European Soil Data Centre: Response to European policy support and public data requirements

Panagos, Panos; Liedekerke, Marc Van; Jones, Arwyn; Montanarella, Luca

doi:10.1016/j.landusepol.2011.07.003

Cited by 547 publications

(297 citation statements)

References 28 publications

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“…scale and a uniform outcrop depth throughout the majority of the analyzed area. We consider these data more relevant for landslide susceptibility evaluation than the unsystematic soil parent material data of the ESDB (Heineke et al, 1998;Panagos et al, 2012) used for ELSUS 1000. As discussed in Günther et al (2014), soil parent material descriptions over Europe, as derived from the ESDB, are only partly lithological but also genetical and therefore hard to be spatially evaluated.…”

Section: Controlling Factors: Environmental Datamentioning

confidence: 99%

“…In particular, ELSUS V2: (i) covers a larger area (including Iceland, Cyprus, the Faroe Islands and the Shetland islands) with a higher spatial resolution (200 × 200 m cell size in contrast to the 1 × 1 km resolution of ELSUS 1000); (ii) uses an extended landslide inventory; and (iii) exploits the newly available digital information on shallow subsurface lithology, derived from the International Hydrogeological Map of Europe (IHME) at a 1:1.5 Mil. scale (Duscher et al, 2015), replacing the data set on soil parent material from the European Soil Database (ESDB) (Heineke et al, 1998;Panagos, Van Liedekerke, Jones, & Montanarella, 2012) previously used as a proxy for shallow subsurface lithology.…”

Section: Introductionmentioning

confidence: 99%

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Pan-European landslide susceptibility mapping: ELSUS Version 2

et al. 2018

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We present an updated version of the European landslide susceptibility map ELSUS 1000 released through the European Soil Data Centre in 2013. The ELSUS V2 map shows the landslide susceptibility zonation for individual climate-physiographic zones across Europe. ELSUS V2 covers a larger area of Europe than ELSUS 1000 at a higher spatial resolution (200 × 200 m). The updated map was prepared using the same semi-quantitative method as for ELSUS 1000, combining landslide frequency ratios information with a spatial multi-criteria evaluation model of three thematic predictors: slope angle, shallow subsurface lithology and land cover. However, the new map was prepared using also: (i) an extended landslide inventory, containing 30% of additional locations for model calibration, map validation and classification and (ii) a new lithological data set derived from the International Hydrogeological Map of Europe (IHME). The new version of the map increases the overall predictive performance of ELSUS by 8 %.ARTICLE HISTORY

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Section: Controlling Factors: Environmental Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Pan-European landslide susceptibility mapping: ELSUS Version 2

et al. 2018

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“…In summary, soil data used by the model were derived from the European Soil Database (ESDB) (King et al, 1994) available at the European Soil Data Centre (ESDAC-http://eusoils.jrc.ec. europa.eu/library/esdac/esdac_access2.cfm) (Panagos et al, 2012). The properties considered for the topsoil layer (0-30 cm) included texture, bulk density, pH, drainage class and rock content.…”

Section: Model and Input Data Setmentioning

confidence: 99%

Potential carbon sequestration of European arable soils estimated by modelling a comprehensive set of management practices

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Bampa

Panagos

et al. 2014

Global Change Biology

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Bottom-up estimates from long-term field experiments and modelling are the most commonly used approaches to estimate the carbon (C) sequestration potential of the agricultural sector. However, when data are required at European level, important margins of uncertainty still exist due to the representativeness of local data at large scale or different assumptions and information utilized for running models. In this context, a pan-European (EU + Serbia, Bosnia and Herzegovina, Montenegro, Albania, Former Yugoslav Republic of Macedonia and Norway) simulation platform with high spatial resolution and harmonized data sets was developed to provide consistent scenarios in support of possible carbon sequestration policies. Using the CENTURY agroecosystem model, six alternative management practices (AMP) scenarios were assessed as alternatives to the business as usual situation (BAU). These consisted of the conversion of arable land to grassland (and vice versa), straw incorporation, reduced tillage, straw incorporation combined with reduced tillage, ley cropping system and cover crops. The conversion into grassland showed the highest soil organic carbon (SOC) sequestration rates, ranging between 0.4 and 0.8 t C ha À1 yr À1 , while the opposite extreme scenario (100% of grassland conversion into arable) gave cumulated losses of up to 2 Gt of C by 2100. Among the other practices, ley cropping systems and cover crops gave better performances than straw incorporation and reduced tillage. The allocation of 12 to 28% of the European arable land to different AMP combinations resulted in a potential SOC sequestration of 101-336 Mt CO 2 eq. by 2020 and 549-2141 Mt CO 2 eq. by 2100. Modelled carbon sequestration rates compared with values from an ad hoc meta-analysis confirmed the robustness of these estimates.

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“…2005;Panagos, P. et al 2012). This types of information requirement generally cannot be fulfi lled with new data collections, at least not on such a level as in the frame of traditional soil surveys (Montanarella, L. 2010).…”

Section: Demands On Spatial Soil Informationmentioning

confidence: 99%

Compilation of novel and renewed, goal oriented digital soil maps using geostatistical and data mining tools

et al. 2015

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Due to former soil surveys and mapping activities signifi cant amount of soil information has accumulated in Hungary. Present soil data requirements are mainly fulfi lled with these available datasets either by their direct usage or aft er certain specifi c and generally fortuitous, thematic and/or spatial inference. Due to the more and more frequently emerging discrepancies between the available and the expected data, there might be notable imperfection as for the accuracy and reliability of the delivered products. With a recently started project we would like to signifi cantly extend the potential, how soil information requirements could be satisfi ed in Hungary. We started to compile digital soil maps, which fulfi l optimally the national and international demands from points of view of thematic, spatial and temporal accuracy. In addition to the auxiliary, spatial data themes related to soil forming factors and/or to indicative environmental elements we heavily lean on the various national soil databases. The set of the applied digital soil mapping techniques is gradually broadened incorporating and eventually integrating geostatistical, data mining and GIS tools. Regression kriging has been used for the spatial inference of certain quantitative data, like particle size distribution components, rootable depth and organic matt er content. Classifi cation and regression trees were applied for the understanding of the soil-landscape models involved in existing soil maps, and for the post-formalization of survey/compilation rules. The relationships identifi ed and expressed in decision rules made the compilation of spatially refi ned category-type soil maps (like genetic soil type and soil productivity maps) possible with the aid of high resolution environmental auxiliary variables. In our paper, we give a short introduction to soil mapping and information management concentrating on the driving forces for the renewal of soil spatial data infrastructure provided by the framework of Digital Soil Mapping. The fi rst results of DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project are presented in the form of brand new national and regional soil maps.

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European Soil Data Centre: Response to European policy support and public data requirements

Cited by 547 publications

References 28 publications

Pan-European landslide susceptibility mapping: ELSUS Version 2

Pan-European landslide susceptibility mapping: ELSUS Version 2

Potential carbon sequestration of European arable soils estimated by modelling a comprehensive set of management practices

Compilation of novel and renewed, goal oriented digital soil maps using geostatistical and data mining tools

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