{"type": "FeatureCollection", "features": [{"id": "0c6c5bbc-20a7-4011-8585-7befb511a4b4", "type": "Feature", "geometry": null, "properties": {"updated": "2024-09-24T14:57:55", "type": "Dataset", "language": "en", "title": "GSI GEMAS European Geochemical Data", "description": "The GEMAS Dataset is based on low density geochemical sampling of agriculture (Ap) and Grassland (Gr) Soils across 34 European countries. Sample density covering an area of 5.6 million km\u00b2 of 1 site each, arable land (0-20\u00a0cm) and land under permanent grass cover (0-10\u00a0cm), per 2\u00a0500\u00a0km\u00b2. The Geochemical Mapping of Agricultural and GRAZING Land Soil comprises more than 70 chemical elements and parameters determined on more than 4000 soil samples. The geochemistry of European agriculture and grazing Soils are depicted graphically on maps of the GEMAS geochemical atlas.  In 2016 the Geological Survey of Ireland as a European partner contributes to GEMAS and EGDI (European Geological Data Infrastructure) with provision of a GIS Spatial data classification and publication of WMS geochemical web mapping services to support European data interoperability of EGDI web portal.   The GIS GEMAS sample classification was constructed in ArcGIS 10.1 and the original GEMAS Dataset is available as ESRI shapefile format.", "formats": [{"name": "ESRI REST"}], "keywords": ["agricultural-soil", "analysis", "arable-land", "arable-land-groundwater", "chemical", "chemistry", "continental-scale", "earth-science", "egdi", "environment", "europe", "european-soil-analysis", "forensic-chemistry", "gemas", "geochemical", "geochemical-analysis", "geochemical-mapping", "geology", "geoscientificinformation", "grazing-land", "groundwater", "heavy-metals", "ie", "ireland", "land", "lithosphere", "mapping", "metal", "micka", "pedosphere", "science", "soil", "soil-nutrient", "toxic-element", "trace-element"], "contacts": [{"organization": "https://data.gov.ie/organization/geological-survey-of-ireland", "roles": ["publisher"]}]}, "links": [{"href": "https://data.geus.dk/egdi/?mapname=egdi_new_structure#baslay=baseMapGEUS&optlay=&extent=1237790%2C1796730%2C4849410%2C4619780&%20target=_blank"}, {"href": "https://gemas.eurogeosurveys.org/"}, {"href": "https://gsi.geodata.gov.ie/downloads/Geochemistry/Data/IE_GSI_GEMAS_Geochemistry_Agricultural_Grazing_Land_Soil_EU_WGS84.zip"}, {"href": "https://gsi.geodata.gov.ie/server/rest/services/Geochemistry/IE_GSI_GEMAS_Geochemistry_Agricultural_Grazing_Land_Soil_EU_WGS84/MapServer"}, {"href": "https://gsi.geodata.gov.ie/server/rest/services/Geochemistry/IE_GSI_GEMAS_Geochemistry_Agricultural_Grazing_Land_Soil_EU_WGS84/MapServer?f=pjson"}, {"href": "https://gsi.geodata.gov.ie/server/services/Geochemistry/IE_GSI_GEMAS_Geochemistry_Agricultural_Grazing_Land_Soil_EU_WGS84/MapServer/WMSServer?request=GetCapabilities&service=WMS"}, {"href": "http://data.europa.eu/88u/dataset/0c6c5bbc-20a7-4011-8585-7befb511a4b4"}, {"rel": "self", "type": "application/geo+json", "title": "0c6c5bbc-20a7-4011-8585-7befb511a4b4", "name": "item", "description": "0c6c5bbc-20a7-4011-8585-7befb511a4b4", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0c6c5bbc-20a7-4011-8585-7befb511a4b4"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "10.1128/aem.01081-21", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-01T16:19:10Z", "type": "Journal Article", "created": "2021-09-01", "title": "Seasonality and geography have a greater influence than the use of chlorine-based cleaning agents on the microbiota of bulk tank raw milk.", "description": "<p>The microbiota of raw milk is affected by many factors that can control or promote the introduction of undesirable microorganisms. Chlorine-based cleaning agents have been commonly used due to their effectiveness in controlling undesirable microorganisms, but they have been associated with the formation of chlorine residues that are detrimental to product quality and may impact consumer health.</p>", "keywords": ["0301 basic medicine", "2. Zero hunger", "0303 health sciences", "Geography", "Microbiota", "Dairy", "Dairying", "03 medical and health sciences", "Milk", "Food Microbiology", "Animals", "Equipment Contamination", "DNA sequencing", "Metagenomics", "Seasons", "Chlorine", "Ireland", "Disinfectants"]}, "links": [{"href": "https://journals.asm.org/doi/pdf/10.1128/AEM.01081-21"}, {"href": "https://doi.org/10.1128/aem.01081-21"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20and%20Environmental%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1128/aem.01081-21", "name": "item", "description": "10.1128/aem.01081-21", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1128/aem.01081-21"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-10-28T00:00:00Z"}}, {"id": "10.2134/jeq2005.0121", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-01T16:20:08Z", "type": "Journal Article", "created": "2006-01-06", "title": "Greenhouse Gas Emissions From Conventional, Agri-Environmental Scheme, And Organic Irish Suckler-Beef Units", "description": "ABSTRACT<p>The problems of overproduction within the European Union countries and the environmental impact of agriculture have lead to the introduction of schemes that aim to reduce both. Beef (Bos taurus) production forms a large component of the Irish agricultural industry and accounts for more than one quarter of agricultural economic output. Recently, the European CAP (Common Agricultural Policy) has been re\uffe2\uff80\uff90evaluated to include supplementary measures that encompass the environmental role of agriculture rather than just the production role. A life cycle assessment (LCA) method was adopted to estimate emissions per kilogram of CO2 equivalent per kilogram of live weight (LW) leaving the farm gate per annum (kg CO2 kg\uffe2\uff88\uff921 LW yr\uffe2\uff88\uff921) and per hectare (kg CO2 ha\uffe2\uff88\uff921 yr\uffe2\uff88\uff921). Fifteen units engaged in suckler\uffe2\uff80\uff90beef production (five conventional, five in an Irish agri\uffe2\uff80\uff90environmental scheme, and five organic units) were evaluated for emissions per unit product and area. The average emissions from the conventional units were 13.0 kg CO2 kg\uffe2\uff88\uff921 LW yr\uffe2\uff88\uff921, from the agri\uffe2\uff80\uff90environmental scheme units 12.2 kg CO2 kg\uffe2\uff88\uff921 LW yr\uffe2\uff88\uff921, and from the organic units 11.1 kg CO2 kg LW yr\uffe2\uff88\uff921 The average emissions per unit area from the conventional units was 5346 kg CO2 ha\uffe2\uff88\uff921 yr\uffe2\uff88\uff921, from the agri\uffe2\uff80\uff90environmental scheme units 4372 kg CO2 ha\uffe2\uff88\uff921 yr\uffe2\uff88\uff921, and from the organic units 2302 kg CO2 ha\uffe2\uff88\uff921 yr\uffe2\uff88\uff921 Results indicated that moving toward extensive production could reduce emissions per unit product and area but live weight production per hectare would be reduced.