Records |
Author |
Van De Vijver, E.; Delbecque, N.; Verdoodt, A.; Seuntjens, P. |
Title |
Estimating the urban soil information gap using exhaustive land cover data: The example of Flanders, Belgium |
Type |
A1 Journal article |
Year |
2020 |
Publication |
Geoderma |
Abbreviated Journal |
Geoderma |
Volume |
372 |
Issue |
|
Pages |
114371 |
Keywords |
A1 Journal article; Sustainable Energy, Air and Water Technology (DuEL) |
Abstract |
Human activities related to urbanization and industrialization have established a vast territory of urban soil worldwide. On traditional soil maps, urban and industrial areas usually appear as blind spots as they were beyond the interest of national soil survey campaigns. Furthermore, these soil maps are likely already outdated with respect to urban soil due to rapid urban expansion in recent decades. This research aims to evaluate the use of land cover data to estimate the urban soil information gap considering the highly urbanized region of Flanders, Belgium, as a case study. The current extent and spatial distribution of anthropogenic urban soil (1) was estimated through reclassification of recently acquired (2012) exhaustive land cover data, discriminating three qualitative likelihood levels (high-intermediate-low) of anthropogenic influence by urbanization, and (2) compared with its occurrence as represented by the 'Technosols/Not Surveyed area' in the legacy soil map of Belgium, as this map unit best matches with the likelihood for anthropogenic urban soil at the time of the National Soil Survey conducted between end 1940s and mid 1970s. The proposed reclassification of the land cover map resulted in 16.3% and 16.7% of Flanders' total area that corresponds with a high and intermediate likelihood for anthropogenic urban soil, which highlights the underestimation of the anthropogenic urban soil extent as represented by the 'Technosol/Not Surveyed' unit in the legacy soil map (only 13.7%). Moreover, a more realistic spatial pattern of anthropogenic urban soil occurrence was obtained, providing an improved basis for urban soil spatial analysis studies. The produced anthropogenic urban soil likelihood map therefore presents a useful supporting tool for coordinating future soil surveys in urban environments. |
Address |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
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Wos |
000535713600006 |
Publication Date |
2020-04-21 |
Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0016-7061 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
Impact Factor |
6.1 |
Times cited ![sorted by Times cited field, descending order (down)](img/sort_desc.gif) |
2 |
Open Access |
|
Notes |
; ; |
Approved |
Most recent IF: 6.1; 2020 IF: 4.036 |
Call Number |
UA @ admin @ c:irua:170153 |
Serial |
6510 |
Permanent link to this record |
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Author |
Allegretta, I.; Legrand, S.; Alfeld, M.; Gattullo, C.E.; Porfido, C.; Spagnuolo, M.; Janssens, K.; Terzano, R. |
Title |
SEM-EDX hyperspectral data analysis for the study of soil aggregates |
Type |
A1 Journal article |
Year |
2022 |
Publication |
Geoderma: an international journal of soil science |
Abbreviated Journal |
Geoderma |
Volume |
406 |
Issue |
|
Pages |
|
Keywords |
A1 Journal article; Antwerp X-ray Imaging and Spectroscopy (AXIS) |
Abstract |
Scanning electron microscopy coupled with microanalysis (SEM-EDX) is an important analytical tool for the morphological and chemical characterization of different types of materials. In many applications, SEM-EDX elemental maps are usually used and processed as images, thus flattening and reducing the spectroscopic information contained in EDX hyperspectral data cubes. The exploitation of the full hyperspectral dataset could be indeed very useful for the study of complex matrices like soil. In order to maximize the information attainable by SEM-EDX data cubes analysis, the software package “Datamuncher Gamma” was implemented and applied to study soil aggregates. By using this approach, different phases (silicates, aluminosilicates, Ca-carbonates, Ca-phosphates, organic matter, iron oxides) inside soil aggregates were successfully identified and segmented. The advantages of this method over the common ROI imaging approach are presented. Finally, this method was used to compare different aggregates in a Cr-polluted soil and understand their possible pedological history. The present method can be used for the analysis of every type of SEM-EDX data cubes, allowing its application to different types of samples and fields of study. |
Address |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
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Wos |
000708893700026 |
Publication Date |
2021-10-21 |
Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
|
Series Issue |
|
Edition |
|
ISSN |
0016-7061 |
ISBN |
|
Additional Links |
UA library record; WoS full record; WoS citing articles |
Impact Factor |
6.1 |
Times cited ![sorted by Times cited field, descending order (down)](img/sort_desc.gif) |
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Open Access |
Not_Open_Access |
Notes |
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Approved |
Most recent IF: 6.1 |
Call Number |
UA @ admin @ c:irua:182493 |
Serial |
7207 |
Permanent link to this record |