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Visualization, integration and analysis of multi-element geochemical data
KTH, School of Architecture and the Built Environment (ABE), Land and Water Resources Engineering.
2005 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

generated large databases containing information on the concentrations of chemical elements in rocks, surface sediments and biogeochemical materials. Regional geochemical data being imprecise, multivariate, spatially auto-correlated and non-normally distributed pose specific problems to the choice of data analysis methods. Commonly several methods are combined, and the choice of techniques depends on the characteristics of data as well as the purpose of study. One critical issue is dealing with extreme data values (or outliers) in the initial stages of analysis. Another common problem is that integrated analysis of several geochemical datasets is not possible without interpolating the point data into surfaces. Finally, separation of anthropogenic influences from natural geochemical background in the surface materials is an issue of great importance for environmental studies.

This study describes an approach to address the above-mentioned problems by a flexible combination and use of GIS and multivariate statistical techniques with high-dimensional visualization. Dynamically linked parallel coordinate and scatterplot matrix display techniques allow simultaneous presentation of spatial, multi-element and qualitative information components of geochemical data. The plots not only display data in multi-dimensional space, but also allow detailed inspection of the data with interactive multi-dimensional brushing tools. The results of the study indicate that these simple high-dimensional visualization techniques can successfully complement the traditional statistical and GIS analysis in all steps of data processing, from data description and outlier identification through data integration, analysis, validation, and presentation of results. The outcomes of the study include: a visual procedure towards intelligent data cleaning where potentially significant information in very high element concentrations is preserved, methods for integration and visual analysis of geochemical datasets collected in different grids, estimation of geochemical baseline concentrations of trace metals in till geochemistry of southeastern Sweden, use of multi-element spatial fingerprints to trace natural geochemical patterns in biogeochemistry, and a new graphical approach to present multi-element geochemical data summaries and results from numerical analysis.

Place, publisher, year, edition, pages
Stockholm: KTH , 2005.
Series
Trita-LWR. PHD, ISSN 1650-8602 ; 1018
Keyword [en]
Earth sciences, GIS, interactive visualization, glacial till, biogeochemistry, metals, southeastern Sweden
Keyword [sv]
Geovetenskap
National Category
Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:kth:diva-169ISBN: 91-7178-014-9 (print)OAI: oai:DiVA.org:kth-169DiVA: diva2:7639
Public defence
2005-04-21, Kollegiesalen, Valhallavägen 79, Stockholm, 10:00
Opponent
Supervisors
Note
QC 20100609Available from: 2005-04-18 Created: 2005-04-18 Last updated: 2010-06-09Bibliographically approved
List of papers
1. Interactive visualization applied to multivariate geochemical data: A case study
Open this publication in new window or tab >>Interactive visualization applied to multivariate geochemical data: A case study
2003 (English)In: Journal de Physique IV: Colloque, ISSN 1155-4339, E-ISSN 1764-7177, Vol. 107, 577-580 p.Article in journal (Refereed) Published
Abstract [en]

Geochemical survey data have commonly been analysed combining methods from several disciplines - statistics, geostatistics, geographic information technology, visualization. In initial stages of analysis, tables are often used to describe the data and present statistical measures. For too often the original data are manipulated in one or another way, for example, using mathematical transformations, or interpolation of points to a surface. It is the author's opinion that raw geochemical data should be used in initial stages of data description, thus preserving the original details. This is not a simple task, as geochemical data are commonly complex, multivariate, and collected on irregular grid. Data contain outliers, element contents vary within thousands of ppm (parts per million), and different chemical elements may be correlated. In the present study a graphical approach has been used to study distribution of 5 heavy metals in glacial till. Using interactive visualization and multiple linked views of the data, the following issues were addressed: multi-element outliers, spatial trends, multi-element correlations and patterns. Interactive graphical techniques proved to be especially suitable for studying outliers and identifying and locating samples that are redundant and may be removed from data without loss of information. Visualization using linked views gave valuable insights about metal correlations and spatial trends. As the development of appropriate tools for analysing multivariate spatial data are still in its early stages, visualization freeware seems to be a good alternative providing powerful, easy to use and intuitive techniques for exploratory data analysis.

Keyword
Engineering research, Environmental engineering, Environmental impact, Geographic information systems, Graph theory, Heavy metals, Interactive computer systems, Interpolation, Mathematical transformations, Statistical methods, Surveys
National Category
Earth and Related Environmental Sciences
Identifiers
urn:nbn:se:kth:diva-5027 (URN)10.1051/jp4:20030369 (DOI)000183782300142 ()
Note
QC 20100609Available from: 2005-04-18 Created: 2005-04-18 Last updated: 2017-12-05Bibliographically approved
2. Dealing with outliers and censored values in multi-element geochemical data: a visualization approach using XmdvTool
Open this publication in new window or tab >>Dealing with outliers and censored values in multi-element geochemical data: a visualization approach using XmdvTool
2005 (English)In: Applied Geochemistry, ISSN 0883-2927, E-ISSN 1872-9134, Vol. 20, no 2, 341-352 p.Article in journal (Refereed) Published
Abstract [en]

 Dealing with geochemical data also means coping with their underlying limitations that are related to sampling, analytical techniques, and other characteristics of the data. This paper discusses the issue of data cleaning, using a regional geochemical dataset of 6 heavy metals in glacial till. Interactive data manipulation techniques provided in the freeware visualization system XmdvTool were used for exploring both metal concentrations reported as under the detection limit, and high or extreme values (outliers) in the dataset. The proposed integrated visual evaluation (IVE) approach for selective removal of outliers outperformed simple removal of the highest concentrations of metals, showing that existing spatial multi-element fingerprints in data could be recognized and preserved by IVE. The uniqueness of visualization is in simultaneous display of both multivariate and spatial information. Being simple and interactive, integrated visual evaluation can be recommended as a valuable complementary tool in cleaning and analysing multielement geochernical data.