</p>", "keywords": ["Greenhouse Effect", "2. Zero hunger", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "Animal Feed", "01 natural sciences", "7. Clean energy", "12. Responsible consumption", "13. Climate action", "11. Sustainability", "Animals", "0401 agriculture", " forestry", " and fisheries", "Cattle", "Gases", "Ireland", "0105 earth and related environmental sciences"], "contacts": [{"organization": "J. W. Casey, Nicholas M. Holden,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.2134/jeq2005.0121"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Quality", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2134/jeq2005.0121", "name": "item", "description": "10.2134/jeq2005.0121", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2134/jeq2005.0121"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2006-01-01T00:00:00Z"}}, {"id": "10.2134/jeq2006.0547", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-01T16:20:09Z", "type": "Journal Article", "created": "2008-01-05", "description": "Abstract<p>Nitrate (NO3) loss from arable systems to surface and groundwater has attracted considerable attention in recent years in Ireland. Little information exists under Irish conditions, which are wet and temperate, on the effects of winter cover crops and different tillage techniques on NO3 leaching. This study investigated the efficacy of such practices in reducing NO3 leaching from a spring barley (Hordeum vulgare L.) system in the Barrow River valley, southeast Ireland. The study compared the effect of two tillage systems (plow\uffe2\uff80\uff90based tillage and noninversion tillage) and two over\uffe2\uff80\uff90winter alternatives (no vegetative cover and a mustard cover crop) on soil solution NO3 concentrations at 90 cm depth over two winter drainage seasons (2003/04 and 2004/05). Soil samples were taken and analyzed for inorganic N. During both years of the study, the use of a mustard cover crop significantly reduced NO3 losses for the plowed and reduced cultivation treatments. Mean soil solution NO3 concentrations were between 38 and 70% lower when a cover crop was used, and total N load lost over the winter was between 18 and 83% lower. Results from this study highlight the importance of drainage volume and winter temperatures on NO3 concentrations in soil solution and overall N load lost. It is suggested that cover crops will be of particular value in reducing NO3 loss in temperate regions with mild winters, where winter N mineralization is important and high winter temperatures favor a long growing season.</p>", "keywords": ["Crops", " Agricultural", "2. Zero hunger", "Nitrates", "Nitrogen", "Rain", "Water Pollution", "Temperature", "Water", "Agriculture", "Hordeum", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "6. Clean water", "Soil", "13. Climate action", "Soil Pollutants", "0401 agriculture", " forestry", " and fisheries", "Ireland", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.2134/jeq2006.0547"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Quality", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2134/jeq2006.0547", "name": "item", "description": "10.2134/jeq2006.0547", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2134/jeq2006.0547"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2008-01-01T00:00:00Z"}}, {"id": "10.3168/jds.2019-16575", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-01T16:20:41Z", "type": "Journal Article", "created": "2019-08-22", "title": "Using machine learning to estimate herbage production and nutrient uptake on Irish dairy farms", "description": "Nutrient management on grazed grasslands is of critical importance to maintain productivity levels, as grass is the cheapest feed for ruminants and underpins these meat and milk production systems. Many attempts have been made to model the relationships between controllable (crop and soil fertility management) and noncontrollable influencing factors (weather, soil drainage) and nutrient/productivity levels. However, to the best of our knowledge not much research has been performed on modeling the interconnections between the influencing factors on one hand and nutrient uptake/herbage production on the other hand, by using data-driven modeling techniques. Our paper proposes to use predictive clustering trees (PCT) learned for building models on data from dairy farms in the Republic of Ireland. The PCT models show good accuracy in estimating herbage production and nutrient uptake. They are also interpretable and are found to embody knowledge that is in accordance with existing theoretical understanding of the task at hand. Moreover, if we combine more PCT into an ensemble of PCT (random forest of PCT), we can achieve improved accuracy of the estimates. In practical terms, the number of grazings, which is related proportionally with soil drainage class, is one of the most important factors that moderates the herbage production potential and nutrient uptake. Furthermore, we found the nutrient (N, P, and K) uptake and herbage nutrient concentration to be conservative in fields that had medium yield potential (11 t of dry matter per hectare on average), whereas nutrient uptake was more variable and potentially limiting in fields that had higher and lower herbage production. Our models also show that phosphorus is the most limiting nutrient for herbage production across the fields on these Irish dairy farms, followed by nitrogen and potassium.", "keywords": ["2. Zero hunger", "nutrient uptake", "Nutrients", "04 agricultural and veterinary sciences", "15. Life on land", "Poaceae", "Animal Feed", "Diet", "Machine Learning", "herbage production", "Dairying", "Milk", "nutrient uptake", " herbage production", " predictive clustering trees", " random forest", "predictive clustering trees", "Animals", "Lactation", "0401 agriculture", " forestry", " and fisheries", "Cattle", "Female", "Ireland", "random forest"]}, "links": [{"href": "https://doi.org/10.3168/jds.2019-16575"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Dairy%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3168/jds.2019-16575", "name": "item", "description": "10.3168/jds.2019-16575", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3168/jds.2019-16575"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-11-01T00:00:00Z"}}, {"id": "10.5281/zenodo.13945384", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-01T16:22:22Z", "type": "Report", "title": "Evaluation of soil threats and ecosystem service evolution under climate, land use or management changes.", "description": "The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.  