Science. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Min Ji, Jing Ren, Liguo Zhang, Ting Li, Yong Sun), CN=ArticleExt(id=1233732526976586122, articleId=1233732520190201932, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=面向拓扑分析的海洋流场临界点提取算法研究, columnId=1149698756456657529, journalTitle=海洋学报, columnName=论文, runingTitle=null, highlight=null, articleAbstract=

临界点是海洋流场拓扑结构中的重要构成要素,基于临界点的特征提取对于揭示海洋流场拓扑特征、开展海洋流场拓扑分析具有重要意义。本文基于临界点理论和Sperner引理,综合改进后的双线性插值算法和Sperner完全标号法,对海洋流场数据进行了临界点特征提取。首先,在双线性插值算法中添加滑动窗口处理,筛选临界点的候选网格单元,并采用聚合思想通过降低网格分辨率解决了网格插值中的二义性问题,同时考虑了0值网格存在的9种情形,通过迭代聚合思想滑动筛选候选网格单元,解决了插值网格均为0的情况。其次,提出了基于Sperner完全标号的最小值法临界点提取规则,将速度向量模最小的网格中心作为临界点,解决了实际流场物理场景中非0值的临界点提取。对两次提取结果进行合并、去重等处理,可以得到较为全面的临界点提取与分类结果。最后,通过对多个海域、不同深度流场数据的实验结果分析,证明了综合后的临界点提取方法的有效性及可行性。

, correspAuthors=任静, authorNote=null, correspAuthorsNote=
任静(1995-),女,山东省青州市人,主要研究方向为地理信息分析及应用。E-mail:
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季民(1970-),男,山东省齐河县人,博士,教授,主要从事地理信息系统设计与开发。E-mail:

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季民(1970-),男,山东省齐河县人,博士,教授,主要从事地理信息系统设计与开发。E-mail:

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季民(1970-),男,山东省齐河县人,博士,教授,主要从事地理信息系统设计与开发。E-mail:

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Qingdao: Ocean University of China, 2009., articleTitle=null, refAbstract=null)], funds=[Fund(id=1233807278961390083, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, awardId=null, language=CN, fundingSource=国家自然科学基金(41976184);山东省重大科技创新工程(2019JZZY020103), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1233807270069465395, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, xref=1, ext=[AuthorCompanyExt(id=1233807270077854005, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, companyId=1233807270069465395, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China), AuthorCompanyExt(id=1233807270086242614, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, companyId=1233807270069465395, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1山东科技大学 测绘与空间信息学院,山东 青岛 266590)]), AuthorCompany(id=1233807270182711610, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, xref=2, ext=[AuthorCompanyExt(id=1233807270191100218, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, companyId=1233807270182711610, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2National Land Surveying and Mapping Institute of Shandong Province, Jinan 250102, China), AuthorCompanyExt(id=1233807270199488827, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, companyId=1233807270182711610, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2山东省国土测绘院,山东 济南 250102)])], figs=[ArticleFig(id=1233807274888720819, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=EN, label=Fig. 1, caption=Classification of critical points in two-dimensional flow field, figureFileSmall=fbHK+cYrTteE2ZGiPRF9tg==, figureFileBig=ZohA4QTrxra/tih0TfhXdQ==, tableContent=null), ArticleFig(id=1233807274989384120, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=CN, label=图1, caption=二维流场临界点分类图, figureFileSmall=fbHK+cYrTteE2ZGiPRF9tg==, figureFileBig=ZohA4QTrxra/tih0TfhXdQ==, tableContent=null), ArticleFig(id=1233807275106824637, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=EN, label=Fig. 2, caption=Fully numbered illustration of a two-dimensional flow field[7]

Arrows and numbers 1, 2, 3 and 4 represent the direction of velocity vector; point P represents the possible position of critical point

, figureFileSmall=kEFj+DGIM/cXksM3aB5UfA==, figureFileBig=utBgtCz16N41evL0kWHEEg==, tableContent=null), ArticleFig(id=1233807275194905025, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=CN, label=图2, caption=二维流场完全标号示意图[7]

