Title: Topological data analysis (TDA) applied to reveal pedogenetic principles of European topsoil system
Authors: SAVIC ALEXANDERTOTH GERGELYDUPONCHEL LUDAOVIC
Citation: SCIENCE OF THE TOTAL ENVIRONMENT vol. 586 p. 1091-1100
Publisher: ELSEVIER SCIENCE BV
Publication Year: 2017
JRC N°: JRC106266
ISSN: 0048-9697
URI: http://www.sciencedirect.com/science/article/pii/S0048969717303431?via%3Dihub
http://publications.jrc.ec.europa.eu/repository/handle/JRC106266
DOI: 10.1016/j.scitotenv.2017.02.095
Type: Articles in periodicals and books
Abstract: Recent developments in appliedmathematics are bringing newtools that are capable to synthesize knowledge in various disciplines, and help in finding hidden relationships between variables. One such technique is topological data analysis (TDA), a fusion of classical exploration techniques such as principal component analysis (PCA), and a topological point of view applied to clustering of results. Various phenomena have already received new interpretations thanks to TDA, fromthe proper choice of sport teams to cancer treatments. For the first time, this technique has been applied in soil science, to showthe interaction between physical and chemical soil attributes and main soil-forming factors, such as climate and land use. The topsoil data set of the Land Use/Land Cover Area Frame survey (LUCAS) was used as a comprehensive database that consists of approximately 20,000 samples, each described by 12 physical and chemical parameters. After the application of TDA, results obtained were cross-checked against known grouping parameters including five types of land cover, nine types of climate and the organic carbon content of soil. Some of the grouping characteristics observed using standard approaches were confirmed by TDA (e.g., organic carbon content) but novel subtle relationships (e.g., magnitude of anthropogenic effect in soil formation), were discovered as well. The importance of this finding is that TDA is a unique mathematical technique capable of extracting complex relations hidden in soil science data sets, giving the opportunity to see the influence of physicochemical, biotic and abiotic factors on topsoil formation through fresh eyes.
JRC Directorate:Sustainable Resources

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