The application of fuzzy C-means cluster analysis and non-linear mapping to a soil data set for the detection of polluted sites

Hanesch, Monika; Scholger, Robert; Dekkers, Mark J.

doi:10.1016/s1464-1895(01)00137-5

Cited by 124 publications

(66 citation statements)

References 12 publications

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“…The characterization of the spatial variability of soil attributes is essential to achieve a better understanding of the complex relations between soil properties, environmental factors and land use (Veldkamp et al, 2001;Yemefack et al, 2005). The problems associated with the characterization of heavy metals in the majority of sites are often due to multiple sources of pollution (Serrano et al, 1984;Boluda et al, 1988;Hanesch et al, 2001;Zarcinas et al, 2004) which can act on different scales.…”

Section: Introductionmentioning

confidence: 99%

Multiscale analysis of heavy metal contents in Spanish agricultural topsoils

Rodríguez¹,

Nanos

Grau³

et al. 2008

Chemosphere

207

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This study characterized and mapped the spatial variability patterns of seven topsoil heavy metals (Cr, Ni, Pb, Cu, Zn, Hg and Cd) within the Ebro river basin (9.3 million ha) by Multivariate Factorial Kriging. The variograms and cross-variograms of heavy metal concentrations showed the presence of multiscale variation that was modeled using three variogram models with ranges of 20 km (short-range), 100 km (medium-range) and 225 km (long-range). Our results indicate that the heavy metal concentration is influenced by bedrock composition and dynamics at all the spatial scales, while human activities have a notorious effect only at the short-and medium-range scale of variation. Sources of Cu, Pb and Zn (and secondary Cd) are associated with agricultural practices (at the short-range scale of variation), whereas Hg variation at the short-and medium-range scale of variation is related to atmospheric deposition.

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Section: Introductionmentioning

confidence: 99%

Multiscale analysis of heavy metal contents in Spanish agricultural topsoils

Rodríguez¹,

Nanos

Grau³

et al. 2008

Chemosphere

207

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“…Differences caused by soil texture, geological origin and anthropogenic sources of heavy metals results in spatial variability (Bak et al 1997), which increases the difficulty of this research and makes it necessary to conduct the surveys in different areas. However, since soil samples were distinct, it is essential to illustrate the data and assess potential environmental hazard in the form of raster maps depicting the regional geochemical distribution of pollutants by spatial interpolation (Li et al 2006, Hanesch 2001. Geostatistics provides a set of statistical tools for incorporating spatial coordinates of observations in data processing (Tao 1995, Goovaerts 1999, Norra et al 2001.…”

Section: Introductionmentioning

confidence: 99%

Multivariate geostatistical analysis of heavy metals in topsoils from Beijing, China

2007

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trolled by the soil parent materials. Concentrations of 7 heavy metals were comparable with the first level of environmental quality standard for soils of China and much lower than the second level of national standard for soils. Conclusion. The heavy metal concentrations in the topsoil of Beijing are mostly comparable with the background values, especially for As, Cr and Ni. In the city center of Beijing, Cu, Pb and Zn had a high concentration of distribution. The spatial features of As, Cr and Ni are mainly controlled by pedogenic factors, whereas Cd, Cu, Pb and Zn are controlled by anthropogenic and parent factors. Traffic and smelting contribute greatly to the increase of Pb, Zn and Cu in the soil, especially in the center of the city. Landfill may have also affected the soil quality around it. Recommendation. Different factors were controlled by parent materials, which might be related to the different soil minerals. Further research should be conducted in Beijing to elucidate the relationship between heavy metals and soil minerals. AbstractBackground. Regional soil environmental quality is a hotspot and difficulty in the environmental sciences for the spatial variability of pollutants and the relationship between them. Beijing, the capital of China, has been undergoing a rapid economical development during the past three decades, and thus might encounter the same issues as the developed countries. However, there is little information about the soil environmental quality of Beijing, especially at the regional scale. The real soil environmental situation of heavy metals remains unknown, even less the sources of possible pollutants.

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“…The usefulness and successful application of fuzzy clustering to geoscientific data has been demonstrated in several studies, e.g. Bosch et al (2013), Dekkers et al (2014), Hanesch et al (2001) and Templ et al (2008).…”

Section: Introductionmentioning

confidence: 99%

Testing cluster analysis on combined petrophysical and geochemical data for rock mass classification

Kitzig

Kepic

Kieu

2017

Exploration Geophysics

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Abstract. New drilling, measurement-while-drilling and top-of-hole sensing technologies are being developed to overcome the challenges of exploration for new mineral deposits under deep cover. These methods will provide continuous, near-real time data collection from every drillhole in the future. Consequently, there will be a need for efficient methods of analysing and interpreting this data stream to complement the exploration strategy. We demonstrate the usefulness of cluster analysis for rapid, automated rock mass classification, and the impact of selecting different subsets of the available data on the classification results. Our study shows that only a few measurements are needed to broadly domain the intersected rock mass and highlights the importance of selecting correct input data depending on the purpose of the classification. Our analysis also indicates the potential of identifying textural and rock mechanical properties from petrophysical measurements via cluster analysis.

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The application of fuzzy C-means cluster analysis and non-linear mapping to a soil data set for the detection of polluted sites

Cited by 124 publications

References 12 publications

Multiscale analysis of heavy metal contents in Spanish agricultural topsoils

Multiscale analysis of heavy metal contents in Spanish agricultural topsoils

Multivariate geostatistical analysis of heavy metals in topsoils from Beijing, China

Testing cluster analysis on combined petrophysical and geochemical data for rock mass classification

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