箭头及数字1,2,3,4代表速度矢量方向;点P代表临界点可能存在位置

, figureFileSmall=kEFj+DGIM/cXksM3aB5UfA==, figureFileBig=utBgtCz16N41evL0kWHEEg==, tableContent=null), ArticleFig(id=1233807275299762630, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=EN, label=Fig. 3, caption=Candidate grid case

● represents the center of the grid; +, − represent the different directions of seawater flow; P and Q represent the points with zero velocity component; dashed lines are the grid center lines; bold solid PQ is the contour of critical point

, figureFileSmall=SOMeuPlxTuPrRLb5wrHoDA==, figureFileBig=eMpvtkhQry624dl96GyILw==, tableContent=null), ArticleFig(id=1233807275463340491, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=CN, label=图3, caption=候选网格情况

●代表网格中心点;+、−代表海水流动的不同方向;PQ点代表流速分量为0的点;虚线为网格中心点连线;加粗实线PQ为临界点等值线

, figureFileSmall=SOMeuPlxTuPrRLb5wrHoDA==, figureFileBig=eMpvtkhQry624dl96GyILw==, tableContent=null), ArticleFig(id=1233807275597558221, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=EN, label=Fig. 4, caption=Ambiguous grid

● represents the center of the grid; +, − represent the different directions of seawater flow; P represents the points with zero velocity component; dashed lines are the grid center lines; bold solid lines are the contours of critical point

, figureFileSmall=MrENnOVlYUTi4GkPx1qbbg==, figureFileBig=fVpNxZGuIwUbV11NUze00A==, tableContent=null), ArticleFig(id=1233807275673055696, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=CN, label=图4, caption=二义性网格

●代表网格中心点;+、−代表海水流动的不同方向;P点代表流速分量为0的点;虚线为网格中心点连线;加粗实线为临界点等值线

, figureFileSmall=MrENnOVlYUTi4GkPx1qbbg==, figureFileBig=fVpNxZGuIwUbV11NUze00A==, tableContent=null), ArticleFig(id=1233807275782107603, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=EN, label=Fig. 5, caption=Grid value with 0

● represents the center of the grid; +, − represent the different directions of seawater flow; P represents the point with zero velocity component; dashed lines are the grid center lines; bold solid lines are the contours of critical point

, figureFileSmall=O9FnWnFf03PHiLk5tH1bZA==, figureFileBig=qbx80U0QhYXJ1CFAiBdoGQ==, tableContent=null), ArticleFig(id=1233807275886965204, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=CN, label=图5, caption=网格值含0的情况

●代表网格中心点;+、−代表海水流动的不同方向;P点代表流速分量为0的点;虚线为网格中心点连线;加粗实线为临界点等值线

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● represents the center of the grid; +, − represent the different directions of seawater flow; P and Q represent the points with 0 velocity component; dashed lines are the grid center lines; bold solid PQ is the contour of critical point

, figureFileSmall=4pQNH9QbQPw0X8fKEjNC4w==, figureFileBig=H1Id82BKTgPnKA22kYLYIg==, tableContent=null), ArticleFig(id=1233807276209926617, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=CN, label=图6, caption=双线性插值过程图

●代表网格中心点;+、−代表海水流动的不同方向;PQ点代表流速分量为0的点;虚线为网格中心点连线;加粗实线PQ为临界点等值线

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Trigonometric symbols are the critical points not extracted by bilinear interpolation

, figureFileSmall=gFuzfPsJuFkxi+AZywjZlg==, figureFileBig=evbJ9+YxRNzauEOPyMCFIQ==, tableContent=null), ArticleFig(id=1233807278202221038, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=CN, label=图9, caption=基于Sperner完全标号的临界点提取(a)与分类(b)结果

三角符号为双线性插值法未提出的临界点

, figureFileSmall=gFuzfPsJuFkxi+AZywjZlg==, figureFileBig=evbJ9+YxRNzauEOPyMCFIQ==, tableContent=null), ArticleFig(id=1233807278319661553, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=EN, label=Fig. 10, caption=Comprehensive extraction and classification result chart

In figure b, the triangle symbol represents the critical points extracted by Sperner complete labeling, which are not extracted by bilinear interpolation

