GEOGCS['GCS_WGS_1984', DATUM['D_WGS_1984', SPHEROID['WGS_1984',6378137,298.257223563]], PRIMEM['Greenwich',0], UNIT['Degree',0.017453292519943295]] (base) [jbk@theseus ltar_regionalization]$ g.proj -w GEOGCS['wgs84', DATUM['WGS_1984', SPHEROID['WGS_1984',6378137,298.257223563]], PRIMEM['Greenwich',0], UNIT['degree',0.0174532925199433]] Annual stocks.
Each of these 13 years is 3TB when extracted. So that is 39 TB as a tif.
We needed to use file geodatabase format to compress enough to post on the Dataverse. Hence no TIffs.", "keywords": ["Earth and Environmental Sciences", "Raster", "ArcGIS file Geodatabase rasters", "Global Mangrove Carbon"], "contacts": [{"organization": "Hamilton, Stuart", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/T8CMAT"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/T8CMAT", "name": "item", "description": "10.7910/DVN/T8CMAT", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/T8CMAT"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-01-01T00:00:00Z"}}, {"id": "18968587-3633-4987-a27a-685862803552~~1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:33:59Z", "type": "Dataset", "language": "de", "title": "GcB\u00dcK400 \u2014 arsenic in the upper floor", "description": "Arsenic is a semi-metal, ubiquitous and toxic element. It is widely found in nature in various mineralisations as arsenic sulphide or oxide and as copper, nickel and iron arsenate. The average As content of the rocks of the upper continental crust (Clark value) is 2\u00a0mg/kg. In the literature, As levels 20\u00a0mg/kg are described as normal levels, the mean content being about 5\u00a0mg/kg. Among the toxic elements, the arsenic is particularly important due to its large spread of increased content in Saxon soils. The causes are undoubtedly to be found in the geochemical-metallogenetic specialisation of the Fichtelgebirgisch Erzgebirgic Anticlinal Zone. The area-related mean A content of the main rock types (petrogeochemical component) is approximately 13\u00a0mg/kg. The chalkogenic component is of particular importance in the Ore Mountains. In addition to the element enrichment in the mineralisation itself, which was the subject of mining, there was also a large-scale influence on the side rocks or their weathering products (primary and secondary geochemical aureoles). The anthropogenic influence of natural soils is mainly due to the ore treatment plants and the emissions of non-ferrous metalworks. Whereas low levels dominate in the upper soils of North and in parts of central axis (as-poor periglaciary sandy to loamy substrates; L\u00f6ss), a relative enrichment occurs in the weathering soils via solid rocks as a result of the higher petrogenic A component. Important regional anomalies are mainly located in the Freiberg region (Osterzgebirge), the most important site of mining and the smelting of polymetallic ores, as well as in the West Ore Mountains (Aure \u2014 Ehrenfriedersdorf area). The great extent and intensity of the spread of As minerals in polymetallic, tin-tungsten and bi-co-Ni-Ag-U ore formations, as well as their prevention, led to large-scale geogenic and anthropogenic enrichments. Both areas are separated by the north-south-souting Fl\u00f6ha zone, an area in which hardly any ore mineralisations occur and thus the chalkogenic component is rarely developed. Large-area elevated As levels in soils of the Vorerzgebirgssenke (Zwickau \u2014 Chemnitz) are due to the geochemically specialised rotary sediments (including removal products of the Ore Mountains). Particularly high levels of As are common in the meadows of the Freiberger Mulde, Zschopau, Zwickauer Mulde and the United Mulde. Due to the geological process of the removal of soils from the ore-mounted deposits as well as anthropogenic inputs by the ore processing and metallurgy industry, the deposit of the river sediments and swine parts in the flooding areas leads to constant as-enrichment in the floodplains. As a result of the geogenic and anthropogenic processes described above, the test and measure values of the Federal Soil Protection and Contaminant Ordinance (BBodSchV) for arsenic are sometimes