{"type": "FeatureCollection", "features": [{"id": "10.5281/zenodo.13993045", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:23:36Z", "type": "Dataset", "title": "SERENA EJPSOIL BE Flanders SOCLOSS SOC 0-20cm cookbook", "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\u00a0stakeholders, 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\u00a0the regional, national, and European scales.  This SERENA dataset (100 m resolution) of soil orgnanic carbon concentration (0-20 cm soil layer) for Flanders was mainly produced to test the methodology of the SERENA SOC LOSS cookbook of the European SERENA EJP SOIL project. The data was prepared according to the methodology of SERENA SOC LOSS cookbook. The objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. Soil organic carbon concentration was used as an indicator for soil organic carbon loss (ST). The map was based on digital soil mapping according to the method used in the EJP SOIL project WP6: Digital soil mapping approach with random forest using ISRIC workflow seedling. To create the soil organic carbon concentration map, we used soil organic carbon data of the regional soil organic carbon monitoring network Cmon in Flanders (0-10 and 10-30 cm soil layer) from the period 2021-2024. The soil organic carbon concentration of the 0-20 cm was derived from the 0-10 and 10-30 cm Cmon data. The following auxiliary data was used: Digitale bodemkaart van het Vlaams Gewest: bodemtypes; Regional climate data; Landgebruik - Vlaanderen - toestand 2022; Tertiair geologische kaart (1/50.000); Bodembedekkingskaart (BBK), 1m resolutie, opname 2021; WRB Soil Units 40k: Bodemkaart van het Vlaamse Gewest volgens het internationale bodemclassificatiesysteem World Reference Base op schaal 1:40.000; Digitaal Hoogtemodel Vlaanderen II, DSM, raster, 1 m. The dataset will be mostly useful as a reference result for actors that want to learn to implement the part of the soil organic carbon loss cookbook of SERENA dealing with the creation of a SOC concentration map. It can have limited use as an interim SOC concentration map for Flanders until a better map becomes available using an optimised methodology and/or new data from the regional soil organic carbon monitoring network that was not yet available when this map was created.  This dataset is originally hosted at DOV (https://www.dov.vlaanderen.be/), for the most up to date version of the dataset access the data from the DOV repository through the DOV services. The original metdata is accesible through the DOV metadata catalog: SERENA EJPSOIL BE Flanders SOC 0-20cm cookbook.  The DOV services:    WMS ( OGC:WMS-1.3.0-http-get-map )\u00a0  WCS ( OGC:WCS )", "keywords": ["Soil organic carbon concentration", "Belgium", "D3.3/ WP3/ Task 3.2", "EJPSOIL", "SERENA project", "Flanders", "SOC", "SOCLOSS", "Grant n 862695", "Digital Soil Mapping"], "contacts": [{"organization": "Oorts, Katrien, Josipovic, Davor, Luts, Dries, Salomez, Joost,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13993045"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13993045", "name": "item", "description": "10.5281/zenodo.13993045", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13993045"}, {"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.14044657", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:23:39Z", "type": "Dataset", "title": "SERENA EJPSOIL BE Flanders soil sealing cookbook", "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.The data was prepared according to the Level 2 methodology of the SERENA soil sealing cookbook. For Belgium, the application was carried out at the regional scale for the Flanders region. \u00a0The automatically generated yearly soil sealing maps (1 m resolution GeoTIFF rasters)\u00a0combine \u201cknown\u201d sealing from administrative databases (buildings and transport infrastructure) with modelled sealing based on artificial intelligence. Administrative databases do not (adequately) cover parking lots, private driveways and garden terraces, which are a substantial part of the sealed area in Flanders. Hence, a machine learning model was built for deriving this remaining sealing from aerial imagery. For this purpose, an assessor manually labeled the sealed parts on a subset of the images. Based on this training set, a convolutional neural network model was used to produce a sealing probability map, which was converted to a binary modelled sealing map. Finally, a continuity correction was applied to ensure a temporally consistent result across the yearly maps. \u00a0The objective of the SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. The selected indicator was the degree of soil sealing. By evaluating this degree at two moments in time, the change in soil sealing can be determined. \u00a0\u00a0The following data were used:\u00a0         Large-scale Reference Database (Grootschalig Referentiebestand or Basiskaart), the digital topographic reference map for Flanders (vector)\u00a0           Medium-scale annual winter aerial images of Flanders (15 or 25 cm raster resolution)    This dataset is originally hosted at Geopunt (www.geopunt.be). For the most up-to-date version of the dataset, please access the data from the Geopunt repository.", "keywords": ["soil sealing", "remote sensing", "BELGIUM (FLANDERS)", "aerial images", "SERENA", "EJP-Soil", "photointerpretation"], "contacts": [{"organization": "Cockx, Kasper, Oorts, Katrien,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14044657"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14044657", "name": "item", "description": "10.5281/zenodo.14044657", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14044657"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}, {"id": "10.5281/zenodo.13981884", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:23:35Z", "type": "Dataset", "title": "SERENA EJPSOIL BE Flanders SOCLOSS SOC 0-20cm cookbook", "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\u00a0stakeholders, 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\u00a0the regional, national, and European scales.  This SERENA dataset (100 m resolution) of soil orgnanic carbon concentration (0-20 cm soil layer) for Flanders was mainly produced to test the methodology of the SERENA SOC LOSS cookbook of the European SERENA EJP SOIL project. The data was prepared according to the methodology of SERENA SOC LOSS cookbook. The objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. Soil organic carbon concentration was used as an indicator for soil organic carbon loss (ST). The map was based on digital soil mapping according to the method used in the EJP SOIL project WP6: Digital soil mapping approach with random forest using ISRIC workflow seedling. To create the soil organic carbon concentration map, we used soil organic carbon data of the regional soil organic carbon monitoring network Cmon in Flanders (0-10 and 10-30 cm soil layer) from the period 2021-2024. The soil organic carbon concentration of the 0-20 cm was derived from the 0-10 and 10-30 cm Cmon data. The following auxiliary data was used: Digitale bodemkaart van het Vlaams Gewest: bodemtypes; Regional climate data; Landgebruik - Vlaanderen - toestand 2022; Tertiair geologische kaart (1/50.000); Bodembedekkingskaart (BBK), 1m resolutie, opname 2021; WRB Soil Units 40k: Bodemkaart van het Vlaamse Gewest volgens het internationale bodemclassificatiesysteem World Reference Base op schaal 1:40.000; Digitaal Hoogtemodel Vlaanderen II, DSM, raster, 1 m. The dataset will be mostly useful as a reference result for actors that want to learn to implement the part of the soil organic carbon loss cookbook of SERENA dealing with the creation of a SOC concentration map. It can have limited use as an interim SOC concentration map for Flanders until a better map becomes available using an optimised methodology and/or new data from the regional soil organic carbon monitoring network that was not yet available when this map was created.  This dataset is originally hosted at DOV (https://www.dov.vlaanderen.be/), for the most up to date version of the dataset access the data from the DOV repository through the DOV services. The original metdata is accesible through the DOV metadata catalog: SERENA EJPSOIL BE Flanders SOC 0-20cm cookbook.  