Based on an intensive literature review and results from previous experiences in member states a scenario framework was developed (climate, land use, and management changes) and common methodologies (statistical methods, simple and/or more sophisticated models) were identified, used or validated to forecast how selected soil ecosystem services (SES) and soil threats (ST) will change according to climate, land-use and management changes. In contrast to WP5 we focus in WP3/Task 3 on forecasts of changes of various soil indicators on site, regional or national scale, and could rely on soil maps with high resolution that are maintained by several member states. Three countries out of 6 were able to give predictions for changes on the SES \u201cGHG and climate regulation\u201d. Two countries were working on the SES \u201cPrimary biomass production\u201d and could predict changes in \u201cErosion control\u201d on a national scale. \u201cHydrological control\u201d and \u201cEnvironmental pollution control\u201d was predicted in one country in 2 regions. Changes in climate, land management or land use change and their effects on ST could be predicted less often. Three countries could predict the effects ofchanges on \u201cSoil organic carbon loss\u201d and on \u201cSoil compaction\u201d, two countries estimated the loss ofsoil via erosion. Only one country each could predict effects of changes on \u201cSoil nutrient imbalance\u201dand \u201cSoil acidification\u201d and \u201cSoil sealing\u201d. Either no appropriate model or no experience was availablefor the SES \u201cHabitat for biodiversity\u201d and \u201cPest and disease control\u201d and for the ST\u2019s \u201cWaterlogging\u201d,\u201cSoil contamination\u201d, \u201cLoss of diversity\u201d and \u201cSalinization\u201d.", "keywords": ["Estonia", "land use change", "Task 3.3", "soil nutrient imbalance", "salinization", "management change", "D3.4", "soil", "Environmental pollution control", "loss of diversity", "soil compaction", "soil sealing", "Erosion control", "Soil threats", "habitat for biodiversity", "loss of soil", "Primary biomass production", "Czech Republic", "agriculture", "GHG and climate regulation", "Hydrological control", "scenario analysis", "Grant n. 862695", "Soil ecosystem services", "waterlogging", "soil organic carbon loss", "climate change", "SERENA EJPSOIL", "WP3", "Austria", "pest and disease control", "France", "Poland", "soil acidification", "Ireland", "soil contamination"], "contacts": [{"organization": "Kitzler, Barbara", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13945384"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13945384", "name": "item", "description": "10.5281/zenodo.13945384", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13945384"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-17T00:00:00Z"}}, {"id": "10.5281/zenodo.13945383", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-01T16:22:22Z", "type": "Report", "created": "2024-10-22", "title": "Evaluation of soil threats and ecosystem service evolution under climate, land use or management changes.", "description": "The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.  Based on an intensive literature review and results from previous experiences in member states a scenario framework was developed (climate, land use, and management changes) and common methodologies (statistical methods, simple and/or more sophisticated models) were identified, used or validated to forecast how selected soil ecosystem services (SES) and soil threats (ST) will change according to climate, land-use and management changes. In contrast to WP5 we focus in WP3/Task 3 on forecasts of changes of various soil indicators on site, regional or national scale, and could rely on soil maps with high resolution that are maintained by several member states. Three countries out of 6 were able to give predictions for changes on the SES \u201cGHG and climate regulation\u201d. Two countries were working on the SES \u201cPrimary biomass production\u201d and could predict changes in \u201cErosion control\u201d on a national scale. \u201cHydrological control\u201d and \u201cEnvironmental pollution control\u201d was predicted in one country in 2 regions. Changes in climate, land management or land use change and their effects on ST could be predicted less often. Three countries could predict the effects ofchanges on \u201cSoil organic carbon loss\u201d and on \u201cSoil compaction\u201d, two countries estimated the loss ofsoil via erosion. Only one country each could predict effects of changes on \u201cSoil nutrient imbalance\u201dand \u201cSoil acidification\u201d and \u201cSoil sealing\u201d. Either no appropriate model or no experience was availablefor the SES \u201cHabitat for biodiversity\u201d and \u201cPest and disease control\u201d and for the ST\u2019s \u201cWaterlogging\u201d,\u201cSoil contamination\u201d, \u201cLoss of diversity\u201d and \u201cSalinization\u201d.", "keywords": ["Estonia", "land use change", "Task 3.3", "soil nutrient imbalance", "salinization", "management change", "D3.4", "soil", "Environmental pollution control", "loss of diversity", "soil compaction", "soil sealing", "Erosion control", "Soil threats", "habitat for biodiversity", "loss of soil", "Primary biomass production", "Czech Republic", "agriculture", "GHG and climate regulation", "Hydrological control", "scenario analysis", "Grant n. 862695", "Soil ecosystem services", "waterlogging", "soil organic carbon loss", "climate change", "SERENA EJPSOIL", "WP3", "Austria", "pest and disease control", "France", "Poland", "soil acidification", "Ireland", "soil contamination"], "contacts": [{"organization": "Kitzler, Barbara", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13945383"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13945383", "name": "item", "description": "10.5281/zenodo.13945383", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13945383"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-17T00:00:00Z"}}, {"id": "10.5281/zenodo.13970638", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-01T16:22:23Z", "type": "Dataset", "title": "SERENA EJPSOIL IE SOC Loss SOC", "description": "Open AccessDisclaimer:  The data are derived from the calculation of indicators based on a standard methodology established as part of the EJP Soil SERENA programme. Please keep in mind that:  - It is the result of a modelling exercise and does not necessarily reflect reality.  - Despite the efforts made to provide reliable data, the results may contain inconsistencies, depending in particular on the raw data available and level of accuracy of the techniques chosen and their prior knowledge.  - It is necessary to consider how the results have been obtained in order to decide on their relevance in relation to the intended purpose of reuse.  - These results are interesting from a scientific point of view, but their use for environmental management and policy issues should be done keeping the previous aspects in mind and complementing when necessary the provided results with the best available data.  ==> Finally, it is the responsibility of the users of this information to decide whether it is appropriate to use these data and whether the data meet their needs. The authors of this resource can in no way be held responsible for the results obtained from the use of this data.", "keywords": ["EJP Soil", "Soil organic carbon", "Soil based ecosystem service", "SERENA", "Ireland"], "contacts": [{"organization": "Fahy, Alan, Shahrokh, Vajihe, Buttafuoco, Gabriele, Bondi, Giulia, O'Sullivan, Lilian,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13970638"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13970638", "name": "item", "description": "10.5281/zenodo.13970638", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13970638"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-22T00:00:00Z"}}, {"id": "10.5281/zenodo.13987916", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-01T16:22:24Z", "type": "Dataset", "title": "SERENA EJPSOIL IE MEATH GHG NEP", "description": "Open AccessThe data are derived from the calculation of indicators based on a standard methodology established as\u00a0part of the EJP Soil SERENA\u00a0programme. Please keep in mind that:       It is the result of a modelling exercise and does not necessarily reflect reality.     