exceeded.", "keywords": ["anorganischer-schadstoff", "arsen", "boden", "chemie", "chemisches-element", "de", "geologie", "opendata"]}, "links": [{"href": "https://luis.sachsen.de/boden/geodatendownload.html"}, {"href": "http://data.europa.eu/88u/dataset/18968587-3633-4987-a27a-685862803552~~1"}, {"href": "https://geoportal.sachsen.de/md/18968587-3633-4987-a27a-685862803552"}, {"rel": "self", "type": "application/geo+json", "title": "18968587-3633-4987-a27a-685862803552~~1", "name": "item", "description": "18968587-3633-4987-a27a-685862803552~~1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/18968587-3633-4987-a27a-685862803552~~1"}, {"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": "10.1021/acs.est.3c01816", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:17:58Z", "type": "Journal Article", "created": "2023-09-08", "title": "Effects of Climate Change on Soil Organic Matter C and H Isotope Composition in a Mediterranean Savannah (Dehesa): An Assessment Using Py-CSIA", "description": "Dehesas are Mediterranean agro-sylvo-pastoral systems sensitive to climate change. Extreme climate conditions forecasted for Mediterranean areas may change soil C turnover, which is of relevance for soil biogeochemistry modeling. The effect of climate change on soil organic matter (SOM) is investigated in a field experiment mimicking environmental conditions of global change scenarios (soil temperature increase, +2-3 \u00b0C, W; rainfall exclusion, 30%, D; a combination of both, W+D). Pyrolysis-compound-specific isotope analysis (Py-CSIA) is used for C and H isotope characterization of SOM compounds and to forecast trends exerted by the induced climate shift. After 2.5 years, significant \u03b413C and \u03b42H isotopic enrichments were detected. Observed short- and mid-chain n-alkane \u03b413C shifts point to an increased microbial SOM reworking in the W treatment; a 2H enrichment of up to 40\u2030 of lignin methoxyphenols was found when combining W+D treatments under the tree canopy, probably related to H fractionation due to increased soil water evapotranspiration. Our findings indicate that the effect of the tree canopy drives SOM dynamics in dehesas and that, in the short term, foreseen climate change scenarios will exert changes in the SOM dynamics comprising the biogeochemical C and H cycles.", "keywords": ["2. Zero hunger", "Take urgent action to combat climate change and its impacts", "Analytical pyrolysis", "Climate Change", "biomarkers", "nalyticalpyrolysis", "15. Life on land", "Mediterranean soil", "Trees", "\u03b42H", "\u03b413C \u03b42H", "Soil", "Isotopes", "13. Climate action", "Alkanes", "\u03b413C", "Climate change", "http://metadata.un.org/sdg/13", "climatechange", "Biomarkers", "Pyrolysis"]}, "links": [{"href": "https://pubs.acs.org/doi/pdf/10.1021/acs.est.3c01816"}, {"href": "https://doi.org/10.1021/acs.est.3c01816"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20%26amp%3B%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1021/acs.est.3c01816", "name": "item", "description": "10.1021/acs.est.3c01816", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1021/acs.est.3c01816"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-09-08T00:00:00Z"}}, {"id": "10.5281/zenodo.4542881", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:24:29Z", "type": "Dataset", "title": "Total and partitioned soil respiration and below-ground carbon budget in SAFE intensive carbon plots", "description": "Description: This dataset contains two parts:
1) 'data' worksheet: measured soil respiration, values of individual measurements across all plots.
2) 'Soil C cycle' worksheet: calculated summaries of the components of the below-ground carbon cycle, including total and component soil respiration (this study), soil carbon pools and flows of organic carbon (previous studies). These data form the basis of the below-ground carbon cycle in Riutta et al 2021 GBC. This sheet contains mean values in each 1 ha carbon plot. This worksheet include two addititional carbon plots from Lambir Hills National Park (see Kho et al. 2013 JGR), which are not part of the SAFE Project.
SAFE Intensive Carbon Plots, part of the Global Ecosystem Monitoring (GEM) network, see http://gem.tropicalforests.ox.ac.uk/.
Total soil respiration is measured at 25 points per plot, in the middle of each subplot (16 points per plot in OP, in subplot corners), using PVC collars of 10.65 cm internal diameter, inserted into approximately 5 cm depth.
Partitioned respiration is measured at four points per plot, a using a cluster of six collars (see below).
Disturbance experiment in the plot centre to assess the potential bias on fluxes caused by the collar installation.