The DOV services:    WMS ( OGC:WMS-1.3.0-http-get-map )\u00a0  WCS ( OGC:WCS )", "keywords": ["Soil organic carbon concentration", "Belgium", "Grant\u202f n 862695", "D3.3/ WP3/ Task 3.2", "EJPSOIL", "SERENA project", "Flanders", "SOC", "SOCLOSS", "Grant n 862695", "Digital Soil Mapping"], "contacts": [{"organization": "Oorts, Katrien, Josipovic, Davor, Luts, Dries, Salomez, Joost,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13981884"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13981884", "name": "item", "description": "10.5281/zenodo.13981884", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13981884"}, {"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": "10.1016/J.JENVMAN.2019.04.120", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:15:29Z", "type": "Journal Article", "created": "2019-06-13", "title": "A spatial approach to identify priority areas for pesticide pollution mitigation", "description": "Identifying priority areas is an essential step in developing management strategies to reduce pesticide loads in surface water. A spatially explicit model-based approach was developed to detect priority areas for diffuse pesticide pollution at catchment scale. The method uses available datasets and considers different pesticide pathways in the environment post-application. The approach was applied in a catchment area in SE Flanders (Belgium) as a case study. Calculated risk areas were obtained using detailed landscape data and combining pesticide emissions and hydrological connectivity. The risk areas obtained were further compared with an alternative observation-based method, developed specifically for this study site that includes long-term field observations and local expert knowledge. Both methods equally classified 50% of the areas. The impact of crop rotation on the calculated risk was analysed. High-risk areas were identified and added to a cumulative map over all five years to evaluate temporal variations. The model-based approach was used for the initial identification of risk areas at the study site. The tool helps to prioritise zones and detect particular fields to target landscape mitigation measures to reduce diffuse pesticide pollution reaching surface water bodies.", "keywords": ["Technology and Engineering", "GIS modelling", "FATE", "0207 environmental engineering", "GLYPHOSATE", "02 engineering and technology", "Diffuse pesticide pollution", "01 natural sciences", "12. Responsible consumption", "CATCHMENT", "Belgium", "RUNOFF", "SURFACE WATERS", "Pesticides", "Biology", "0105 earth and related environmental sciences", "RISK", "Catchment scale", "Water Pollution", "Surface water", "Agriculture", "HERBICIDE LOSSES", "15. Life on land", "Field observations", "BUFFER ZONES", "TRANSPORT", "6. Clean water", "NO-TILL", "Chemistry", "13. Climate action", "Earth and Environmental Sciences", "Pesticide risk areas", "Water Pollutants", " Chemical"]}, "links": [{"href": "https://doi.org/10.1016/J.JENVMAN.2019.04.120"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/J.JENVMAN.2019.04.120", "name": "item", "description": "10.1016/J.JENVMAN.2019.04.120", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/J.JENVMAN.2019.04.120"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-09-01T00:00:00Z"}}, {"id": "10.1016/j.foreco.2008.05.007", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:16:30Z", "type": "Journal Article", "created": "2008-06-19", "title": "Effect Of Tree Species On Carbon Stocks In Forest Floor And Mineral Soil And Implications For Soil Carbon Inventories", "description": "<p>Forest soil organic carbon (SOC) and forest floor carbon (FFC) stocks are highly variable. The sampling effort required to assess SOC and FFC stocks is therefore large, resulting in limited sampling and poor estimates of the size, spatial distribution, and changes in SOC and FFC stocks in many countries. Forest SOC and FFC stocks are influenced by tree species. Therefore, quantification of the effect of tree species on carbon stocks combined with spatial information on tree species distribution could improve insight into the spatial distribution of forest carbon stocks. We present a study on the effect of tree species on FFC and SOC stock for a forest in the Netherlands and evaluate how this information could be used for inventory improvement. We assessed FFC and SOC stocks in stands of beech (Fagus sylvatica), Douglas fir (Pseudotsuga menziesii), Scots pine (Pinus sylvestris), oak (Quercus robur) and larch (Larix kaempferi). FFC and SOC stocks differed between a number of species. FFC stocks varied between 11.1 Mg C ha<sup>-1</sup> (beech) and 29.6 Mg C ha<sup>-1</sup> (larch). SOC stocks varied between 53.3 Mg C ha<sup>-1</sup> (beech) and 97.1 Mg C ha<sup>-1</sup> (larch). At managed locations, carbon stocks were lower than at unmanaged locations. The Dutch carbon inventory currently overestimates FFC stocks. Differences in carbon stocks between conifer and broadleaf forests were significant enough to consider them relevant for the Dutch system for carbon inventory.</p>", "keywords": ["0106 biological sciences", "land-use history", "01 natural sciences", "mitigation", "greenhouse gases", "Carbon stock", "Forest floor", "forest ecology", "SDG 15 - Life on Land", "forests", "decomposition", "species composition", "transformation", "carbon dioxide", "belgium", "04 agricultural and veterinary sciences", "15. Life on land", "Management", "impact", "0401 agriculture", " forestry", " and fisheries", "spatial variability", "europe", "Mineral soil", "management", "pine", "Tree species"]}, "links": [{"href": "https://doi.org/10.1016/j.foreco.2008.05.007"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Forest%20Ecology%20and%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.foreco.2008.05.007", "name": "item", "description": "10.1016/j.foreco.2008.05.007", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.foreco.2008.05.007"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2008-07-01T00:00:00Z"}}, {"id": "10.1016/j.jconhyd.2021.103797", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:16:50Z", "type": "Journal Article", "created": "2021-03-18", "title": "Dynamics of nitrous oxide with depth in groundwater: Insights from ambient groundwater and laboratory incubation experiments (Hesbaye chalk aquifer, Belgium)", "description": "Aquifers under agricultural areas are considered to be an indirect source of nitrous oxide emission (N2O) to the atmosphere, which is the greenhouse gas (GHGs) characterized with the highest global warning potential and acts as a stratospheric ozone depletion agent. Previous investigations performed in the Cretaceous Hesbaye chalk aquifer in Eastern Belgium suggested that the dynamics of N2O in the aquifer is controlled by overlapping biochemical processes such as nitrification and denitrification. The current study aims to obtain better insight concerning the factors controlling the distribution of N2O concentration along a vertical dimension in the aquifer, and to capture and quantify the occurrence of nitrification and denitrification processes in the groundwater system. Low-flow groundwater sampling technique was undertaken at different depths in the aquifer to collect groundwater samples aiming at obtaining information about ambient aquifer hydrogeochemical conditions and their effect on the accumulation of GHGs. Afterwards, laboratory stable isotope experiments, using NO3- and NH4+ compounds labeled with heavy 15N isotope, were applied to quantify the rates of nitrification and denitrification processes. Ambient studies suggest that the occurrence of N transformation was related to denitrification while laboratory incubation experiments did not detect it. Such controversial results might be explained by the discrepancy between real aquifer conditions and lab design studies. Thus, additional in situ tracer experiments should be carried out in areas where natural groundwater fluxes do not flush the injected tracer too rapidly. In addition, it would be useful to conduct microbiological studies to obtain better insight into the nature of subsurface biofilm biotope.", "keywords": ["2. Zero hunger", "Nitrous