Despite the efforts made to provide reliable data, the results\u00a0may contain inconsistencies,\u00a0depending\u00a0in particular on\u00a0the raw data\u00a0available\u00a0and level of accuracy of the techniques chosen\u00a0and\u00a0their prior knowledge\u00a0.     It is necessary to consider how the results have been obtained\u00a0in order to\u00a0decide on their\u00a0relevance\u00a0in relation to the intended\u00a0purpose\u00a0of reuse.     These results are interesting from a scientific point of view, but their use\u00a0for environmental\u00a0management and policy issues should be done keeping the previous aspects in mind and\u00a0complementing when\u00a0necessary\u00a0the provided results with the best available data.      ==> Finally, it is the responsibility of the users of this information to decide whether it is appropriate to use these data and whether the data meet their needs. The authors of this resource can in no way be held responsible for the results obtained from the use of this data.", "keywords": ["EJP Soil", " Serena", " Greenhouse gas", " soil based ecosystem service", " NEP", " Ireland"], "contacts": [{"organization": "Fahy, Alan, Bondi, Giulia, O'Sullivan, Lilian,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13987916"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13987916", "name": "item", "description": "10.5281/zenodo.13987916", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13987916"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-24T00:00:00Z"}}, {"id": "10.5281/zenodo.13992532", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-01T16:22:24Z", "type": "Other", "title": "SERENA EJPSOIL IE WEXFORD SOIL SEALING", "description": "Open AccessThe internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.  We conducted an analysis using the Level 1 version of the soil-sealing cookbook on Sentinel 2 tiles 29UPU and 29UPT, with a reference year of 2019. For this analysis, we used National Orthophotos and Google Satellite images to confirm/deny potential changes in soil sealing identified by cookbook methodology. The 2018 Copernicus Land Monitoring Service High Resolution Layer Imperviousness served as the baseline for soil sealing.", "keywords": ["EJP Soil", " SERENA", " Soil sealing", " Soil based ecosystem service", " Ireland"], "contacts": [{"organization": "Fahy, Alan, Bondi, Giulia, O'Sullivan, Lilian,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13992532"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13992532", "name": "item", "description": "10.5281/zenodo.13992532", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13992532"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-25T00:00:00Z"}}, {"id": "11019/1960", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-01T16:24:43Z", "type": "Journal Article", "created": "2019-08-22", "title": "Using machine learning to estimate herbage production and nutrient uptake on Irish dairy farms", "description": "Nutrient management on grazed grasslands is of critical importance to maintain productivity levels, as grass is the cheapest feed for ruminants and underpins these meat and milk production systems. Many attempts have been made to model the relationships between controllable (crop and soil fertility management) and noncontrollable influencing factors (weather, soil drainage) and nutrient/productivity levels. However, to the best of our knowledge not much research has been performed on modeling the interconnections between the influencing factors on one hand and nutrient uptake/herbage production on the other hand, by using data-driven modeling techniques. Our paper proposes to use predictive clustering trees (PCT) learned for building models on data from dairy farms in the Republic of Ireland. The PCT models show good accuracy in estimating herbage production and nutrient uptake. They are also interpretable and are found to embody knowledge that is in accordance with existing theoretical understanding of the task at hand. Moreover, if we combine more PCT into an ensemble of PCT (random forest of PCT), we can achieve improved accuracy of the estimates. In practical terms, the number of grazings, which is related proportionally with soil drainage class, is one of the most important factors that moderates the herbage production potential and nutrient uptake. Furthermore, we found the nutrient (N, P, and K) uptake and herbage nutrient concentration to be conservative in fields that had medium yield potential (11 t of dry matter per hectare on average), whereas nutrient uptake was more variable and potentially limiting in fields that had higher and lower herbage production. Our models also show that phosphorus is the most limiting nutrient for herbage production across the fields on these Irish dairy farms, followed by nitrogen and potassium.", "keywords": ["2. Zero hunger", "nutrient uptake", "Nutrients", "04 agricultural and veterinary sciences", "15. Life on land", "Poaceae", "Animal Feed", "Diet", "Machine Learning", "herbage production", "Dairying", "Milk", "predictive clustering trees", "Animals", "Lactation", "0401 agriculture", " forestry", " and fisheries", "Cattle", "Female", "Ireland", "random forest"]}, "links": [{"href": "https://doi.org/11019/1960"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Dairy%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11019/1960", "name": "item", "description": "11019/1960", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11019/1960"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-11-01T00:00:00Z"}}, {"id": "111731d9-b65d-4211-a754-d1a16ccb49ba", "type": "Feature", "geometry": null, "properties": {"updated": "2025-09-20T08:25:15Z", "type": "Dataset", "language": "en", "title": "National Ecosystem and Ecosystem Services Map - Ecosystem Service Stock Map: Soil Carbon", "description": "This dataset contains a raster file showing the contribution of land to the regulation of greenhouse gases (carbon) through carbon sequestration associated with the soil.  This dataset is part of a dataset series that establishes an ecosystem service maps (national scale) for a set of services prioritised through stakeholder consultation and any intermediate layers created by Environment Systems Ltd in the cause of the project. The individual dataset resources in the datasets series are to be considered in conjunction with the project report: https://www.npws.ie/research-projects/ecosystems-services-mapping-and-assessment  The project provides a National Ecosystem and Ecosystem Services (ES) map for a suite of prioritised services to assist implementation of MAES (Mapping and Assessment of Ecosystems and their services) in Ireland.  This involves stakeholder consultation for identification of services to be mapped, the development of a list of indicators and proxies for mapping, as well as an assessment of limitations to ES mapping on differing scales (Local, Catchment, Region, National, EU) based on data availability. Reporting on data gaps forms part of the project outputs.  