All the methods and installation is described in detail in the GEM Intensive Carbon Plots manual, available at http://gem.tropicalforests.ox.ac.uk/files/rainfor-gemmanual.v3.0.pdf.
The aim is to measure monthly, but in practice the measurement interval is almost always longer (problems with access, staffing and instruments).
EGM-4 infrared CO2 analyser and SRC-1 respiration chamber (PP Systems).
Chamber closure time is 124 seconds, CO2 concentration inside the chamber is recorded every 5 s. Flux is calculated from the linear change in concentration in the chamber headspace.
Conversion from parts per million (ppm) of total gas volume per second per unit collar area to mega grams (1 Mg = 10^6 g) of carbon per hectare per month.
Idea gas law: pV=nRT --> n=pV/(RT)
Mass-Mole: n=m/M --> m=n*M
Combined: m=MpV/(RT)
p (constant) 101,325
R (constant) 8.314472
T temperature in Kelvins --> AirT_Use + 273.15
V headspace volume
M_carbon 12.01
parts per million to absolute units 10^-6
A collar area, m2 0.008825
m2 to hectare 10^4
grams to megagrams 10^-6
seconds to months 2592000
Flux_MgCha-1month-1 = Slope_ppm_s-1 * M* p* V /(R*T) * 10^-6 / A * 10^4 * 10^-6 * 2592000
Soil collar codes Partitioned respiration
C1 All soil respiration components: litter, roots, mycorrhiza, soil organic matter (SOM)
C2 Roots excluded (litter, mycorrhiza, SOM)
C3 Roots and mycorrhiza excluded (litter, SOM)
S1 Litter excluded (roots, mycorrhiza, SOM)
S2 Litter and roots excluded (mycorrhiza, SOM)
S3 Litter, roots and mycorrhiza excluded (only SOM)
D1 Double litter, roots, mycorrhiza, soil organic matter (SOM)
D2 Roots excluded (double litter, mycorrhiza, SOM)
D3 Roots and mycorrhiza excluded (double litter, SOM)
X Organic layer of the soil removed
Disturbance The purpose of the disturbance experiment is to quantify how much disturbance the removal of the roots and mixing the soil causes, compared to just hammering in the deep collar
ND1 Roots severed, not removed and soil not mixed at the installation
ND2 ND1-ND5 are replicates, same treatmet
ND3
ND4
ND5
D1 Roots removed, soil mixed at the installation
D2 D1-D5 are replicates
D3
D4
D5
Project: This dataset was collected as part of the following SAFE research project: Changing carbon dioxide and water budgets from deforestation and habitat modificationFunding: These data were collected as part of research funded by: Sime Darby Foundation (Grant, SAFE Core data)European Research Council Advanced Investigator Grant, GEM-TRAIT (Grant, Grant number 321131)NERC Human-Modified Tropical Forests Programme: Biodiversity And Land-use Impacts on tropical ecosystem function (BALI) Project (Grant, NE/K016369/1)NERC standard grant: The multi-year impacts of the 2015/2016 El Ni\u00f1o on the carbon cycle of tropical forests worldwide (Grant, NE/P001092/1)HSBC Malaysia (Grant)The University of Zurich (Grant)This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.Permits: These data were collected under permit from the following authorities:Sabah Biodiversity Council (Research licence JKM/MBs.1000-2/2 JLD.6 (76))XML metadata: GEMINI compliant metadata for this dataset is available hereFiles: This dataset consists of 2 files: SAFE_SoilRespiration_Data_SAFEdatabase_update_2021-01-11.xlsx, SAFE_soil_DATA.zipSAFE_SoilRespiration_Data_SAFEdatabase_update_2021-01-11.xlsxThis file contains dataset metadata and 2 data tables:Soil respiration data (described in worksheet data)Description: Soil respiration data by individual measurementsNumber of fields: 21Number of data rows: 20602Fields: ForestType: Old-growth, Logged or Oil palm (Field type: categorical)SAFEPlotName: SAFE plot name (Field type: location)PlotName: Plot name (Field type: id)ForestPlotsCode: Plot code in the ForestPlots database (this should be used in publications, instead of plot name). OP plot is not in the ForestPlots database (ForestPlotsCode = NA) (Field type: id)Date: Measurement date (dd/mm/yyyy) (Field type: date)Observers: Observers (Field type: comments)Subplot: Subplot number within each