Oxide", "N stable isotope analysis", "Nitrification", "01 natural sciences", "Low-flow sampling", "6. Clean water", "Calcium Carbonate", "Greenhouse gases", "Belgium", "13. Climate action", "Denitrification", "Laboratories", "Groundwater", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.jconhyd.2021.103797"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Contaminant%20Hydrology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jconhyd.2021.103797", "name": "item", "description": "10.1016/j.jconhyd.2021.103797", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jconhyd.2021.103797"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-08-01T00:00:00Z"}}, {"id": "10.1016/j.jenvman.2019.04.120", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:16:51Z", "type": "Journal Article", "created": "2019-06-13", "title": "A spatial approach to identify priority areas for pesticide pollution mitigation", "description": "Identifying priority areas is an essential step in developing management strategies to reduce pesticide loads in surface water. A spatially explicit model-based approach was developed to detect priority areas for diffuse pesticide pollution at catchment scale. The method uses available datasets and considers different pesticide pathways in the environment post-application. The approach was applied in a catchment area in SE Flanders (Belgium) as a case study. Calculated risk areas were obtained using detailed landscape data and combining pesticide emissions and hydrological connectivity. The risk areas obtained were further compared with an alternative observation-based method, developed specifically for this study site that includes long-term field observations and local expert knowledge. Both methods equally classified 50% of the areas. The impact of crop rotation on the calculated risk was analysed. High-risk areas were identified and added to a cumulative map over all five years to evaluate temporal variations. The model-based approach was used for the initial identification of risk areas at the study site. The tool helps to prioritise zones and detect particular fields to target landscape mitigation measures to reduce diffuse pesticide pollution reaching surface water bodies.", "keywords": ["Technology and Engineering", "GIS modelling", "FATE", "0207 environmental engineering", "GLYPHOSATE", "02 engineering and technology", "Diffuse pesticide pollution", "01 natural sciences", "12. Responsible consumption", "CATCHMENT", "Belgium", "RUNOFF", "SURFACE WATERS", "Pesticides", "Biology", "0105 earth and related environmental sciences", "RISK", "Catchment scale", "Water Pollution", "Surface water", "Agriculture", "HERBICIDE LOSSES", "15. Life on land", "Field observations", "BUFFER ZONES", "TRANSPORT", "6. Clean water", "NO-TILL", "Chemistry", "13. Climate action", "Earth and Environmental Sciences", "Pesticide risk areas", "Water Pollutants", " Chemical"]}, "links": [{"href": "https://doi.org/10.1016/j.jenvman.2019.04.120"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jenvman.2019.04.120", "name": "item", "description": "10.1016/j.jenvman.2019.04.120", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jenvman.2019.04.120"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-09-01T00:00:00Z"}}, {"id": "10.21203/rs.3.rs-3537993/v2", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:20:51Z", "type": "Journal Article", "created": "2024-12-01", "title": "Metal(loid) tolerance, accumulation, and phytoremediation potential of wetland macrophytes for multi-metal(loid)s polluted water.", "description": "<title>Abstract</title>         <p>Natural based solutions, notably constructed/artificial wetland treatment systems, rely heavily on identification and use of macrophytes with the ability to tolerate multiple contaminants and grow for an extended period to reduce contamination. The potential to tolerate and remediate metal(loid) contaminated groundwater from an industrial site located in Flanders (Belgium) was assessed for 10 wetland macrophytes (including <italic>Carex riparia, Cyperus longus, Cyperus rotundus, Iris pseudacorus, Juncus effusus, Lythrum salicaria, Menta aquatica, Phragmites australis, Scirpus holoschoenus,</italic> and <italic>Typha angustifolia</italic>). The experiment was conducted under static conditions, where plants were exposed to polluted acidic (pH~4)water, having high level of metal(loid)s for 15 days. Plant biomass, morphology, and metal uptake by roots and shoots were analysed every 5 days for all species. <italic>T. angustifolia</italic> and <italic>S. holoschoenus </italic>produced ~3 and ~1.1 times more dried biomass than the controls, respectively. For <italic>S. holoschoenus, P. australis,</italic> and <italic>T. angustifolia</italic>, no apparent morphological stress symptoms were observed, and plant heights were similar between control and plants exposed to polluted groundwater. Higher concentrations of all metal(loid)s were detected in the roots indicating a potential for phytostabilization of metal(loid)s below the water column. For <italic>J. effusus</italic> and <italic>T. angustifolia</italic>, Cd, Ni, and Zn accumulation was observed higher in the shoots. <italic>S. holoschoenus</italic>, <italic>P. australis,</italic> and <italic>T. angustifolia</italic> are proposed for restoration and phytostabilization strategies in natural and/or constructed wetland and aquatic ecosystems affected by metal(loid) inputs.</p>", "keywords": ["580", "570", "Constructed wetlands", "15. Life on land", "Biorremediaci\u00f3n", "6. Clean water", "Macrophytes", "Agua-Contaminaci\u00f3n", "Biodegradation", " Environmental", "Heavy metals", "Water-Pollution", "Belgium", "Metals", "13. Climate action", "Wetlands", "Metals", " Heavy", "Phytostabilization", "Groundwater", "Bioremediation", "Water Pollutants", " Chemical", "Research Article"]}, "links": [{"href": "https://doi.org/10.21203/rs.3.rs-3537993/v2"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20and%20Pollution%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.21203/rs.3.rs-3537993/v2", "name": "item", "description": "10.21203/rs.3.rs-3537993/v2", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.21203/rs.3.rs-3537993/v2"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-12T00:00:00Z"}}, {"id": "10.3390/agronomy11050946", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:21:48Z", "type": "Journal Article", "created": "2021-05-11", "title": "Estimating Farm Wheat Yields from NDVI and Meteorological Data", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Information on crop yield at scales ranging from the field to the global level is imperative for farmers and decision makers. The current data sources to monitor crop yield, such as regional agriculture statistics, are often lacking in spatial and temporal resolution. Remotely sensed vegetation indices (VIs) such as NDVI are able to assess crop yield using empirical modelling strategies. Empirical NDVI-based crop yield models were evaluated by comparing the model performance with similar models used in different regions. The integral NDVI and the peak NDVI were weak predictors of winter wheat yield in northern Belgium. Winter wheat (Triticum aestivum) yield variability was better predicted by monthly precipitation during tillering and anthesis than by NDVI-derived yield proxies in the period from 2016 to 2018 (R2 = 0.66). The NDVI series were not sensitive enough to yield affecting weather conditions during important phenological stages such as tillering and anthesis and were weak predictors in empirical crop yield models. In conclusion, winter wheat yield modelling using NDVI-derived yield proxies as predictor variables is dependent on the environment.