, figureFileSmall=thKFms8rsXuWxyTqL/7LAQ==, figureFileBig=Pyzf8V8WquC4rwcgis9vZQ==, tableContent=null), ArticleFig(id=1233807278428713460, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=CN, label=图10, caption=综合提取分类结果

b中的三角符号为Sperner完全标号提取双线性插值未提取的临界点

, figureFileSmall=thKFms8rsXuWxyTqL/7LAQ==, figureFileBig=Pyzf8V8WquC4rwcgis9vZQ==, tableContent=null), ArticleFig(id=1233807278516793845, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=EN, label=Table 1, caption=

Statistical table of classification results of two methods

, figureFileSmall=null, figureFileBig=null, tableContent=
中心点鞍点交点排斥聚点吸引聚点
双线性插值分类结果80824
Sperner分类结果40034
), ArticleFig(id=1233807278609068538, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=CN, label=表1, caption=

两种方法分类结果统计表

, figureFileSmall=null, figureFileBig=null, tableContent=
中心点鞍点交点排斥聚点吸引聚点
双线性插值分类结果80824
Sperner分类结果40034
), ArticleFig(id=1233807278697148921, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=EN, label=Table 2, caption=

Different data validation results

, figureFileSmall=null, figureFileBig=null, tableContent=
美国沿海 5 000 m大西洋 2 500 m太平洋 3 000 m
双线性插值
Sperner完全标号
综合结果
中心点; 交点; 吸引聚点; 排斥聚点
), ArticleFig(id=1233807278776840701, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233732520190201932, language=CN, label=表2, caption=

不同数据验证结果

, figureFileSmall=null, figureFileBig=null, tableContent=
美国沿海 5 000 m大西洋 2 500 m太平洋 3 000 m
双线性插值
Sperner完全标号
综合结果
中心点; 交点; 吸引聚点; 排斥聚点
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面向拓扑分析的海洋流场临界点提取算法研究
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季民 1 , 任静 1, * , 张立国 2 , 李婷 1 , 孙勇 1
海洋学报 | 论文 2021,43(5): 135-144
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海洋学报 | 论文 2021, 43(5): 135-144
面向拓扑分析的海洋流场临界点提取算法研究
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季民1 , 任静1, * , 张立国2, 李婷1, 孙勇1
作者信息
  • 1山东科技大学 测绘与空间信息学院,山东 青岛 266590
  • 2山东省国土测绘院,山东 济南 250102
  • 季民(1970-),男,山东省齐河县人,博士,教授,主要从事地理信息系统设计与开发。E-mail:

通讯作者:

任静(1995-),女,山东省青州市人,主要研究方向为地理信息分析及应用。E-mail:
Research on extraction algorithm of critical points of ocean flow field for topological analysis
Min Ji1 , Jing Ren1, * , Liguo Zhang2, Ting Li1, Yong Sun1
Affiliations
  • 1College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
  • 2National Land Surveying and Mapping Institute of Shandong Province, Jinan 250102, China
出版时间: 2021-05-25 doi: 10.12284/hyxb2021067
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临界点是海洋流场拓扑结构中的重要构成要素,基于临界点的特征提取对于揭示海洋流场拓扑特征、开展海洋流场拓扑分析具有重要意义。本文基于临界点理论和Sperner引理,综合改进后的双线性插值算法和Sperner完全标号法,对海洋流场数据进行了临界点特征提取。首先,在双线性插值算法中添加滑动窗口处理,筛选临界点的候选网格单元,并采用聚合思想通过降低网格分辨率解决了网格插值中的二义性问题,同时考虑了0值网格存在的9种情形,通过迭代聚合思想滑动筛选候选网格单元,解决了插值网格均为0的情况。其次,提出了基于Sperner完全标号的最小值法临界点提取规则,将速度向量模最小的网格中心作为临界点,解决了实际流场物理场景中非0值的临界点提取。对两次提取结果进行合并、去重等处理,可以得到较为全面的临界点提取与分类结果。最后,通过对多个海域、不同深度流场数据的实验结果分析,证明了综合后的临界点提取方法的有效性及可行性。