plot, 1-25 (in OP, because the total respiration collars are in subplot corners, no subplot numbers are used, but the collars are refered to as SR1 - SR16. Subplot numbers are used for the partitioned respiration) (Field type: id)MeasurementType: Total, Partitioned or Disturbance (Field type: categorical)CollarType: Total; Partitioned: C1, C2, C3, S1, S2, S3, D1, D2, D3, X; Disturbance: ND1, ND2, ND3, ND4, ND5, D1, D2, D3, D4, D5 (see metadata description for codes) (Field type: id)EGM_RecordNumber: Record number in of the raw flux file. (Field type: id)SoilMoisture: Volumetric soil moisture content (% of pore space) next to the collar. measured with Campbell Scientific Hydrosense sensor with 12 cm rods. (Field type: numeric)SoilT: Soil temperature (\u00b0C) is measured with a handheld digital thermometer next to the collar, inserted into 10 cm depth (Field type: numeric)AirT: Air temperature (\u00b0C) is measured with a handheld digital thermometer outside the chamber, at the chamber height, in a shaded spot (Field type: numeric)Slope: Slope of the linear regression between time (seconds) from the chamber closure and CO2 concentration (parts per million, ppm) in the chamber headspace. (Field type: numeric)Remarks: Any notes in the field or at data entry stage. 0 = no remarks. If the measurement is repeated in the field multiple times, the other flux estimates are sometimes written in the remarks (not consistent). 2x, 3x etc. indicate multiple repeats. (Field type: comments)CollarHeight: Height from the top of the soil to the top of the collar, mm. This is used for calculating the total headspapce volume (chamber volume + collar volume above the soil surface). (Field type: numeric)HeadspaceVolume: Total headspace volume, sum of the chamber volume (0.001229 m3) and collar volume (d=0.106 m, h=CollarHeight_mm/1000) (Field type: numeric)AirT_Use: Gap filled air temperature data, missing air temperatures replaced with average temperature in logged (27.1), old-growth forest (26.2) and OP (28.7). This is needed for calculating the flux, but should not be used in response functions etc. (Field type: numeric)Flux: Flux corverted from ppm s-1 to Mg carbon per hectare per month. See conversion below. (Field type: numeric)Quality: 1 - good flux; 0 - missing data or bad measurement; 2 - outlier (Field type: numeric)Girdling_0_1: In Tower Plot (SAF-05), subplots 14-25, all trees were girdled in late January - early February 2016. Post-girdling data = 1, if no girdling = 0. (Field type: numeric)Soil carbon cycle (described in worksheet Soil C cycle)Description: Estimates of soil carbon pools (fine and coarse root biomass, root and litter necromass, soil organic carbon); fluxes of organic carbon into and respiration out of the different pools. Values are means for each intensive carbon plot.Number of fields: 41Number of data rows: 11Fields: ForestType: Old-growth, Logged or Oil palm (Field type: categorical)SAFEPlotName: SAFE plot name, as in the SAFE Gazetteer (Field type: location)PlotName: Plot name (used in field work) (Field type: id)ForestPlotsCode: Plot code, as in the ForestPlots database (this should be used in publications, instead of plot name) (Field type: id)SOC_0to100cm: Soil carbon stock, 0-100 cm layer (Field type: numeric)CanopyStock: Biomass stock of the canopy (Field type: numeric)LitterStock: Necromass stock of the litter layer (leaf, branch and reproductive litter) (Field type: numeric)NPP_Canopy: Canopy net primary productivity (Field type: numeric)CanopyHerbivory: Canopy herbivory (Field type: numeric)Litterfall: Canopy litterfall (leaves, reproductive parts, twigs < 2 cm diameter) (Field type: numeric)Frassfall1: Frassfall, 1st literature estimate (Field type: numeric)Frassfall2: Frassfall, 2nd literature estimate (Field type: numeric)Frassfall_Mean: Frassfall, mean of the Frassfall 1 and Frassfall 2 (Field type: numeric)FineRootStock: Fine root biomass stock (Field type: numeric)CoarseRootStock: Coarse root biomass stock (Field type: numeric)Delta_FRstock: Change in fine root biomass stock in logged forest (old-growth forest stock assumed to be in quasi-equilibrium) (Field type: numeric)Delta_CRstock: Change in coarse root biomass stock in logged forest (old-growth forest stock assumed to be in quasi-equilibrium) (Field type: numeric)NPP_FR: Fine root net primary productivity (Field type: numeric)NPP_CR: Coarse root net primary productivity (Field type: numeric)Mortality_FR: Fine root mortality (Field type: numeric)Mortality_CR: Coarse root mortality (Field type: numeric)R_Tot: Total soil respiration (litter, roots, mycorrhiza, soil organic matter) (Field type: numeric)R_SOM: Soil organic matter respiration (Field type: numeric)R_Litter: Litter layer respiration (Field type: numeric)R_Root: Root and priming respiration (Field type: numeric)R_Myc: Mycorrhizal respiration (Field type: numeric)R_Rhizosphere: Rhizosphere respiration (Field type: numeric)R_FRdebris: Fine root debris (recently dead, < 1 year) respiration (Field type: numeric)R_CRdebris: Coarse root debris (recently dead, < 1 year) respiration (Field type: numeric)R_RootTurnover: Root turnover respiration (sum of fine and coarse root debris respiration) (Field type: numeric)R_Het: Heterotrophic respiration (Field type: numeric)Exudation1: Root exudation, 1st literature estimate (Field type: numeric)Exudation2: Root exudation, 2nd literature estimate (Field type: numeric)Exudation3: Root exudation, 3rd literature estimate (Field type: numeric)Exudation4: Root exudation, 4th literature estimate (Field type: numeric)Exudation5: Root exudation, 5th literature estimate (Field type: numeric)Exudation_Mean: Root exudation, mean of the five literature-based estimates (Field type: numeric)LitterToSOM: Litter inputs (> 1 year old material) to soil organic matter (Field type: numeric)FRdebrisToSOM: Fine root debris inputs (> 1 year old material) to soil organic matter (Field type: numeric)CRdebrisToSOM: Coarse root debris inputs (> 1 year old material) to soil organic matter (Field type: numeric)OrgInputsToSOM: Total labile organic inputs (> 1 year old material) to soil organic matter (Field type: numeric)SAFE_soil_DATA.zipDescription: Raw EGM files and a ReadMe doc explaining how to interpret Date range: 2011-08-25 to 2018-07-17Latitudinal extent: 4.1830 to 5.0700Longitudinal extent: 114.0190 to 117.8200", "keywords": ["570", "Soil carbon cycle", "Soil organic matter", "Flux", "Total respiration", "Soil respiration", "15. Life on land", "Partioned respiration", "Autotrophic respiration", "Roots", "6. Clean water", "630", "SAFE core data", "Below-ground", "Carbon dioxide", "SAFE project", "Heterotropchic respiration", "Litter", "Soil temperature", "CO2", "Carbon plot", "Soil moisture"], "contacts": [{"organization": "Riutta, Terhi, Ewers, Robert M, Malhi, Yadvinder, Majalap, Noreen, Khoon, Kho Lip,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4542881"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4542881", "name": "item", "description": "10.5281/zenodo.4542881", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4542881"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-16T00:00:00Z"}}, {"id": "c7970c8d-3eaa-42e4-8373-dbdf44f28d34", "type": "Feature", "geometry": null, "properties": {"updated": "2024-11-09T00:00:00Z", "type": "Dataset", "language": "nl", "title": "Soil Organic Carbon Stock Maps for Belgium: standard deviation (1 km grid)", "description": "The Belgian soil organic carbon (SOC) stock map for topsoils (0-30 cm) was composed of 2 regional SOC stock maps. 