</p></article>", "keywords": ["yield estimation", "PREDICTION", "NDVI", "Triticum aestivum", "0703 Crop and Pasture Production", "3002 Agriculture", " land and farm management", "3004 Crop and pasture production", "Belgium", "0502 Environmental Science and Management", "<i>Triticum aestivum</i>", "2. Zero hunger", "Science & Technology", "S", "Plant Sciences", "Agriculture", "weather impact", "04 agricultural and veterinary sciences", "WINTER-WHEAT", "15. Life on land", "Agronomy", "winter wheat", "MODEL", "RESOLUTION", "SENTINEL-2", "0401 agriculture", " forestry", " and fisheries", "LANDSAT 8", "Life Sciences & Biomedicine"]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/5/946/pdf"}, {"href": "https://doi.org/10.3390/agronomy11050946"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/agronomy11050946", "name": "item", "description": "10.3390/agronomy11050946", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/agronomy11050946"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-11T00:00:00Z"}}, {"id": "10.3390/w14081188", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:22:10Z", "type": "Journal Article", "created": "2022-04-10", "title": "Estimating Yield from NDVI, Weather Data, and Soil Water Depletion for Sugar Beet and Potato in Northern Belgium", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Crop-yield models based on vegetation indices such as the normalized difference vegetation index (NDVI) have been developed to monitor crop yield at higher spatial and temporal resolutions compared to agricultural statistical data. We evaluated the model performance of NDVI-based random forest models for sugar beet and potato farm yields in northern Belgium during 2016\u20132018. We also evaluated whether weather variables and root-zone soil water depletion during the growing season improved the model performance. The NDVI integral did not explain early and late potato yield variability and only partly explained sugar-beet yield variability. The NDVI series of early and late potato crops were not sensitive enough to yield affecting weather and soil water conditions. We found that water-saturated conditions early in the growing season and elevated temperatures late in the growing season explained a large part of the sugar-beet and late-potato yield variability. The NDVI integral in combination with monthly precipitation, maximum temperature, and root-zone soil water depletion during the growing season explained farm-scale sugar beet (R2 = 0.84, MSE = 48.8) and late potato (R2 = 0.56, MSE = 57.3) yield variability well from 2016 to 2018 in northern Belgium.</p></article>", "keywords": ["AquaCrop-OSPy", "STRESS", "root-zone soil water depletion; AquaCrop-OSPy; sugar beet; potato; crop yield; NDVI; Belgium; weather impact; random forest", "NDVI", "Environmental Sciences & Ecology", "root-zone soil water depletion", "01 natural sciences", "Belgium", "INDEX", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "PRODUCTIVITY", "CROP", "sugar beet", "weather impact", "04 agricultural and veterinary sciences", "crop yield", "WINTER-WHEAT", "15. Life on land", "MODEL", "Physical Sciences", "Water Resources", "potato", "0401 agriculture", " forestry", " and fisheries", "Life Sciences & Biomedicine", "Environmental Sciences", "random forest"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/14/8/1188/pdf"}, {"href": "https://www.mdpi.com/2073-4441/14/8/1188/pdf"}, {"href": "https://doi.org/10.3390/w14081188"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/w14081188", "name": "item", "description": "10.3390/w14081188", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/w14081188"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-04-08T00:00:00Z"}}, {"id": "10.5281/zenodo.14008412", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:23:37Z", "type": "Dataset", "title": "SERENA EJPSOIL BE Flanders soil sealing cookbook", "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.The data was prepared according to the Level 2 methodology of the SERENA soil sealing cookbook. For Belgium, the application was carried out at the regional scale for the Flanders region. \u00a0The automatically generated yearly soil sealing maps (1 m resolution GeoTIFF rasters)\u00a0combine \u201cknown\u201d sealing from administrative databases (buildings and transport infrastructure) with modelled sealing based on artificial intelligence. Administrative databases do not (adequately) cover parking lots, private driveways and garden terraces, which are a substantial part of the sealed area in Flanders. Hence, a machine learning model was built for deriving this remaining sealing from aerial imagery. For this purpose, an assessor manually labeled the sealed parts on a subset of the images. Based on this training set, a convolutional neural network model was used to produce a sealing probability map, which was converted to a binary modelled sealing map. Finally, a continuity correction was applied to ensure a temporally consistent result across the yearly maps. \u00a0The objective of the SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. The selected indicator was the degree of soil sealing. By evaluating this degree at two moments in time, the change in soil sealing can be determined. \u00a0\u00a0The following data were used:\u00a0         Large-scale Reference Database (Grootschalig Referentiebestand or Basiskaart), the digital topographic reference map for Flanders (vector)\u00a0           Medium-scale annual winter aerial images of Flanders (15 or 25 cm raster resolution)    This dataset is originally hosted at Geopunt (www.geopunt.be). For the most up-to-date version of the dataset, please access the data from the Geopunt repository.", "keywords": ["soil sealing", "remote sensing", "BELGIUM (FLANDERS)", "aerial images", "SERENA", "EJP-Soil", "photointerpretation"], "contacts": [{"organization": "Cockx, Kasper, Oorts, Katrien,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14008412"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14008412", "name": "item", "description": "10.5281/zenodo.14008412", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14008412"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}, {"id": "10.5281/zenodo.13993234", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:23:36Z", "type": "Dataset", "title": "SERENA EJPSOIL BE Flanders EROSION SOILLOSS cookbook", "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.  The dataset (5m resolution) was mainly produced to test the methodology of the SERENA soil erosion cookbook of the European SERENA EJP SOIL project. The data was prepared according to the methodology of SERENA soil erosion cookbook. The objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. Soil loss was used as an indicator for soil erosion. For Belgium, the application was carried out at regional scale for the Flanders region. To create the soil erosion map, RULSE modelling was done according to the SERENA cookbook using several publicly available datasets. The following auxiliary data was used: K-Factor, Land-Cover Map, Long-term 30 yr averaged monthly rainfall,\u00a0LS-Factor given by Panagos et al. (2015). The dataset will be mostly useful as a reference result for actors that want to learn to implement the part of the soil erosion cookbook of SERENA dealing with the creation of an erosion map. It has limited use as an erosion map for Flanders because a more detailed and accurate map exists for Flanders based on regional covariates.  This dataset is originally hosted at DOV (https://www.dov.vlaanderen.be/), for the most up to date version of the dataset access the data from the DOV repository through the DOV services. The original metdata is accesible through the DOV metadata catalog: SERENA EJPSOIL BE Flanders EROSION SOILLOSS cookbook  The DOV services:    WMS ( OGC:WMS-1.3.0-http-get-map )\u00a0  WCS ( OGC:WCS )", "keywords": ["soil erosion", "Belgium", "EROSION", "D3.3/ WP3/ Task 3.2", "EJPSOIL", "SERENA project", "SOILLOSS", "Flanders", "Grant n 862695", "Digital Soil Mapping"], "contacts": [{"organization": "Callewaert, Seth, Oorts, Katrien, Luts, Dries, Deproost, Petra,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13993234"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13993234", "name": "item", "description": "10.5281/zenodo.13993234", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13993234"}, {"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": "10.5281/zenodo.13993235", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:23:36Z", "type": "Dataset", "title": "SERENA EJPSOIL BE Flanders EROSION SOILLOSS cookbook", "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.  