Title: Mapping LUCAS topsoil chemical properties at European scale using Gaussian process regression
Authors: BALLABIO CRISTIANOLUGATO EMANUELEFERNANDEZ UGALDE OIHANEORGIAZZI ALBERTOJONES ARWYNBORRELLI PASQUALEMONTANARELLA LUCAPANAGOS PANAGIOTIS
Citation: GEODERMA vol. 355 p. 113912
Publisher: ELSEVIER SCIENCE BV
Publication Year: 2019
JRC N°: JRC115473
ISSN: 0016-7061 (online)
URI: https://www.sciencedirect.com/science/article/pii/S0016706119304768
http://publications.jrc.ec.europa.eu/repository/handle/JRC115473
DOI: 10.1016/j.geoderma.2019.113912
Type: Articles in periodicals and books
Abstract: This paper presents the second part of the mapping of topsoil properties based on the Land Use and Cover Area frame Survey (LUCAS). The first part described the physical properties (Ballabio et al., 2016) while this second part includes the following chemical properties: pH, Cation Exchange Capacity (CEC), calcium carbonates (CaCO3), C:N ratio, nitrogen (N), phosphorus (P) and potassium (K). The LUCAS survey collected harmonised data on changes in land cover and the state of land use for the European Union (EU). Among the 270,000 land use and cover observations selected for field visit, approximately 20,000 soil samples were collected in 24 EU Member States in 2009 together with more than 2000 samples from Bulgaria and Romania in 2012. The chemical properties maps for the European Union were produced using Gaussian process regression (GPR) models. GPR was selected for its capacity to assess model uncertainty and the possibility of adding prior knowledge in the form of covariance functions to the model. The derived maps will establish baselines that will help monitor soil quality and provide guidance to agro-environmental research and policy developments in the European Union. The derived maps will establish baselines that will help monitor soil quality and provide guidance to agro-environmental research and policy developments in the European Union.
JRC Directorate:Sustainable Resources

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