The project relied on the usage of pre-existing data, which was also utilised to create intermediate data layers to aid in ES mapping. For a full list of the data used throughout the project workings, please refer to the project report.", "formats": [{"name": "HTML"}], "keywords": ["biota", "ecosystem", "ecosystem-services", "environment", "geoscientificinformation", "habitat-protection", "habitats-and-biotopes", "heritage", "ie", "ireland", "landscape", "national-biodiversity-plan", "national-parks-and-wildlife-service", "npws", "soil"], "contacts": [{"organization": "Department of Housing, Local Government and Heritage", "roles": ["creator"]}, {"organization": "https://data.gov.ie/organization/department-of-housing-planning-community-and-local-government", "roles": ["publisher"]}]}, "links": [{"href": "https://dahg.maps.arcgis.com/apps/MapSeries/index.html?appid=cb5040a4a19645b6b424bed940c54fff"}, {"href": "https://www.npws.ie/sites/default/files/general/MAES15_ESmap_SoilCarbon_Final.zip"}, {"href": "http://data.europa.eu/88u/dataset/111731d9-b65d-4211-a754-d1a16ccb49ba~~1"}, {"rel": "self", "type": "application/geo+json", "title": "111731d9-b65d-4211-a754-d1a16ccb49ba", "name": "item", "description": "111731d9-b65d-4211-a754-d1a16ccb49ba", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/111731d9-b65d-4211-a754-d1a16ccb49ba"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "4b970e59-fbb7-4f9b-8155-ceebabd2d971", "type": "Feature", "geometry": null, "properties": {"updated": "2024-09-24T14:39:18", "type": "Dataset", "language": "en", "title": "Landslide susceptibility Classification 1:50,000 Ireland (ROI) ITM", "description": "A landslide is the movement of material down a Slope. This includes rock, earth, mud and Peat. Landslides in Ireland mainly occur on steep mountain slopes.  A landslide susceptibility map shows areas where a landslide could occur, how likely it will occur and what Causes them. The likelihood is measured from low to high.  The map is created using a method called the Unique Condition Unit (UCU).  A unique condition unit is an area with a set of ground types. It tells us what the soil type is, what the Slope is (angle of the ground) and where water flows.  When many landslides occur in a unit, the map will show high landslide susceptibility.  The landslide susceptibility classification map is to the scale 1:50,000 (1\u00a0cm on the map relates to a distance of 500\u00a0m) It is a vector Dataset. Vector data portray the world using points, lines, and polygons. A polygon represents the area.  The landslide susceptibility data is shown from polygons. Each polygon gives information on the unit, its soil type, the Slope of the ground, its description and the description of landslide susceptibility.", "formats": [{"name": "DATA VIEWER"}], "keywords": ["earth-science", "environment", "fossil-fuel", "geology", "geomorphic-process", "geoscientificinformation", "ie", "ireland", "landslide", "lithosphere", "peat", "pedosphere", "science", "soil", "soil-degradation"], "contacts": [{"organization": "Geological Survey of Ireland", "roles": ["creator"]}, {"organization": "https://data.gov.ie/organization/geological-survey-of-ireland", "roles": ["publisher"]}]}, "links": [{"href": "https://dcenr.maps.arcgis.com/apps/webappviewer/index.html?id=b68cf1e4a9044a5981f950e9b9c5625c"}, {"href": "https://gsi.geodata.gov.ie/downloads/Geohazards/Data/IE_GSI_Landslide_Data_IE32_ITM.zip"}, {"href": "https://gsi.geodata.gov.ie/downloads/Geohazards/Reports/IE_GSI_Landslide_Susceptibility_Mapping_Summary.pdf"}, {"href": "https://gsi.geodata.gov.ie/server/rest/services/Geohazards/IE_GSI_Landslide_Susceptibility_Classification_50K_IE26_ITM/MapServer"}, {"href": "https://gsi.geodata.gov.ie/server/rest/services/Geohazards/IE_GSI_Landslide_Susceptibility_Classification_50K_IE26_ITM/MapServer?f=pjson"}, {"href": "https://gsi.geodata.gov.ie/server/services/Geohazards/IE_GSI_Landslide_Susceptibility_Classification_50K_IE26_ITM/MapServer/WMSServer?request=GetCapabilities&service=WMS"}, {"href": "http://data.europa.eu/88u/dataset/4b970e59-fbb7-4f9b-8155-ceebabd2d971"}, {"rel": "self", "type": "application/geo+json", "title": "4b970e59-fbb7-4f9b-8155-ceebabd2d971", "name": "item", "description": "4b970e59-fbb7-4f9b-8155-ceebabd2d971", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/4b970e59-fbb7-4f9b-8155-ceebabd2d971"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "50|od______2659::0395267d7be317e5e01fc3de076959c4", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-01T16:26:36Z", "type": "Dataset", "title": "SERENA EJPSOIL IE SOC Loss SOC", "description": "The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.", "keywords": ["EJP Soil", "Soil organic carbon", "Soil based ecosystem service", "SERENA", "Ireland"], "contacts": [{"organization": "Fahy, Alan, Shahrokh, Vajihe, Buttafuoco, Gabriele, Bondi, Giulia, O'Sullivan, Lilian,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/50|od______2659::0395267d7be317e5e01fc3de076959c4"}, {"rel": "self", "type": "application/geo+json", "title": "50|od______2659::0395267d7be317e5e01fc3de076959c4", "name": "item", "description": "50|od______2659::0395267d7be317e5e01fc3de076959c4", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/50|od______2659::0395267d7be317e5e01fc3de076959c4"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-22T00:00:00Z"}}, {"id": "69390796-042f-49e8-a33b-7c37c54b9137", "type": "Feature", "geometry": null, "properties": {"updated": "2024-11-05T12:39:12", "type": "Dataset", "language": "en", "title": "Coastal Soil Susceptibility", "description": "This dataset was created to ascertain the level of vulnerability to erosion processes along 7 coastal local authorities. . The dataset classifies the coast line into areas at High, Medium or Low risk based on the subsoil type along the coast at that point. The data was extracted from the EPA/Teagasc subsoils dataset, with each subsoil type within this dataset classified with either a \u2018High\u2019, \u2018Moderate\u2019 or \u2018Low\u2019 ranking, depending on their susceptibility to erosion.", "formats": [{"name": "CSV"}], "keywords": ["coastal-erosion", "coastal-susceptibility", "coastal-zone-planning", "environment", "erosion", "geoscientificinformation", "ie", "ireland", "marine", "marine-environments", "oceans", "soil", "soil-erosion"], "contacts": [{"organization": "Heritage Council", "roles": ["creator"]}, {"organization": "https://data.gov.ie/organization/heritage-council", "roles": ["publisher"]}]}, "links": [{"href": "http://www.heritagecouncil.ie/content/files/Coastal%20Soil%20Susceptibility%20Shapefiles.zip"}, {"href": "http://www.heritagecouncil.ie/content/files/Coastal-Soil-Susceptibility.csv"}, {"href": "http://www.heritagecouncil.ie/content/files/Coastal-Soil-Susceptibility.xlsx"}, {"href": "http://www.heritagecouncil.ie/content/files/Coastal_Soil_Susceptibility.pdf"}, {"href": "https://heritagemaps.ie/"}, {"href": "http://data.europa.eu/88u/dataset/69390796-042f-49e8-a33b-7c37c54b9137"}, {"rel": "self", "type": "application/geo+json", "title": "69390796-042f-49e8-a33b-7c37c54b9137", "name": "item", "description": "69390796-042f-49e8-a33b-7c37c54b9137", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/69390796-042f-49e8-a33b-7c37c54b9137"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "7520bfe1-d548-4ffb-bdd8-18cc534df855", "type": "Feature", "geometry": null, "properties": {"updated": "2024-09-25T14:47:06", "type": "Dataset", "language": "en", "title": "Tellus Geochemistry \u2014 topsoil", "description": "The latest topsoils data from the Tellus project, managed by the Geological Survey Ireland.  