The dataset (5m resolution) was mainly produced to test the methodology of the SERENA soil erosion cookbook of the European SERENA EJP SOIL project. The data was prepared according to the methodology of SERENA soil erosion cookbook. The objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. Soil loss was used as an indicator for soil erosion. For Belgium, the application was carried out at regional scale for the Flanders region. To create the soil erosion map, RULSE modelling was done according to the SERENA cookbook using several publicly available datasets. The following auxiliary data was used: K-Factor, Land-Cover Map, Long-term 30 yr averaged monthly rainfall,\u00a0LS-Factor given by Panagos et al. (2015). The dataset will be mostly useful as a reference result for actors that want to learn to implement the part of the soil erosion cookbook of SERENA dealing with the creation of an erosion map. It has limited use as an erosion map for Flanders because a more detailed and accurate map exists for Flanders based on regional covariates.  This dataset is originally hosted at DOV (https://www.dov.vlaanderen.be/), for the most up to date version of the dataset access the data from the DOV repository through the DOV services. The original metdata is accesible through the DOV metadata catalog: SERENA EJPSOIL BE Flanders EROSION SOILLOSS cookbook  The DOV services:    WMS ( OGC:WMS-1.3.0-http-get-map )\u00a0  WCS ( OGC:WCS )", "keywords": ["soil erosion", "Belgium", "EROSION", "D3.3/ WP3/ Task 3.2", "EJPSOIL", "SERENA project", "SOILLOSS", "Flanders", "Grant n 862695", "Digital Soil Mapping"], "contacts": [{"organization": "Callewaert, Seth, Oorts, Katrien, Luts, Dries, Deproost, Petra,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13993235"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13993235", "name": "item", "description": "10.5281/zenodo.13993235", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13993235"}, {"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": "10259/9749", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:25:54Z", "type": "Journal Article", "created": "2024-12-01", "title": "Metal(loid) tolerance, accumulation, and phytoremediation potential of wetland macrophytes for multi-metal(loid)s polluted water.", "description": "<title>Abstract</title>         <p>Natural based solutions, notably constructed/artificial wetland treatment systems, rely heavily on identification and use of macrophytes with the ability to tolerate multiple contaminants and grow for an extended period to reduce contamination. The potential to tolerate and remediate metal(loid) contaminated groundwater from an industrial site located in Flanders (Belgium) was assessed for 10 wetland macrophytes (including <italic>Carex riparia, Cyperus longus, Cyperus rotundus, Iris pseudacorus, Juncus effusus, Lythrum salicaria, Menta aquatica, Phragmites australis, Scirpus holoschoenus,</italic> and <italic>Typha angustifolia</italic>). The experiment was conducted under static conditions, where plants were exposed to polluted acidic (pH~4)water, having high level of metal(loid)s for 15 days. Plant biomass, morphology, and metal uptake by roots and shoots were analysed every 5 days for all species. <italic>T. angustifolia</italic> and <italic>S. holoschoenus </italic>produced ~3 and ~1.1 times more dried biomass than the controls, respectively. For <italic>S. holoschoenus, P. australis,</italic> and <italic>T. angustifolia</italic>, no apparent morphological stress symptoms were observed, and plant heights were similar between control and plants exposed to polluted groundwater. Higher concentrations of all metal(loid)s were detected in the roots indicating a potential for phytostabilization of metal(loid)s below the water column. For <italic>J. effusus</italic> and <italic>T. angustifolia</italic>, Cd, Ni, and Zn accumulation was observed higher in the shoots. <italic>S. holoschoenus</italic>, <italic>P. australis,</italic> and <italic>T. angustifolia</italic> are proposed for restoration and phytostabilization strategies in natural and/or constructed wetland and aquatic ecosystems affected by metal(loid) inputs.</p>", "keywords": ["580", "570", "Constructed wetlands ; Metals/metabolism [MeSH] ; Groundwater ; Phytostabilization ; Wetlands [MeSH] ; Metals", " Heavy/metabolism [MeSH] ; Heavy metals ; Macrophytes ; Water Pollutants", " Chemical/metabolism [MeSH] ; Research Article ; Biodegradation", " Environmental [MeSH] ; Belgium [MeSH]", "Constructed wetlands", "15. Life on land", "Biorremediaci\u00f3n", "6. Clean water", "Macrophytes", "Agua-Contaminaci\u00f3n", "Biodegradation", " Environmental", "Heavy metals", "Water-Pollution", "Belgium", "Metals", "13. Climate action", "Wetlands", "Metals", " Heavy", "Phytostabilization", "Groundwater", "Bioremediation", "Water Pollutants", " Chemical", "Research Article"]}, "links": [{"href": "https://doi.org/10259/9749"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20and%20Pollution%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10259/9749", "name": "item", "description": "10259/9749", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10259/9749"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-12T00:00:00Z"}}, {"id": "1854/LU-01JM00E41RAYQZ9BSHZ6EH3WV9", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:26:33Z", "type": "Journal Article", "created": "2025-02-03", "title": "How do varying nitrogen fertilization rates affect crop yields and riverine N2O emissions? A hybrid modeling study", "description": "Headwater streams in agricultural areas constitute significant sources of nitrous oxide (N2O) due to nutrient enrichment; however, their emissions are often overlooked in current environmental impact assessments. This scarcity highlights the importance of developing advanced decision tools to evaluate these contributions and create effective mitigation strategies. Our study establishes the first integrated modeling framework that combines a process-based model SWAT+ with a linear mixed model (LMM) to predict N2O emissions from a headwater agricultural river system in Belgium under diverse climate change and fertilization scenarios. In particular, the calibrated and validated SWAT+ model was used to simulate streamflow, nutrient transport, and crop yields under these scenarios, from which, together with biochemical data collected from sampling campaigns, riverine N2O emissions were predicted via LMM. Our results revealed hydrologically driven patterns in riverine N2O emissions, with peak emissions in winter and spring, driven by precipitations enhancing shallow subsurface flows, carrying leached nutrients from fields to the river, and fueling N2O emissions. These phenomena were intensified under climate change scenarios, especially during combined wetter and hotter winters and springs, which elevated headwater N2O emissions by 40 %. Moreover, when coupling these conditions with a 20 % increase in fertilizer rates, riverine N2O emissions would be boosted by 83 %. These findings underscore the importance of integrating land-surface and river processes, to effectively quantify the feedback loop between river nutrient enrichment and climate change under the influence of agricultural practices, and to support comprehensive mitigation strategies under the warming climate.", "keywords": ["Agriculture and Food Sciences", "Riverine nitrous oxide dynamics", "PROTOCOL", "Crops", " Agricultural", "CLIMATE-CHANGE", "IMPACT", "Nitrogen", "Climate Change", "Nitrous Oxide", "Agriculture", "PERFORMANCE", "Models", " Theoretical", "Headwater streams", "OXIDE EMISSIONS", "Hybrid modeling", "Rivers", "Belgium", "Agricultural GHG impact", "Climate change", "STREAMS", "Fertilizers"]}, "links": [{"href": "https://doi.org/1854/LU-01JM00E41RAYQZ9BSHZ6EH3WV9"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1854/LU-01JM00E41RAYQZ9BSHZ6EH3WV9", "name": "item", "description": "1854/LU-01JM00E41RAYQZ9BSHZ6EH3WV9", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-01JM00E41RAYQZ9BSHZ6EH3WV9"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-05-01T00:00:00Z"}}, {"id": "1854/LU-8619257", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:26:33Z", "type": "Journal Article", "created": "2019-06-13", "title": "A spatial approach to