Keyword
Chemical cleaning, Concentration (process), Data reduction, Heavy metals
National Category
Earth and Related Environmental Sciences
Identifiers
urn:nbn:se:kth:diva-5028 (URN)10.1016/j.apgeochem.2004.08.006 (DOI)000227045100009 ()2-s2.0-12344311443 (Scopus ID)
Note
QC 20100609Available from: 2005-04-18 Created: 2005-04-18 Last updated: 2017-12-05Bibliographically approved
3. Integrating spatio-temporal information in environmental monitoring data: a visualization approach applied to moss data
Open this publication in new window or tab >>Integrating spatio-temporal information in environmental monitoring data: a visualization approach applied to moss data
2005 (English)In: Science of the Total Environment, ISSN 0048-9697, E-ISSN 1879-1026, Vol. 347, no 1-3, 1-20 p.Article in journal (Refereed) Published
Abstract [en]

Large-scale environmental monitoring data being sparse and collected on irregular grids, which may differ from year to year, are difficult to analyse and present. The traditional techniques from statistics and Geographic Information Systems (GIS) may not be useful given the often relatively small sample size combined with varying sampling density. In this study, the freeware visualization package XmdvTool was used for integration and exploration of monitoring data from three surveys of terrestrial mosses. Data on contents of Cu, Ni, Pb, V and Zn in mosses within an area of 300×300 km in southern Sweden, sampled in 1985 (177 samples), 1990 (156 samples) and 1995 (188 samples), were integrated and visualized using parallel coordinate and scatterplot display techniques. Several interesting findings about multi-element composition of samples, as well as changing temporal trends in the relations of five metals were made during interactive visual discovery. Visualization techniques for high-dimensional data may have limitations considering, for example, number of variables, ranges of data values, and spatial scales. Nevertheless, interactive data manipulation tools encourage the process of visual exploration, and the unique way of integrating spatial, temporal and multi-element components of moss data provided visual insights that are not possible to gain with traditional analysis tools.

Keyword
Moss survey; Environmental monitoring; Multi-element data; Visualization
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-5029 (URN)10.1016/j.scitotenv.2004.12.054 (DOI)000231553400001 ()2-s2.0-23444446919 (Scopus ID)
Note
QC 20100609Available from: 2005-04-18 Created: 2005-04-18 Last updated: 2017-12-05Bibliographically approved
4. The separation of multi-element spatial patterns in till geochemistry of southeastern Sweden combining GIS, principal component analysis and high-dimensional visualization
Open this publication in new window or tab >>The separation of multi-element spatial patterns in till geochemistry of southeastern Sweden combining GIS, principal component analysis and high-dimensional visualization
2007 (English)In: Geochemistry: Exploration, Environment, Analysis, ISSN 1467-7873, E-ISSN 2041-4943, Vol. 7, no 4, 303-318 p.Article in journal (Refereed) Published
Abstract [en]

The chemical composition of glacial till is a product of parentrocks, glacial and post-glacial processes and reflects the geogenicvariation of chemical elements. Contrasting chemical compositionof rock types together with spatial variation in distributionpatterns of metals in the fine fraction of till in southeasternSweden assists in the identification of the signatures reflectingparent rocks in glacial till samples. The spatial patterns ofCu, Co, Ni, Pb, V and Zn in 1411 till samples were presentedby point symbol maps, followed by the extraction of multi-elementassociations by employing principal component analysis (PCA)and interactive high-dimensional visualization. The most influentialmulti-element spatial patterns in till data could be separatedusing either the numerical (PCA) or the visual approach. However,more information was extracted by combining the two techniques.In addition, interactive visualization provided an objectivepresentation of complex information in sparse lithogeochemicaldata. The study resulted in new knowledge about the naturalvariation of the levels of six elements in till, and a graphicalpresentation to convey information about and compare multi-elementgeochemical signatures.

Keyword
Multi-element spatial patterns, Southeastern Sweden, Till geochemistry, Visualization
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-5030 (URN)10.1144/1467-7873/06-117 (DOI)000250859200003 ()2-s2.0-36148937858 (Scopus ID)
Note
QC 20100609Available from: 2005-04-18 Created: 2005-04-18 Last updated: 2017-12-05Bibliographically approved
5. Identification of the natural levels of Co, Cu, Ni, Pb, V and Zn in biogeochemical data from southeastern Sweden: use of multi-element signatures
Open this publication in new window or tab >>Identification of the natural levels of Co, Cu, Ni, Pb, V and Zn in biogeochemical data from southeastern Sweden: use of multi-element signatures
(English)Manuscript (Other academic)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-5031 (URN)
Note
QC 20100609Available from: 2005-04-18 Created: 2005-04-18 Last updated: 2010-06-09Bibliographically approved

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