海洋流场  /  临界点提取  /  双线性插值  /  Sperner完全标号  /  算法综合

The critical point is an important component in the topological structure of the ocean flow field. Feature extraction based on the critical point is of great significance to reveal the topological characteristics of the ocean flow field and carry out the topological analysis of the ocean flow field. In this paper, based on critical point theory and Sperner lemma, the improved bilinear interpolation algorithm and Sperner complete labeling method were integrated to extract the critical point features of ocean flow field data. First of all, we added sliding window to the bilinear interpolation algorithm to filter the candidate grid cells of the critical points, and use the aggregation idea to solve the ambiguity problem of grid interpolation by reducing the grid resolution. At the same time, we considered nine cases of the zero value grid, and used the iterative aggregation idea to slide filter the candidate grid cell, which solves the case that the interpolation grids are all 0. Secondly, the extraction rule of critical points of minimum method based on Sperner complete labeling was proposed, and the grid center with the smallest velocity vector module is taken as the critical point to solve the non-zero critical point extraction in the actual flow field physical scene. By combining and de duplicating the two extraction results, more comprehensive critical point extraction and classification results can be obtained. Finally, through the analysis of the experimental results of the flow field data in multiple sea areas and different depths, the effectiveness and feasibility of the integrated critical point extraction algorithm was proved.