The topsoil (c.5\u201320 cm deep) samples were analysed for: Analytical Method: ICP(-OES/-MS) following aqua regia digestion; soil loss-on-ignition at 450\u00a0\u00b0C The survey was conducted on foot; samples were collected approx. every 4 sq km from. For more information please visit tellus.ie.  The following elements were analysed: Aluminium, Antimony, Arsenic, Barium, Beryllium, Bismuth, Cadmium, caesium, Calcium, Cerium, Chromium, Cobalt, Copper, Gallium, Germanium, Hafnium, indium, Iron, Lanthanum, Lead, Lithium, Loss-on-ignition, Lutetium, Magnesium, Manganese, Mercury, Molybdenum, Nickel, Niobium, pH, Phosphorus, Potassium, Rubidium, scandium, Selenium, Silver, Sodium, Strontium, Sulphur, Tantalum, Tellurium, Terbium, Thallium, Thorium, Tin, Titanium, Tungsten, Uranium, vanadium, Ytterbium, Yttrium, Zinc, Zinc, Zirconium (Al, B, Ba, Ca, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, P, S, S, Sr, Ti, V, Zn, Zr, Ag, Be, Be, Bi, Cd, Ce, Co, Cs, Ga, Ge, Hf, In, La, Lu, P, Mo, Mo, Pb, Rb, Sb, Sb, Sb, Sn, Sn, Tb, Te, Th, Tl, U, W, Yb) The current coverage includes:  Tellus Border survey block (2011-2013, Co Donegal, Sligo, Leitrim, Cavan, Monaghan, Louth)  Some elements have been merged with topsoil data from Northern Ireland conducted in the mid ninties and Noughties.", "formats": 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The purpose of this study was to investigate the impacts of agricultural intensification in Europe, and to understand its environmental impact. Metal concentrations in soils were used from two consecutive Europe-wide geochemical surveys, sampled in 1998 (FOREGS survey) and 2009 (GEMAS survey). For land use, the 2010 Eurostat data were used. \n\nThe metals included in this data set are cadmium (Cd), copper (Cu), lead (Pb) and zinc (Zn). The results on the fate of Nitrogen (N) and Phosphorus (P) are included in a separate dataset. Cu and Zn are minor nutrients but at high inputs, they may cause adverse impacts on soil biodiversity, whereas Cd and Pb are toxic metals that may lead to soil degradation, by both affecting soil biodiversity and food quality. Metal budgets based on spatially explicit input and output data were calculated using the INTEGRATOR model; approximately 40,000 so-called NCUs as unique combinations of soil type, administrative region, slope class and altitude class were used. Available critical limits for food, water and soil organisms, from different existing regulations and studies, were converted to soil property-dependent critical metal concentrations (soil-based quality standards), which were then used to calculate critical metal inputs. \n\nThe results allow for the first time to identifying spatial hot spots for critical environmental impact of soil pollution for the four most abundant heavy metals. It thus informs policy processes important for planning and guiding sustainable agriculture and soil management. The work is methodologically novel, as it applies endpoint risk to thresholds in soils, and thus guides future impact studies. Updates with more recent land use and soil data are now possible.\n\nThe description of the included model results and the reference report is provided under \"lineage\". The data set is provided as SHP and also in a GDB, the latter including as well the N and P concentrations. 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The purpose of this study was to investigate the impacts of agricultural intensification in Europe, and to understand its environmental impact.", "formats": [{"name": "SHP"}, {"name": "EEA:FOLDERPATH"}, {"name": "WWW:URL"}, {"name": "ESRI:REST"}, {"name": "OGC:WMS"}], "keywords": ["Soil", "Land use", "nitrogen", "ammonia", "nutrient", "concentration (value)", "soil pollution", "phosphorus", "ecosystem degradation", "land use", "agricultural land", "soil degradation", "agriculture", "environmental pressure", "soil", "United Kingdom", "Ireland", "Portugal", "Lithuania", "Italy", "France", "Greece", "Austria", "Denmark", "Czechia", "Poland", "Finland", "Slovenia", "Hungary", "Spain", "Belgium", "Netherlands", "Slovakia", "Luxembourg", "Sweden", "Latvia", "Estonia", "Bulgaria", "Romania", "Germany", "European", "Soil", "Land use"], "contacts": [{"name": null, "organization": "European Environment Agency", "position": null, "roles": ["pointOfContact"], "phones": [{"value": null}], "emails": [{"value": "sdi@eea.europa.eu"}], "addresses": [{"deliveryPoint": ["Kongens Nytorv 6"], "city": "Copenhagen", "administrativeArea": "K", "postalCode": "1050", "country": "Denmark"}], "links": [{"href": {"url": "http://www.eea.europa.eu", "protocol": "WWW:LINK-1.0-http--link", "protocol_url": "", "name": "European Environment Agency public website", "name_url": "", "description": null, "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": "information"}}]}, {"name": null, "organization": "European Environment Agency", "position": null, "roles": ["custodian"], "phones": [{"value": null}], "emails": [{"value": "sdi@eea.europa.eu"}], "addresses": [{"deliveryPoint": ["Kongens Nytorv 6"], "city": "Copenhagen", "administrativeArea": "K", "postalCode": "1050", "country": "Denmark"}], "links": [{"href": null}]}], "distancevalue": "1", "distanceuom": "km", "edition": "01.00"}, "links": [{"href": "https://sdi.eea.europa.eu/webdav/datastore/public/eea_v_3035_1_km_n-p-agri-soil_p_2008-2019_v01_r00/SHP/", "protocol": "EEA:FOLDERPATH", "rel": "download"}, {"href": "https://sdi.eea.europa.eu/webdav/datastore/public/eea_v_3035_1_km_n-p-agri-soil_p_2008-2019_v01_r00/GDB/", "protocol": "EEA:FOLDERPATH", "rel": "download"}, {"href": "https://sdi.eea.europa.eu/data/044814bf-0a21-41f7-83bd-596f3afb364d", "name": "Direct download", "protocol": "WWW:URL", "rel": "download"}, {"href": "https://land.discomap.eea.europa.eu/arcgis/rest/services/Agriculture/concentrations_of_nitrogen_phosphorus_in_EU_agricultural_soils/MapServer", "protocol": "ESRI:REST", "rel": "information"}, {"href": "https://land.discomap.eea.europa.eu/arcgis/services/Agriculture/concentrations_of_nitrogen_phosphorus_in_EU_agricultural_soils/MapServer/WMSServer?request=GetCapabilities&service=WMS", "protocol": "OGC:WMS", "rel": "information"}, {"href": "https://sdi.eea.europa.eu/public/catalogue-graphic-overview/044814bf-0a21-41f7-83bd-596f3afb364d.