identify priority areas for pesticide pollution mitigation", "description": "Identifying priority areas is an essential step in developing management strategies to reduce pesticide loads in surface water. A spatially explicit model-based approach was developed to detect priority areas for diffuse pesticide pollution at catchment scale. The method uses available datasets and considers different pesticide pathways in the environment post-application. The approach was applied in a catchment area in SE Flanders (Belgium) as a case study. Calculated risk areas were obtained using detailed landscape data and combining pesticide emissions and hydrological connectivity. The risk areas obtained were further compared with an alternative observation-based method, developed specifically for this study site that includes long-term field observations and local expert knowledge. Both methods equally classified 50% of the areas. The impact of crop rotation on the calculated risk was analysed. High-risk areas were identified and added to a cumulative map over all five years to evaluate temporal variations. The model-based approach was used for the initial identification of risk areas at the study site. The tool helps to prioritise zones and detect particular fields to target landscape mitigation measures to reduce diffuse pesticide pollution reaching surface water bodies.", "keywords": ["Technology and Engineering", "GIS modelling", "FATE", "0207 environmental engineering", "GLYPHOSATE", "02 engineering and technology", "Diffuse pesticide pollution", "01 natural sciences", "12. Responsible consumption", "CATCHMENT", "Belgium", "RUNOFF", "SURFACE WATERS", "Pesticides", "Biology", "0105 earth and related environmental sciences", "RISK", "Catchment scale", "Water Pollution", "Surface water", "Agriculture", "HERBICIDE LOSSES", "15. Life on land", "Field observations", "BUFFER ZONES", "TRANSPORT", "6. Clean water", "NO-TILL", "Chemistry", "13. Climate action", "Earth and Environmental Sciences", "Pesticide risk areas", "Water Pollutants", " Chemical"]}, "links": [{"href": "https://doi.org/1854/LU-8619257"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1854/LU-8619257", "name": "item", "description": "1854/LU-8619257", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-8619257"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-09-01T00:00:00Z"}}, {"id": "2268/262547", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:27:05Z", "type": "Journal Article", "created": "2021-03-18", "title": "Dynamics of nitrous oxide with depth in groundwater: Insights from ambient groundwater and laboratory incubation experiments (Hesbaye chalk aquifer, Belgium)", "description": "Aquifers under agricultural areas are considered to be an indirect source of nitrous oxide emission (N2O) to the atmosphere, which is the greenhouse gas (GHGs) characterized with the highest global warning potential and acts as a stratospheric ozone depletion agent. Previous investigations performed in the Cretaceous Hesbaye chalk aquifer in Eastern Belgium suggested that the dynamics of N2O in the aquifer is controlled by overlapping biochemical processes such as nitrification and denitrification. The current study aims to obtain better insight concerning the factors controlling the distribution of N2O concentration along a vertical dimension in the aquifer, and to capture and quantify the occurrence of nitrification and denitrification processes in the groundwater system. Low-flow groundwater sampling technique was undertaken at different depths in the aquifer to collect groundwater samples aiming at obtaining information about ambient aquifer hydrogeochemical conditions and their effect on the accumulation of GHGs. Afterwards, laboratory stable isotope experiments, using NO3- and NH4+ compounds labeled with heavy 15N isotope, were applied to quantify the rates of nitrification and denitrification processes. Ambient studies suggest that the occurrence of N transformation was related to denitrification while laboratory incubation experiments did not detect it. Such controversial results might be explained by the discrepancy between real aquifer conditions and lab design studies. Thus, additional in situ tracer experiments should be carried out in areas where natural groundwater fluxes do not flush the injected tracer too rapidly. In addition, it would be useful to conduct microbiological studies to obtain better insight into the nature of subsurface biofilm biotope.", "keywords": ["Sciences aquatiques & oc\u00e9anologie", "Physique", " chimie", " math\u00e9matiques & sciences de la terre", "Nitrous Oxide", "01 natural sciences", "Low-flow sampling", "Ing\u00e9nierie", " informatique & technologie", "Calcium Carbonate", "Physical", " chemical", " mathematical & earth Sciences", "Belgium", "Groundwater", "0105 earth and related environmental sciences", "2. Zero hunger", "Aquatic sciences & oceanology", "N stable isotope analysis", "Life sciences", "Nitrification", "Geological", " petroleum & mining engineering", "6. Clean water", "Engineering", " computing & technology", "Sciences de la terre & g\u00e9ographie physique", "Greenhouse gases", "13. Climate action", "Earth sciences & physical geography", "Sciences du vivant", "Denitrification", "G\u00e9ologie", " ing\u00e9nierie du p\u00e9trole & des mines", "Laboratories"]}, "links": [{"href": "https://orbi.uliege.be/bitstream/2268/262547/2/Dynamics%20of%20nitrous%20oxide%20with%20depth%20in%20groundwater%20insights%20from%20ambient%20groundwater.pdf"}, {"href": "https://doi.org/2268/262547"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Contaminant%20Hydrology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2268/262547", "name": "item", "description": "2268/262547", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2268/262547"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-08-01T00:00:00Z"}}, {"id": "3138664797", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:27:42Z", "type": "Journal Article", "created": "2021-03-18", "title": "Dynamics of nitrous oxide with depth in groundwater: Insights from ambient groundwater and laboratory incubation experiments (Hesbaye chalk aquifer, Belgium)", "description": "Aquifers under agricultural areas are considered to be an indirect source of nitrous oxide emission (N2O) to the atmosphere, which is the greenhouse gas (GHGs) characterized with the highest global warning potential and acts as a stratospheric ozone depletion agent. Previous investigations performed in the Cretaceous Hesbaye chalk aquifer in Eastern Belgium suggested that the dynamics of N2O in the aquifer is controlled by overlapping biochemical processes such as nitrification and denitrification. The current study aims to obtain better insight concerning the factors controlling the distribution of N2O concentration along a vertical dimension in the aquifer, and to capture and quantify the occurrence of nitrification and denitrification processes in the groundwater system. Low-flow groundwater sampling technique was undertaken at different depths in the aquifer to collect groundwater samples aiming at obtaining information about ambient aquifer hydrogeochemical conditions and their effect on the accumulation of GHGs. Afterwards, laboratory stable isotope experiments, using NO3- and NH4+ compounds labeled with heavy 15N isotope, were applied to quantify the rates of nitrification and denitrification processes. Ambient studies suggest that the occurrence of N transformation was related to denitrification while laboratory incubation experiments did not detect it. Such controversial results might be explained by the discrepancy between real aquifer conditions and lab design studies. Thus, additional in situ tracer experiments should be carried out in areas where natural groundwater fluxes do not flush the injected tracer too rapidly. In addition, it would be useful to conduct microbiological studies to obtain better insight into the nature of subsurface biofilm biotope.", "keywords": ["2. Zero hunger", "Nitrous Oxide", "N stable isotope analysis", "Nitrification", "01 natural sciences", "Low-flow sampling", "6. Clean water", "Calcium Carbonate", "Greenhouse gases", "Belgium", "13. Climate