Visualizing GPR Data Using Spatial-Subband Configuration
In ground penetrating radar (GPR) applications, base-scale analysis can be a powerful tool to support data analysis and to build a consensus in data interpretation. In this paper, a study using the spatial-subband as a characterizing method to visualize structure attributes of GPR is presented. A dy...
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| Veröffentlicht in: | IEEE access 2018-01, Vol.6, p.54651-54659 |
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| creator | Yuan, Da Hong, Mei An, Zhiyong |
| description | In ground penetrating radar (GPR) applications, base-scale analysis can be a powerful tool to support data analysis and to build a consensus in data interpretation. In this paper, a study using the spatial-subband as a characterizing method to visualize structure attributes of GPR is presented. A dynamic framework is proposed to support the effective understanding and interpretation of structural patterns occluded in massive data. In this framework, variational mode decomposition is adopted to transform the GPR data into a set of subbands, each of which has a single mode and limited bandwidth. Meanwhile, the definable reconstruction provides a multiscale mapping for structural attributes. Significant patterns in the mapping are observed by employing both parameter adjustment and scale variation in data from a highway survey. The proposed approach can be extended to generate a broader interface with the parameter space for further exploration. Moreover, a multi-spatial map provides means of visualizing structural patterns of heterogeneous media. |
| doi_str_mv | 10.1109/ACCESS.2018.2868797 |
| format | Article |
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Moreover, a multi-spatial map provides means of visualizing structural patterns of heterogeneous media.</description><subject>Data analysis</subject><subject>data visualization</subject><subject>dynamic mapping</subject><subject>fuzzy c-means</subject><subject>Ground penetrating radar</subject><subject>Ground penetrating radar (GPR)</subject><subject>Mapping</subject><subject>Parameters</subject><subject>Spatial data</subject><subject>variational mode decomposition</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUE1Lw0AQXUTBUvsLegl4Tt3NZD9yLLHWQkEx1usySXbLlprUTXLQX29iSnEuM_OY997wCJkzumCMJg_LNF1l2SKiTC0iJZRM5BWZREwkIXAQ1__mWzJrmgPtS_UQlxOiPlzT4dH9uGofrF_fgkdsMdg1w5qdsHV4DLMuz7Eqg7SurNt3vkfr6o7cWDw2ZnbuU7J7Wr2nz-H2Zb1Jl9uwiKlqw-GhAmQkYsO4UYglA1CWJyjLHEoRK-SiBEBrEa0BhVQaZqAQMc2tiGBKNqNuWeNBn7z7RP-ta3T6D6j9XqNvXXE0mkKUIOMCjJCxRaFywRB624gzEJb1Wvej1snXX51pWn2oO1_17-so5lxxSdngCONV4eum8cZeXBnVQ-J6TFwPietz4j1rPrKcMebCUDGPJU3gF7MMelk</recordid><startdate>20180101</startdate><enddate>20180101</enddate><creator>Yuan, Da</creator><creator>Hong, Mei</creator><creator>An, Zhiyong</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| source | IEEE Open Access Journals; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Data analysis data visualization dynamic mapping fuzzy c-means Ground penetrating radar Ground penetrating radar (GPR) Mapping Parameters Spatial data variational mode decomposition |
| title | Visualizing GPR Data Using Spatial-Subband Configuration |
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