GEMAS

Spatial analysis of the Ni distribution on a continental-scale using digital image processing techniques on European agricultural soil data

The GEMAS Project Team

Research output: Article

5 Citations (Scopus)

Abstract

This study demonstrates the use of digital image processing for the spatial pattern recognition and characterisation of Ni concentrations in topsoil in Europe. Moving average smoothing was applied to the TIN-interpolated grid model to suppress small irregularities. Digital image processing was applied then to the grid. Several NE-SW, E-W and NW-SE oriented features were revealed at the continental scale. The dominant NE-SW linear features follow the Variscan and Alpine orogenies. The highest variability zones are in the Alps and the Balkans where mafic and ultramafic rocks outcrop. A single major E-W oriented north-facing feature runs along the last continental glaciation zone. This zone also coincides with a series of local maxima in Ni concentration along the glaciofluvial deposits. The NW-SE elongated features are located in the Pyrenees, northern Italy, Hellas and Fennoscandia. This study demonstrates the advantages of digital image processing analysis in identifying and characterising spatial geochemical patterns unseen before on conventional colour-surface maps.

Original languageEnglish
Pages (from-to)143-157
Number of pages15
JournalJournal of Geochemical Exploration
Volume186
DOIs
Publication statusPublished - márc. 1 2018

Fingerprint

digital image
spatial analysis
agricultural soil
image processing
Image processing
Soils
glaciofluvial deposit
pattern recognition
ultramafic rock
mafic rock
Hercynian orogeny
smoothing
topsoil
Pattern recognition
glaciation
outcrop
Deposits
Rocks
Color
distribution

ASJC Scopus subject areas

  • Geochemistry and Petrology
  • Economic Geology

Cite this

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title = "GEMAS: Spatial analysis of the Ni distribution on a continental-scale using digital image processing techniques on European agricultural soil data",
abstract = "This study demonstrates the use of digital image processing for the spatial pattern recognition and characterisation of Ni concentrations in topsoil in Europe. Moving average smoothing was applied to the TIN-interpolated grid model to suppress small irregularities. Digital image processing was applied then to the grid. Several NE-SW, E-W and NW-SE oriented features were revealed at the continental scale. The dominant NE-SW linear features follow the Variscan and Alpine orogenies. The highest variability zones are in the Alps and the Balkans where mafic and ultramafic rocks outcrop. A single major E-W oriented north-facing feature runs along the last continental glaciation zone. This zone also coincides with a series of local maxima in Ni concentration along the glaciofluvial deposits. The NW-SE elongated features are located in the Pyrenees, northern Italy, Hellas and Fennoscandia. This study demonstrates the advantages of digital image processing analysis in identifying and characterising spatial geochemical patterns unseen before on conventional colour-surface maps.",
keywords = "Lineament analysis, Lithology, Numerical differential calculation, Soil parent material, Spatial pattern, Univariate statistics",
author = "{The GEMAS Project Team} and G. Jord{\'a}n and Attila Petrik and {De Vivo}, Benedetto and Stefano Albanese and Alecos Demetriades and Martiya Sadeghi",
year = "2018",
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T2 - Spatial analysis of the Ni distribution on a continental-scale using digital image processing techniques on European agricultural soil data

AU - The GEMAS Project Team

AU - Jordán, G.

AU - Petrik, Attila

AU - De Vivo, Benedetto

AU - Albanese, Stefano

AU - Demetriades, Alecos

AU - Sadeghi, Martiya

PY - 2018/3/1

Y1 - 2018/3/1

N2 - This study demonstrates the use of digital image processing for the spatial pattern recognition and characterisation of Ni concentrations in topsoil in Europe. Moving average smoothing was applied to the TIN-interpolated grid model to suppress small irregularities. Digital image processing was applied then to the grid. Several NE-SW, E-W and NW-SE oriented features were revealed at the continental scale. The dominant NE-SW linear features follow the Variscan and Alpine orogenies. The highest variability zones are in the Alps and the Balkans where mafic and ultramafic rocks outcrop. A single major E-W oriented north-facing feature runs along the last continental glaciation zone. This zone also coincides with a series of local maxima in Ni concentration along the glaciofluvial deposits. The NW-SE elongated features are located in the Pyrenees, northern Italy, Hellas and Fennoscandia. This study demonstrates the advantages of digital image processing analysis in identifying and characterising spatial geochemical patterns unseen before on conventional colour-surface maps.

AB - This study demonstrates the use of digital image processing for the spatial pattern recognition and characterisation of Ni concentrations in topsoil in Europe. Moving average smoothing was applied to the TIN-interpolated grid model to suppress small irregularities. Digital image processing was applied then to the grid. Several NE-SW, E-W and NW-SE oriented features were revealed at the continental scale. The dominant NE-SW linear features follow the Variscan and Alpine orogenies. The highest variability zones are in the Alps and the Balkans where mafic and ultramafic rocks outcrop. A single major E-W oriented north-facing feature runs along the last continental glaciation zone. This zone also coincides with a series of local maxima in Ni concentration along the glaciofluvial deposits. The NW-SE elongated features are located in the Pyrenees, northern Italy, Hellas and Fennoscandia. This study demonstrates the advantages of digital image processing analysis in identifying and characterising spatial geochemical patterns unseen before on conventional colour-surface maps.

KW - Lineament analysis

KW - Lithology

KW - Numerical differential calculation

KW - Soil parent material

KW - Spatial pattern

KW - Univariate statistics

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