ocean flow field  /  critical point extraction  /  bilinear interpolation  /  Sperner complete labeling  /  algorithm synthesis
季民, 任静, 张立国, 李婷, 孙勇. 面向拓扑分析的海洋流场临界点提取算法研究. 海洋学报, 2021 , 43 (5) : 135 -144 . DOI: 10.12284/hyxb2021067
Min Ji, Jing Ren, Liguo Zhang, Ting Li, Yong Sun. Research on extraction algorithm of critical points of ocean flow field for topological analysis[J]. Haiyang Xuebao, 2021 , 43 (5) : 135 -144 . DOI: 10.12284/hyxb2021067
随着海洋探测技术的快速发展,人类取得了前所未有的海洋大数据集合。海洋流场作为典型的矢量场,其特征结构复杂而多变,通过对其拓扑特征结构进行可视化变化分析,对于理解诸多海洋现象的产生、发展和演变等都具有十分重要的意义。
矢量场的拓扑特征可视化,自20世纪90年代提出以来就得到了迅猛发展。Helman和Hesselink[1-2]提出了基于雅克比矩阵特征值的临界点分类和矢量场的拓扑分析方法,而临界点作为矢量场拓扑结构分析的基础和重要组成部分,国内外学者针对矢量场临界点的提取进行了一系列研究。鉴于临界点一般位于0值矢量处,Lavin等[3]通过线性插值的方式进行了0矢量搜寻,Batra和Hesselink[4]通过对三角网格上的分段线性矢量场进行线性插值来提取临界点,Bhatia等[5]及王文涛[6]通过判断单纯形顶点处的矢量值是否构成一个内部包含原点的单纯形来快速判定临界点的存在。吴晓莉等[7]则将Sperner引理引入到临界点检测中,进行临界点的检测。以上研究均采用的是局部检测法,另有学者基于全局视角进行了临界点提取,Polthier和Preuβ[8-9]提出了一种利用离散Hodge分解的2D非结构化三角形网格矢量场临界点提取方法,Chen等[10]基于Morse分解的方法,通过流组合化、强联通分量提取、商图简化等步骤进行了临界点区域的识别。而海洋流场作为典型的矢量场,众多学者也对其进行了一系列拓扑特征提取与可视化研究,管倩倩[11]基于拓扑理论实现了海洋水团特征提取,廖忠云[12]从提取特征点出发,应用欧拉数值积分算法进行了海洋流线追踪与可视化,王辉赞等[13]通过提取涡旋中心和大小来进行涡旋轨迹追踪与表达,牛婵等[14]通过提取临界点来反映海洋流场空间拓扑结构。
在前述矢量场拓扑分析法中的临界点理论、插值求解临界点算法和Sperner引理检测临界点算法的启发下,综合双线性插值和Sperner引理检测两种算法,通过解决网格插值的二义性和零值网格点的影响问题,实现了海洋流场临界点的提取和分类。研究结果表明,本文算法提取的临界点更加全面、合理。
一个矢量场的拓扑结构由临界点和连接临界点的积分曲线或曲面组成[15]。依据Helman和Hesselink提出的临界点理论,临界点又被称为奇点、不动点或平衡点,在二维流场中是指矢量场的两个分量均为0的点,对于非退化的临界点(xy),可以用临界点位置处的偏导数矩阵(即雅克比矩阵)来表征矢量场及其附近曲线的行为[2-3],其公式如下:
${\boldsymbol{J}}\left( {x,y} \right) = \left[ {\begin{aligned}&{\frac{{\partial u}}{{\partial x}}}\quad{\frac{{\partial u}}{{\partial y}}}\\&{\frac{{\partial v}}{{\partial x}}}\quad{\frac{{\partial v}}{{\partial y}}}\end{aligned}} \right] \text{.}$
对于二维流场,可根据雅克比矩阵两个特征值λ1λ2的实部Re和虚部Im的正负等情况,来进行临界点分类,具体分类情况如图1所示(图中R表示实部值,I表示虚部值)。据此临界点主要分为交点、聚点、马鞍点和中心点,而交点和聚点又可进一步分为吸引交点、排斥交点、吸引聚点、排斥聚点。
现有的矢量场临界点检测方法如MC(Marching Cube)方法[16]、基于几何代数法[17]、基于More分解方法[10]、基于物理特征的方法[18]及庞加莱指数法[19-20]等,这些方法各有优缺点,而吴晓莉等[7]将Sperner引理引入到临界点检测中,给出了一种临界点检测的新算法,该算法定义速度分量均为0的点为临界点,借助Sperner引理和完全标号法进行了临界点提取算法研究。
Sperner引理[21]定义为:给定一个大三角形V1V2V3,并将它三角化(把它划分成有限多个较细的三角形,且每个细三角形的边都是另一个细三角形的边或者落在大三角形的边上),若将各顶点以下述的规定标记:
(1)顶点Vi的标号为ii=1, 2, 3;
