Estimating the soil organic carbon content for European NUTS2 regions based on LUCAS data collection
2013
Panagos, Panos | Ballabio, Cristiano | Yigini, Yusuf | Dunbar, Martha B.
Under the European Union Thematic Strategy for Soil Protection, the European Commission Directorate-General for the Environment and the European Environmental Agency (EEA) identified a decline in soil organic carbon and soil losses by erosion as priorities for the collection of policy relevant soil data at European scale. Moreover, the estimation of soil organic carbon content is of crucial importance for soil protection and for climate change mitigation strategies.Soil organic carbon is one of the attributes of the recently developed LUCAS soil database. The request for data on soil organic carbon and other soil attributes arose from an on-going debate about efforts to establish harmonized datasets for all EU countries with data on soil threats in order to support modeling activities and display variations in these soil conditions across Europe.In 2009, the European Commission's Joint Research Centre conducted the LUCAS soil survey, sampling ca. 20,000 points across 23 EU member states. This article describes the results obtained from analyzing the soil organic carbon data in the LUCAS soil database. The collected data were compared with the modeled European topsoil organic carbon content data developed at the JRC. The best fitted comparison was performed at NUTS2 level and showed underestimation of modeled data in southern Europe and overestimation in the new central eastern member states. There is a good correlation in certain regions for countries such as the United Kingdom, Slovenia, Italy, Ireland, and France. Here we assess the feasibility of producing comparable estimates of the soil organic carbon content at NUTS2 regional level for the European Union (EU27) and draw a comparison with existing modeled data. In addition to the data analysis, we suggest how the modeled data can be improved in future updates with better calibration of the model.
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