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "044814bf-0a21-41f7-83bd-596f3afb364d", "name": "item", "description": "044814bf-0a21-41f7-83bd-596f3afb364d", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/044814bf-0a21-41f7-83bd-596f3afb364d"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["2008-01-01T00:00:00Z", "2019-12-31T00:00:00Z"]}}, {"id": "a3fb227d-3666-400b-9152-58f82acb525b", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-26.0, 32.25], [-26.0, 72.0], [45.7, 72.0], [45.7, 32.25], [-26.0, 32.25]]]}, "properties": {"themes": [{"concepts": [{"id": "environment"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Statistical units"}, {"id": "Land cover"}, {"id": "Land use"}], "scheme": "GEMET - 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Copyright holder: European Environment Agency (EEA).", "updated": "2025-01-09T13:24:20.413356Z", "type": "Dataset", "created": "2016-11-30", "language": "eng", "title": "Grassland intensification by management practices in 2010, Nov. 2016", "description": "The dataset shows the percentage of grasslands under high pressure from management practices in 2010. The area percentage is calculated in relation to the total grassland area within NUTS3 regions (NUTS2 for Germany).\nThe management pressure on grassland was calculated by combining information of nitrogen input from the Farm Structure Survey (FSS), the Corine Land Use/Land Cover dataset and other environmental characteristics such as topographic conditions, soil and climate conditions (etc).\nThis dataset is part of the condition/pressures assessments done for agroecosystems under ETC/SIA actions for MAES (Mapping and Assessment of Ecosystem Services).", "formats": [{"name": "SHP"}, {"name": "EEA:FILEPATH"}, {"name": "WWW:URL"}, {"name": "ESRI:REST"}, {"name": "OGC:WMS"}], "keywords": ["Statistical units", "Land cover", "Land use", "land use", "nutrient", "state", "land cover", "grassland", "pressure", "environmental pressure", "Estonia", "Slovenia", "Slovakia", "Czechia", "Bulgaria", "Austria", "Belgium", "Denmark", "Germany", "France", "Ireland", "Netherlands", "Poland", "Luxembourg", "United Kingdom", "Hungary", "Italy", "Portugal", "Finland", "Latvia", "Spain", "Romania", "Lithuania", "Sweden", "Land use", "Agriculture and food", "Sustainability challenges"], "contacts": [{"name": null, "organization": "European Environment Agency", "position": null, "roles": ["pointOfContact"], "phones": [{"value": null}], "emails": [{"value": "sdi@eea.europa.eu"}], "addresses": [{"deliveryPoint": ["Kongens Nytorv 6"], "city": "Copenhagen", "administrativeArea": "K", "postalCode": "1050", "country": "Denmark"}], "links": [{"href": {"url": "http://www.eea.europa.eu", "protocol": "WWW:LINK-1.0-http--link", "protocol_url": "", "name": "European Environment Agency public website", "name_url": "", "description": null, "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": "information"}}]}, {"name": null, "organization": "European Environment Agency", "position": "Environmental data centre for land use", "roles": ["custodian"], "phones": [{"value": null}], "emails": [{"value": "sdi@eea.europa.eu"}], "addresses": [{"deliveryPoint": ["Kongens Nytorv 6"], "city": "Copenhagen", "administrativeArea": "K", "postalCode": "1050", "country": "Denmark"}], "links": [{"href": null}]}], "denominator": "1000000"}, "links": [{"href": "https://sdi.eea.europa.eu/webdav/datastore/public/eea_v_3035_1_mio_grass-intens-management_p_2010_v01_r00/", "protocol": "EEA:FILEPATH", "rel": "download"}, {"href": "https://sdi.eea.europa.eu/data/a3fb227d-3666-400b-9152-58f82acb525b", "name": "Direct download", "protocol": "WWW:URL", "rel": "download"}, {"href": "https://land.discomap.eea.europa.eu/arcgis/rest/services/Agriculture/Grassland_intensification_2010/MapServer", "protocol": "ESRI:REST", "rel": "information"}, {"href": "https://land.discomap.eea.europa.eu/arcgis/services/Agriculture/Grassland_intensification_2010/MapServer/WMSServer?request=GetCapabilities&service=WMS", "name": "0", "description": "Percentage of grasslands per administrative unit under high pressure from management practices.", "protocol": "OGC:WMS", "rel": "information"}, {"href": "https://sdi.eea.europa.eu/public/catalogue-graphic-overview/a3fb227d-3666-400b-9152-58f82acb525b.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "a3fb227d-3666-400b-9152-58f82acb525b", "name": "item", "description": "a3fb227d-3666-400b-9152-58f82acb525b", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/a3fb227d-3666-400b-9152-58f82acb525b"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["2010-01-01T00:00:00Z", "2010-12-31T00:00:00Z"]}}, {"id": "7067f539-e0e6-4be5-9f97-471362b8466c", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-26.0, 32.25], [-26.0, 72.0], [45.7, 72.0], [45.7, 32.25], [-26.0, 32.25]]]}, "properties": {"themes": [{"concepts": [{"id": "environment"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Land cover"}, {"id": "Land use"}, {"id": "Statistical units"}], "scheme": "GEMET - 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Copyright holder: European Environment Agency (EEA).", "updated": "2025-01-09T13:23:05.616382Z", "type": "Dataset", "created": "2016-11-30", "language": "eng", "title": "Cropland intensification by management practices in 2010, Nov. 2016", "description": "The dataset shows the percentage of croplands under high pressure from management practices in 2010. The area percentage is calculated in relation to the total cropland area within NUTS3 regions (NUTS2 for Germany).\nThe management pressure on croplands was calculated by combining information of nitrogen input from the Farm Structure Survey (FSS), the Corine Land Use/Land Cover dataset and other environmental characteristics such as topographic conditions, soil and climate conditions (etc).\nThis dataset is part of the condition/pressures assessments done for agroecosystems under ETC/SIA actions for MAES (Mapping and Assessment of Ecosystem Services).", "formats": [{"name": "SHP"}, {"name": "EEA:FILEPATH"}, {"name": "WWW:URL"}, {"name": "ESRI:REST"}, {"name": "OGC:WMS"}], "keywords": ["Land cover", "Land use", "Statistical units", "pressure", "land use", "land cover", "state", "Netherlands", "Austria", "Belgium", "Bulgaria", "Czechia", "Germany", "Spain", "Denmark", "France", "Estonia", "Finland", "Hungary", "Italy", "Ireland", "Lithuania", "Latvia", "Poland", "Portugal", "United Kingdom", "Sweden", "Slovakia", "Luxembourg", "Romania", "Slovenia", "Agriculture and food", "Land use"], "contacts": [{"name": null, "organization": "European Environment Agency", "position": null, "roles": ["pointOfContact"], "phones": [{"value": null}], "emails": [{"value": "sdi@eea.europa.eu"}], "addresses": [{"deliveryPoint": ["Kongens Nytorv 6"], "city": "Copenhagen", "administrativeArea": "K", "postalCode": "1050", "country": "Denmark"}], "links": [{"href": {"url": "http://www.eea.europa.eu", "protocol": "WWW:LINK-1.0-http--link", "protocol_url": "", "name": "European Environment Agency public website", "name_url": "", "description": null, "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": "information"}}]}, {"name": null, "organization": "European Environment Agency", "position": "Environmental data centre for land use", "roles": ["custodian"], "phones": [{"value": null}], "emails": [{"value": "sdi@eea.europa.eu"}], "addresses": [{"deliveryPoint": ["Kongens Nytorv 6"], "city": "Copenhagen", "administrativeArea": "K", "postalCode": "1050", "country": "Denmark"}], "links": [{"href": null}]}], "denominator": "1000000"}, "links": [{"href": "https://sdi.eea.europa.eu/webdav/datastore/public/eea_v_3035_1_mio_crop-intens-management_p_2010_v01_r00/", "protocol": "EEA:FILEPATH", "rel": "download"}, {"href": "https://sdi.eea.europa.eu/data/7067f539-e0e6-4be5-9f97-471362b8466c", "name": "Direct