action", "Denitrification", "Laboratories", "Groundwater", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/3138664797"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Contaminant%20Hydrology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3138664797", "name": "item", "description": "3138664797", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3138664797"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-08-01T00:00:00Z"}}, {"id": "3161294357", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:27:44Z", "type": "Journal Article", "created": "2021-05-11", "title": "Estimating Farm Wheat Yields from NDVI and Meteorological Data", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Information on crop yield at scales ranging from the field to the global level is imperative for farmers and decision makers. The current data sources to monitor crop yield, such as regional agriculture statistics, are often lacking in spatial and temporal resolution. Remotely sensed vegetation indices (VIs) such as NDVI are able to assess crop yield using empirical modelling strategies. Empirical NDVI-based crop yield models were evaluated by comparing the model performance with similar models used in different regions. The integral NDVI and the peak NDVI were weak predictors of winter wheat yield in northern Belgium. Winter wheat (Triticum aestivum) yield variability was better predicted by monthly precipitation during tillering and anthesis than by NDVI-derived yield proxies in the period from 2016 to 2018 (R2 = 0.66). The NDVI series were not sensitive enough to yield affecting weather conditions during important phenological stages such as tillering and anthesis and were weak predictors in empirical crop yield models. In conclusion, winter wheat yield modelling using NDVI-derived yield proxies as predictor variables is dependent on the environment.</p></article>", "keywords": ["yield estimation", "PREDICTION", "NDVI", "Triticum aestivum", "0703 Crop and Pasture Production", "3002 Agriculture", " land and farm management", "3004 Crop and pasture production", "Belgium", "0502 Environmental Science and Management", "<i>Triticum aestivum</i>", "2. Zero hunger", "Science & Technology", "S", "Plant Sciences", "Agriculture", "weather impact", "04 agricultural and veterinary sciences", "WINTER-WHEAT", "15. Life on land", "Agronomy", "winter wheat", "MODEL", "RESOLUTION", "SENTINEL-2", "0401 agriculture", " forestry", " and fisheries", "LANDSAT 8", "Life Sciences & Biomedicine"]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/5/946/pdf"}, {"href": "https://doi.org/3161294357"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3161294357", "name": "item", "description": "3161294357", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3161294357"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-11T00:00:00Z"}}, {"id": "37aaa10d-50bd-431e-b924-209c2e88b9d7", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[2.48, 48.49], [2.48, 52.51], [6.5, 52.51], [6.5, 48.49], [2.48, 48.49]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "National"}], "scheme": "https://inspire.ec.europa.eu/metadata-codelist/SpatialScope"}, {"concepts": [{"id": "MensMeu"}], "scheme": "Source"}, {"concepts": [{"id": "Belgium"}], "scheme": "http://publications.europa.eu/resource/authority/country"}, {"concepts": [{"id": "carbon stock"}], "scheme": "http://aims.fao.org/aos/agrovoc/c_330883"}], "updated": "2018-01-01", "type": "Dataset", "created": "2017-12-06", "language": "dut", "title": "Soil Organic Carbon Stock Maps for Belgium", "description": "Soil Organic Carbon Stock Maps for Belgium: mean (1 km grid)", "formats": [{"name": "OGC:WMS-1.3.0-http-get-capabilities"}, {"name": "GLG:KML-2.0-http-get-map"}, {"name": "OGC:WMS-1.3.0-http-get-map"}, {"name": "OGC:WMS"}, {"name": "OGC:WCS-1.1.1-http-get-capabilities"}, {"name": "OGC:WCS-1.1.1-http-get-coverage"}, {"name": "OGC:WCS"}, {"name": "WWW:LINK-1.0-http--related"}, {"name": "ogc:wms"}, {"name": "canonical"}], "keywords": ["soil type", "basic soil properties", "National", "MensMeu", "Bodem", "ondergrond", "landbouw", "koolstof", "totaal aan organische koolstof", "grasland", "akker", "bos", "bos", "DOV", "Vlaanderen", "Ondergrond", "Databank Ondergrond Vlaanderen", "Departement Omgeving", "Regionaal", "Herbruikbaar", "Kosteloos", "Vlaamse Open data", "Toegevoegd GDI-Vl", "Metadata GDI-Vl-conform", "Metadata INSPIRE-conform", "Lijst M&R INSPIRE", "Belgium", "carbon stock"], "contacts": [{"name": "Graaf De Ferraris", "organization": "Vlaams Planbureau voor Omgeving (VPO), Departement Omgeving, Vlaamse overheid", "position": null, "roles": ["pointOfContact"], "phones": [{"value": null}], "emails": [{"value": "vpo.omgeving@vlaanderen.be"}], "addresses": [{"deliveryPoint": ["Koning Albert II-laan 20 bus 8"], "city": "Brussel", "administrativeArea": null, "postalCode": "1000", "country": "Belgium"}], "links": [{"href": {"url": "https://www.omgevingvlaanderen.be", "protocol": null, "protocol_url": "", "name": null, "name_url": "", "description": null, "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Vlaamse Overheid - 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For the regional maps a different approach was used for agricultural land as compared to forest. The maps are based on digital soil mapping approaches using empirical models calibrated to predict the SOC stock and using covariates that are available at a sufficient resolution at the regional scale. All maps are strongly dependent on the Belgian Soil Map (texture and drainage parameters). The regional maps were compiled at a finer resolution (10m x 10m and 40m x 40m grid cells). Next they were joined (40m x 40m grid cells) and finally scaled up to the required 1 by 1 km grid cells. This was done using the following tools: block statistics (mean), mosaic to new raster (mean), project to raster, block statistics (mean), resample (nearest neighbour) and project raster.\nGiven the different origin of the individual maps, the uncertainty varies between maps. For instance, a map of the 90% confidence interval of the SOC stocks was produced for agricultural soils in Wallonia based on a Monte Carlo Approach taking into account both the measurement and the model uncertainties. For Flemish forest soils, spatial and analytical uncertainties were taken into account using bootstrapping techniques. For Flemish agricultural soils, the uncertainty reported is the model uncertainty on point estimates for each data point, in which the estimated model parameters are simulated 1000 times as being independent normal distributed variables using their model estimation and standard error as distribution parameters. No additional uncertainty is taken into account for the conversion functions that use the stochastic variables \"bulk density\".\nThe SOC stock maps are the first comprehensive map for Belgium integrating grasslands, croplands and forests. There are two versions of the SOC stock maps for Belgium: 1) resolution of 40m x 40m in the coordinate reference system Lambert72 and 2) resolution of 1km x 1km in the coordinate reference system WGS84. The metadata are available and allow assessing the uncertainties of the stock estimates in the different component maps.", "protocol": "ogc:wms", "rel": null}, {"href": "https://github.com/ejpsoil/ejpsoildatahub/tree/main/datasets/mensmeu/Belgium/37aaa10d-50bd-431e-b924-209c2e88.yml", "name": "Source of the record", "protocol": "canonical", "rel": "canonical"}, {"rel": "self", "type": "application/geo+json", "title": "37aaa10d-50bd-431e-b924-209c2e88b9d7", "name": "item", "description": "37aaa10d-50bd-431e-b924-209c2e88b9d7", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/37aaa10d-50bd-431e-b924-209c2e88b9d7"}, {"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": "70f368f8-db6e-430d-9ae4-fe0acd55fe52", "type": "Feature", "geometry": null, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "National"}], "scheme": "https://inspire.ec.europa.eu/metadata-codelist/SpatialScope"}, {"concepts": [{"id": "MensMeu"}], "scheme": "Source"}, {"concepts": [{"id": "Belgium"}], "scheme": "http://publications.europa.eu/resource/authority/country"}, {"concepts": [{"id": "soil