(2)在ViVj边上的顶点只可以用i或者j作为标号;
(3)不在大三角形边上的顶点可以随意以1,2,3作为标号。
则至少存在一个细三角形其3个顶点的标号分别为1,2,3[22]
Sperner完全标号:给定二维流场内的2×2网格,各顶点的标号为中心点处速度矢量Vuv)落在uv为坐标轴的象限代码。当出现速度矢量与坐标轴共线的情形时,规定速度矢量与u轴正向重合的顶点标号为1;速度矢量与v轴正向重合的顶点标号为2;速度矢量与u轴负向重合的顶点标号为3;速度矢量与v轴负向重合的顶点标号为4。若4个网格的标号分别为1,2,3,4时,则称其是按矢量方向Sperner完全标号的,简称Sperner完全标号[7],具体完全标号形式如图2所示。
海洋流场中的临界点与流场中有意义的形状、结构、变化和现象(如涡流、激波等)密切相关,因此,临界点提取对于海洋流场拓扑结构特征的研究具有重要意义。目前的临界点检测方法各有优缺点,而线性插值方法简洁明了,易于程序实现,为此本文基于双线性插值方法进行了二维海洋流场中临界点的提取,并基于聚合思想解决了网格插值中的二义性问题,具体算法过程包含了:候选网格的筛选、临界点提取及分类等过程。
本文研究所用的海洋流场数据来源于美国国家海洋和大气管理局(NOAA)的国家环境信息中心(NCEI),为NetCDF格式的海洋再分析数据,包括了经向流速u和纬向流速v,数据空间范围为20°~42°N,98°~116°W,时间为2019年8月4日,深度为5 000 m,分辨率为0.033°。其中数据中的正负代表了海水流动的不同方向,东向和北向为正。
一般线性流场中临界点位于两个异向网格的中间,为了便于在经、纬两个方向同时筛选包含临界点的网格,为此,本文选择2×2滑动窗口,分别在获取的uv方向的两个数据层上进行遍历,筛选出临近网格流向异号的单元作为临界点的候选网格单元,筛选出的网格值正负异号的情况具体如图3所示,主要分为一正三负、两正两负、三正一负等4种情形,在图3a图3b图3d的3种情形中,可根据网格值的正负情形直接通过线性插值获得临界点等值线的位置,具体位置如图中加粗实线所示,而图3c的情形,由于存在正负值交叉的情形,因而带来了线性插值中的二义性问题。
针对图3c情形中的临界点插值,此时可能存在如图4a图4b所示的两种可能连接方式,为了进一步确定临界点等值线的连接方向,本文基于降低分辨率的聚合思想,将4个二义性候选网格的流速均值Avg作为降低分辨率后网格中心点处的值。Avg存在3种情形,若Avg=0,则直接判定该中心点为临界点;若Avg>0,则临界点等值线的连接方向与负向对角网格点的连线方向一致,如图4a;若Avg<0,则临界点等值线的连接方向与正向对角网格点的连线方向一致,如图4b
上述候选网格的筛选与二义性处理等过程,只考虑了网格值为正负的情形,当2×2的滑动窗口中存在0值情形时,若不加以考虑,就会造成临界点的遗漏。为此,根据0值网格的存在情况,本文将临界点的插值分为了如图5所示的9种情形,并且分别给出了临界点等值线的连接方式(加粗实线所示)。其中,第9种情形比较特殊,即4个网格的值均为0,为了解决这个问题,本文借助聚合思想,通过降低分辨率,取临近4个网格的速度均值为降低分辨率后网格的速度分量,并以当前降低分辨率后的大网格为左上角的起始网格,依然按照2×2的窗口进行滑动筛选,其结果必然为图5的9种情形之一,若还存在第9种情形,则进行迭代聚合。
当网格单元足够小时,可以认为沿着网格的边数据场是连续线性变化的[23],因此可以利用双线性插值的方法在网格边上求出0值PQ点的位置,如图6a图6b的计算结果。分别连接uv向计算结果中的插值点,两条连线的交点即为uv向均为0值的临界点,如图6c中的M点。
利用本文的双线性插值算法,对美国东部某海域5 000 m深度0.033°分辨率的再分析流场数据进行了临界点提取,结果如图7a所示,为了进一步确定临界点的分类,通过求其位置处uv速度分量的偏导数,进行雅克比矩阵构建,然后依据图1所示的分类方法对临界点进行了分类,具体分类结果如图7b所示,共22个点。
本文的临界点双线性插值与分类算法,简单明了,算法的时间复杂度为On2),空间复杂度为Onlog2n),提取结果全面,且临界点位置计算精确,可适用于多数二维流场的特征点提取。
前文双线性插值的临界点提取算法是基于临界点速度分量均为0的假设,但由于所采用的海洋流场再分析数据中可能存在计算舍入误差造成的近0值速度向量,并且在实际的流场物理场景中,也存在速度非0的临界点。由于Sperner完全标号理论依据流向变化进行临界点网格的筛选,相比于双线性插值方法依据uv流速数据求解,计算简便,为此本文也基于Sperner完全标号理论进行了临界点的提取算法研究。其算法过程包括了:网格流向计算、临界点候选网格筛选、临界点识别等。
该算法的执行主要包括以下几个步骤:
第一步,基于海洋流场再分析数据中的uv速度分量,进行网格点速度向量计算;
第二步,进行临界点候选网格筛选,首先以2×2的滑动窗口对整个流场进行遍历,在滑动窗口遍历过程中,依据Sperner完全标号理论,对4网格进行标号处理,若4个网格完全标号,则认为4个网格内存在临界点,从而将其作为临界点候选网格予以保留,否则继续进行窗口滑动;