download", "protocol": "WWW:URL", "rel": "download"}, {"href": "https://land.discomap.eea.europa.eu/arcgis/rest/services/Agriculture/Cropland_intensification_2010/MapServer", "protocol": "ESRI:REST", "rel": null}, {"href": "https://land.discomap.eea.europa.eu/arcgis/services/Agriculture/Cropland_intensification_2010/MapServer/WMSServer?request=GetCapabilities&service=WMS", "name": "0", "description": "Percentage of croplands per administrative unit under high pressure from management practices.", "protocol": "OGC:WMS", "rel": 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[-24.71, 36.01]]]}, "properties": {"themes": [{"concepts": [{"id": "environment"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Atmospheric conditions"}, {"id": "Meteorological geographical features"}], "scheme": "http://inspire.ec.europa.eu/theme"}, {"concepts": [{"id": "climate"}, {"id": "climate change impact"}, {"id": "urban environment, urban stress"}, {"id": "climate change adaptation"}, {"id": "urban area"}], "scheme": "GEMET"}, {"concepts": [{"id": "Norway"}, {"id": "Finland"}, {"id": "Germany"}, {"id": "Lithuania"}, {"id": "Spain"}, {"id": "Austria"}, {"id": "Croatia"}, {"id": "Belgium"}, {"id": "Ireland"}, {"id": "Romania"}, {"id": "Albania"}, {"id": "Switzerland"}, {"id": "France"}, {"id": "Italy"}, {"id": "Montenegro"}, {"id": "Poland"}, {"id": "Denmark"}, {"id": "Serbia"}, {"id": "United Kingdom"}, {"id": "Portugal"}, {"id": "Luxembourg"}, {"id": "Netherlands"}, {"id": "Slovenia"}, {"id": "North Macedonia"}, {"id": "Sweden"}, {"id": "Bosnia and Herzegovina"}, {"id": "Slovakia"}, {"id": "Hungary"}, {"id": "Czechia"}, {"id": "Iceland"}, {"id": "Latvia"}, {"id": "Bulgaria"}, {"id": "Greece"}, {"id": "Estonia"}], "scheme": "Continents, countries, sea regions of the world."}, {"concepts": [{"id": "European"}], "scheme": "http://inspire.ec.europa.eu/metadata-codelist/SpatialScope"}, {"concepts": [{"id": "Climate adaptation"}], "scheme": "https://www.eea.europa.eu/themes"}], "updated": "2021-11-10T08:13:45.046Z", "type": "Dataset", "created": "2019-07-09T00:00:00", "language": "eng", "title": "Urban Heat Island (UHI) intensity (90th percentile), Jan. 2020", "description": "This vector dataset shows the Urban Heat Island (UHI) intensity (in degrees Celsius \u00b0C) for 100 European cities, based on their elevation above sea level, land use, soil sealing, vegetation index and anthropogenic heat flux. The Urban Heat Island intensity exacerbates high temperatures in cities and thus may pose additional risks to human thermal comfort and health.\nThe UHI intensity is represented by spatial P90 (90th percentile) urban heat island intensity of a given city (\"P90\" field in the dataset). This indicator is calculated by subtracting the rural (non-water) spatial P10 (10th percentile) temperature value from the average, height-corrected (to exclude terrain effects), air temperature map. This indicator represents the specific exposure of single cities and due to the height correction will be comparable across Europe.\nThe dataset has been created by VITO within the Copernicus Health contract for C3S and is based on UrbClim model (De Ridder et al. 2015). The 100 European cities for the urban simulations were selected based on user requirements within the health community.", "formats": [{"name": "SHP"}, {"name": "EEA:FOLDERPATH"}, {"name": "WWW:LINK-1.0-http--link"}, {"name": "WWW:URL"}, {"name": "OGC:WMS"}, {"name": "ESRI:REST"}], "keywords": ["Atmospheric conditions", "Meteorological geographical features", "climate", "climate change impact", "urban environment", " urban stress", "climate change adaptation", "urban area", "Norway", "Finland", "Germany", "Lithuania", "Spain", "Austria", "Croatia", "Belgium", "Ireland", "Romania", "Albania", "Switzerland", "France", "Italy", "Montenegro", "Poland", "Denmark", "Serbia", "United Kingdom", "Portugal", "Luxembourg", "Netherlands", "Slovenia", "North Macedonia", "Sweden", "Bosnia and Herzegovina", "Slovakia", "Hungary", "Czechia", "Iceland", "Latvia", "Bulgaria", "Greece", "Estonia", "European", "Climate adaptation"], "contacts": [{"name": null, "organization": "European Environment Agency", "position": null, "roles": ["custodian"], "phones": [{"value": null}], "emails": [{"value": "sdi@eea.europa.eu"}], "addresses": [{"deliveryPoint": ["Kongens Nytorv 6"], "city": "Copenhagen", "administrativeArea": "K", "postalCode": "1050", "country": "Denmark"}], "links": [{"href": null}]}], "denominator": "100000", "edition": "01.00"}, "links": [{"href": "https://sdi.eea.europa.eu/webdav/datastore/public/eea_v_4326_100_k_uhi-intensity_p_2008-2017_v01_r00/", "protocol": "EEA:FOLDERPATH", "rel": "download"}, {"href": "https://climate-adapt.eea.europa.eu/en/knowledge/tools/urban-adaptation", "protocol": "WWW:LINK-1.0-http--link", "rel": "download"}, {"href": "https://sdi.eea.europa.eu/data/8b6a3182-0889-4109-ad22-a021e3126b60", "name": "Direct download", "protocol": "WWW:URL", "rel": "download"}, {"href": "https://climate.discomap.eea.europa.eu/arcgis/services/UAMV/Urban_Heat_Island_Intensity/MapServer/WMSServer?request=GetCapabilities&service=WMS", "protocol": "OGC:WMS", "rel": "information"}, {"href": "https://climate.discomap.eea.europa.eu/arcgis/rest/services/UAMV/Urban_Heat_Island_Intensity/MapServer", "protocol": "ESRI:REST", "rel": "information"}, {"href": "https://sdi.eea.europa.eu/public/catalogue-graphic-overview/8b6a3182-0889-4109-ad22-a021e3126b60.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "8b6a3182-0889-4109-ad22-a021e3126b60", "name": "item", "description": "8b6a3182-0889-4109-ad22-a021e3126b60", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/8b6a3182-0889-4109-ad22-a021e3126b60"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["2008-01-01T00:00:00Z", "2017-12-31T00:00:00Z"]}}, {"id": "fd3c8796-d6e7-4135-aafa-92c97a02454a", "type": "Feature", "geometry": null, "properties": {"updated": "2024-02-26T01:54:37", "type": "Dataset", "language": "en", "title": "Identification and mapping of heavy metal pollution in soils of a sports ground in Galway City", "description": "Heavy metals in urban soils continue to attract attention because of their potential long-term effects on human health. During a previous investigation of urban soils in Galway City, Ireland, a pollution hotspot of Pb, Cu, Zn and As was identified in the sports ground of South Park in the Claddagh. The sports ground was formerly a rubbish dumping site for both municipal and industrial wastes. In the present study, a portable X-ray fluorescence (PXRF) analyser was used to obtain rapid in-situ elemental analyses of the topsoil (depth: about 5\u201310 cm) at 200 locations on a 20 \u00b7 20-m grid in South Park. Extremely high values of the pollutants were found, with maximum values of Pb, Zn, Cu and As of 10,297, 24,716, 2224 and 744 mg/kg soil, respectively. High values occur particularly where the topsoil cover is thin, whereas lower values were found in areas where imported topsoil covers the polluted substrate. Geographic Information Systems (GIS) techniques were applied to the dataset to create elemental spatial distribution maps,  three-dimensional images and interpretive hazard maps of the pollutants in the study area. 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