erosion"}], "scheme": "http://aims.fao.org/aos/agrovoc/c_330883"}], "updated": "2011-01-01", "type": "Dataset", "created": "2010-12-01", "language": "dut", "title": "Potential soil erosion aggregated for a grid of 1 km by 1 km in Flanders", "description": "The potential soil erosion aggregated for a grid of 1 km  (ton/ha)", "formats": [{"name": "OGC:WFS"}, {"name": "OGC:WFS-2.0.0-http-get-capabilities"}, {"name": "OGC:WMS-1.3.0-http-get-capabilities"}, {"name": "GLG:KML-2.0-http-get-map"}, {"name": "OGC:WMS-1.3.0-http-get-map"}, {"name": "OGC:WMS"}, {"name": "OGC:WFS-2.0.0-http-get-feature"}, {"name": "ogc:wms"}, {"name": "canonical"}], "keywords": ["soil degradation processes", "National", "MensMeu", "Gebieden met natuurrisico's", "ondergrond", "bodemerosie", "erosie", "DOV", "Vlaanderen", "Ondergrond", "Databank Ondergrond Vlaanderen", "Regionaal", "Herbruikbaar", "Kosteloos", "Vlaamse Open data", "Toegevoegd GDI-Vl", "Metadata GDI-Vl-conform", "Metadata INSPIRE-conform", "Lijst M&R INSPIRE", "Belgium", "soil erosion"], "contacts": [{"name": "Koning Albert", "organization": "Bureau for Environment and Spatial Development \u2013 Flanders", "position": null, "roles": ["pointOfContact"], "phones": [{"value": null}], "emails": [{"value": "vpo.omgeving@vlaanderen.be"}], "addresses": [{"deliveryPoint": ["Koning Albert II-laan 20 bus 8"], "city": "Brussel", "administrativeArea": null, "postalCode": "1000", "country": "Belgium"}], "links": [{"href": {"url": "https://www.omgevingvlaanderen.be", "protocol": null, "protocol_url": "", "name": null, "name_url": "", "description": null, "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Vlaamse Overheid - 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The map is the sum of water and tillage erosion. The map takes into account 4 types of land use: forest, permanent cover, agricultural crops without permanent cover and other land use. The map is based on the soil erosion map aggregated for each agricultural parcel in Flanders (2010).  The original map on parcel level is a product of computer modeling with a spatial resolution of 5 m * 5 m by the \"Physical and Regional Geography Division, Department of Earth and Environmental Sciences, K.U. Leuven\". The calculation of water erosion is based on the Revised Soil Loss Equation (RUSLE, Renard et al., 1991) using a 2 dimensional approach for calculating the LS factor based on Desmet and Govers (1996).  The water erosion is calculated with a crop factor of 0,001 for forest, a crop factor of 0,01 for permanent cover (excluding forest), a crop factor of 0,37 for other agricultural crops and a crop factor of 0 for other land use. Tillage erosion is calculated according to the WaTEM/SEDEM model based on Van Oost et al. (2000).", "protocol": "ogc:wms", "rel": null}, {"href": "https://github.com/ejpsoil/ejpsoildatahub/tree/main/datasets/mensmeu/Belgium/70f368f8-db6e-430d-9ae4-fe0acd55.yml", "name": "Source of the record", "protocol": "canonical", "rel": "canonical"}, {"rel": "self", "type": "application/geo+json", "title": "70f368f8-db6e-430d-9ae4-fe0acd55fe52", "name": "item", "description": "70f368f8-db6e-430d-9ae4-fe0acd55fe52", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/70f368f8-db6e-430d-9ae4-fe0acd55fe52"}, {"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": "836f001d-da7e-489a-bf8b-fb798be61231", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:29:17Z", "type": "Dataset", "language": "nl", "title": "SERENA EJPSOIL BE Flanders SOCLOSS SOC 0-20cm cookbook", "description": "This SERENA dataset (100 m resolution) of soil orgnanic carbon concentration (0-20 cm soil layer) for Flanders was mainly produced to test the methodology of the SERENA SOC loss cookbook of the European SERENA EJP SOIL project. The data was prepared according to the methodology of SERENA SOC loss cookbook. The objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. Soil organic carbon concentration was used as an indicator for soil organic carbon loss (ST). The map was based on digital soil mapping according to the method used in the EJP SOIL project WP6: Digital soil mapping approach with random forest using ISRIC workflow seedling. To create the soil organic carbon concentration map, we used soil organic carbon data of the regional soil organic carbon monitoring network Cmon in Flanders (0-10 and 10-30 cm soil layer). The soil organic carbon concentration of the 0-20 cm was derived from the 0-10 and 10-30 cm data. The following auxiliary data was used: Digital soil map of the Flemish Region: soil types; Regional climate data; Land use - Flanders - state 2022; Tertiary geological map (1/50,000); Ground cover map (BBK), 1m resolution, recording 2021; WRB Soil Units 40k: Soil map of the Flemish Region according to the international soil classification system World Reference Base on a scale of 1:40,000; The dataset will be mostly useful as a reference result for actors that want to learn to implement the part of the soil organic carbon loss cookbook of SERENA dealing with the creation of a SOC concentration map. 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Voor een volledige weergave van alle attribuutinformatie van de bodemprofielen wordt verwezen naar de volledige Aardewerk-Vlaanderen-2010 databank. Aardewerk-Vlaanderen-2010 is een databank met de beschrijving en analyseresultaten van 7.020 bodemprofielen en 42.529 geassocieerde bodemhorizonten, aangevuld met 9.281 oppervlaktemonsters, allen gesitueerd op het grondgebied Vlaanderen en Brussel. Deze gegevens (143 variabelen) werden verzameld tijdens de systematische bodemprofielstudie, die tussen 1949 en 1971 werd uitgevoerd in Belgi\u00eb, onder auspici\u00ebn van het Instituut tot aanmoediging van het Wetenschappelijk Onderzoek in Nijverheid en Landbouw. 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De totale potenti\u00eble erosie houdt geen rekening met het huidige landgebruik (grasland of akkerland). In het veld \u2018Erosiegevoeligheid verzamelaanvraag\u2019 staat de informatie die overeenkomt met de erosiegevoeligheid op de verzamelaanvraag 2018. De goedgekeurde bezwaren werden zowel in het veld 'Erosiegevoeligheid verzamelaanvraag' als in het veld 'Totale erosie' verwerkt. De goedgekeurde aanvragen van de verlaging van de erosiegevoeligheidsklasse op basis van een hoog koolstofgehalte werden in het veld 'Erosiegevoeligheid verzamelaanvraag' verwerkt met aanduiding van \u2018/ C\u2019 achter de erosiegevoeligheid, maar het veld 'Totale erosie' behield zijn oorspronkelijke waarde voor deze percelen.\nErosie door water is een proces waarbij bodemdeeltjes door de impact van regendruppels en afstromend water worden losgemaakt en getransporteerd, hetzij laagsgewijs over een grote oppervlakte, hetzij geconcentreerd in geulen en ravijnen. 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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:FOLDERPATH"}, {"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 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"Spain"}, {"id": "Finland"}, {"id": "Belgium"}, {"id": "Sweden"}, {"id": "Poland"}, {"id": "Luxembourg"}, {"id": "Netherlands"}, {"id": "Slovakia"}], "scheme": "Continents, countries, sea regions of the world."}, {"concepts": [], "scheme": "Temporal resolution"}, {"concepts": [{"id": "European"}], "scheme": "http://inspire.ec.europa.eu/metadata-codelist/SpatialScope"}, {"concepts": [{"id": "Land use"}], "scheme": "https://www.eea.europa.eu/themes"}], "updated": "2025-10-09T11:22:40.120411Z", "type": "Dataset", "created": "2020-10-07T00:00:00", "language": "eng", "title": "Concentrations of heavy metals in European agricultural soils, Oct. 2020", "description": "This data set contains current and critical metal concentrations and its exceedances in topsoils, as well as data related to the current and critical metal inputs to and outputs from soils (uptake, accumulation and leaching) and the resulting exceedances of critical metal inputs. \n\nThis data set has been compiled by the 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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 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:FOLDERPATH"}, {"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", 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