第三步,进行临界点提取,临界点候选网格筛选完成后,多数研究是通过插值算法进行临界点提取,为了具有更宽泛的适用性,本文在此提出了基于最小值法的临界点提取规则,根据该规则,将4个候选网格中速度向量模最小的网格中心作为临界点,从而完成临界点的提取。
为了检测该算法提取的临界点的位置精度,本文还基于线性插值算法对上述过程提取的临界点进行了位置计算,具体计算结果如图8所示,其中红色圆点表示插值位置,绿色圆点表示最小值网格的中心点。通过计算分析发现,插值圆点基本上位于最小值网格内,且网格值越小,插值点距离中心越近,当网格分辨率足够小时,两类点的距离可忽略不计,但是最小值法临界点的提取,可避免插值处理过程,其算法复杂度为On),比插值算法更加高效,并且可忽略插值算法中的0值影响,因而,算法的适用性更广。
依据Sperner完全标号最小值法的临界点提取过程,同样对美国东部某海域5 000 m深度0.033°分辨率的再分析流场数据进行了临界点提取,结果如图9a所示,同样基于雅克比矩阵计算,对提取的临界点进行了分类,具体结果如图9b所示,共获得11个临界点。
通过对比图7图9的提取结果,发现Sperner完全标号法虽然未能检索出更多的临界点,但的确另外提取了几个插值算法遗漏的临界点,如图9中三角符号所示的临界点。该算法计算效率高、速度快,可较好的弥补双线性插值遗漏的临界点。
从两种算法的临界点提取结果图看,双线性插值算法提取结果数量更多,覆盖范围更广,但Sperner完全标号最小值法提取了双线性插值法未提取的临界点,并且速度更快,因此可综合两种算法临界点提取结果作为最终临界点提取结果。
统计分析两种算法的分类结果,如表1所示。
以上两种临界点提取算法各有优缺点,通过将两种算法提取结果的合并、去重等处理,可得到如图10所示的更加全面的临界点提取与分类结果,其中,中心点7个,交点7个,吸引聚点5个,排斥聚点5个,共24个。
为了进一步验证本文算法的适用性及可行性,针对不同区域、不同深度的大量海洋流场数据进行多次验证分析,其中表2所示,是以美国沿海区域深度5 000 m、大西洋部分海域深度2 500 m和太平洋海域深度3 000 m的数据为例进行的对比分析。提取结果显示:双线性插值算法临界点提取结果较为全面完整,但对非0值临界点的提取会偶有遗漏,而Sperner完全标号法计算高效,较好地弥补了双线性插值算法遗漏的部分临界点,如表2中美国沿海深度5 000 m数据中,弥补提取了1个中心点、1个交点和1个排斥聚点;对大西洋部分海域深度2 500 m数据中,弥补提取了1个吸引聚点、1个排斥聚点;对太平洋海域深度3 000 m数据中,弥补提取了1个吸引聚点。研究表明通过两种算法的综合处理,全面完整的提取了二维流场中的拓扑结构临界点,且算法简洁明了,可为二维流场的拓扑结构分析提供一种新的研究思路。
本文依据矢量场拓扑结构分析的临界点理论和Sperner引理,综合改进后的双线性插值算法和Sperner完全标号法,实现了海洋流场数据的临界点特征提取。相比于现有算法,本文算法临界点提取效果理想,且易于程序实现。改进后的双线性插值算法添加滑动窗口处理,便于临界点候选单元的筛选,涉及的聚合思想为解决插值网格二义性问题提供了新思路,而0值网格中临界点等值线连接方式的考虑,补充了流场网格插值情形,使得提取结果更加全面,且临界点位置计算精确,可适用于多数二维流场的特征点提取。同时,基于Sperner完全标号的临界点提取算法抛开传统插值求解临界点思想,创造性地提出了最小值法临界点提取规则,避免了插值处理过程,并且可忽略插值算法中的0值影响,效率更高,有着更广的适用性。而两种算法作为互补,算法的综合可实现更加全面的临界点提取与分类结果,为进一步实现海洋流场拓扑分析的流线追踪奠定临界点基础。
  • 国家自然科学基金(41976184);山东省重大科技创新工程(2019JZZY020103)
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doi: 10.12284/hyxb2021067
  • 接收时间:2020-03-13
  • 首发时间:2026-02-26
  • 出版时间:2021-05-25
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  • 收稿日期:2020-03-13
  • 修回日期:2020-06-10
基金
国家自然科学基金(41976184);山东省重大科技创新工程(2019JZZY020103)
作者信息
    1山东科技大学 测绘与空间信息学院,山东 青岛 266590
    2山东省国土测绘院,山东 济南 250102

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任静(1995-),女,山东省青州市人,主要研究方向为地理信息分析及应用。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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