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. Given the different origins 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\". The 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.", "formats": [{"name": "KML"}], "keywords": ["High value dataset", "akker", "be", "bodem", "bos", "databank-ondergrond-vlaanderen", "departement-omgeving", "dov", "grasland", "koolstof", "landbouw", "ondergrond", "totaal-aan-organische-koolstof", "vlaanderen"], "contacts": [{"organization": "Vlaamse overheid, Departement Omgeving, Vlaams Planbureau voor Omgeving (VPO)", "roles": ["creator"]}, {"organization": "https://org.belgif.be/id/CbeEstablishmentUnit/2143719695", "roles": ["publisher"]}]}, "links": [{"href": "https://metadata.vlaanderen.be/srv/dut/catalog.search#/metadata/8626aca9-9d5e-414d-92e0-351b0d8d7ba2"}, {"href": "https://www.vlaanderen.be/DataCatalogRecord/8626aca9-9d5e-414d-92e0-351b0d8d7ba2"}, {"href": "http://data.europa.eu/88u/dataset/c7970c8d-3eaa-42e4-8373-dbdf44f28d34"}, {"rel": "self", "type": "application/geo+json", "title": "c7970c8d-3eaa-42e4-8373-dbdf44f28d34", "name": "item", "description": "c7970c8d-3eaa-42e4-8373-dbdf44f28d34", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/c7970c8d-3eaa-42e4-8373-dbdf44f28d34"}, {"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": "caa134ea-ce26-4e82-a48e-8bd5c35c467e~~1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:34:03Z", "type": "Dataset", "language": "de", "title": "GcB\u00dcK400 \u2014 Copper in the upper floor", "description": "Copper is an essential element for the diet of all living beings, which, however, can lead to toxic effects in the event of an extreme oversupply. The mean Cu content of the rocks of the upper continental crust (Clark value) is 14\u00a0mg/kg. Analogous to chromium and nickel, it is mainly enriched in basic rocks (Diabase, Basalte, Metabasite). The mean Cu content (mediane) of the main Saxon rock types ranges from 2 to 67\u00a0mg/kg, and the regional Clarke of the Ore Mountains/Vogtland is 23\u00a0mg/kg. Geogenic Cu enrichments can be found mainly in the Ore Mountains via the widely used mineralisations here. Chalkopyrite (copper jaw) is common in almost all mineral associations as so-called pass-through minerals. Strong anthropogenic Cu entries are mainly caused by non-ferrous metallurgy. Due to the diverse use of Cu, e.g. in electrical engineering, as alloy metal, piping material and rain gutters, the element is also increasingly entered into the wastewater. For uncontaminated soils Cu levels from 2 to 40\u00a0mg/kg are considered normal. The regional distribution of Cu levels in the upper soil is mainly determined by the geogenic proportion of substrates. Due to the increased Cu levels of the diabase widespread in the Vogtland (58\u00a0mg/kg), the point-like tertiary basaltoids (60\u00a0mg/kg) and the locally stored amphibolites (46\u00a0mg/kg) of the metamorphic basement, there is anomalously high Cu content in the weathering soils above the said solid rocks. Increased solubility influence (with relatively low Cu content of about 12\u00a0mg/kg) can lead to a \u201cdilution effect\u201d via Cu-rich substrates, depending on the proportion of the solution (e.g. via the monzonitoid at bites). Extremely low Cu concentrations can be observed in weathering soils over acidic magmatites (Granite of Ei-Benstock, Teplice-Rhyolite), metagranitoids (central zone of ore), sandstones (Elbe sandstone and Zittau mountains) and soil societies from periglaciar sandy deck sediments in northern axes. Important regional anomalies are mainly located in the Freiberg region, the most important former site of mining and the smelting of polymetallic ores. However, the anthropogenic entries are usually limited to the immediate vicinity of the metallurgical sites. This leads to overlay with geogenic proportions in the soil, which are causally linked to the spread of copper gravel leading mineral associations. Analogous conditions can be found, albeit in a weakened form, in the Schneeberg \u2014 Schwarzenberg \u2014 Annaberg-Buchholz \u2014 Marienberg area. Especially high Cu-contents have the meadow soils of the Freiberger Mulde. After the entry of the Freiberger Mulde into the Freiberg mining and metallurgy area, there is a sustainable material burden on the floodplains, which extends across the Aue of the United Mulde to the northern border. Increased Cu levels, but at a much lower level, also occur in the floodplains of the Zwickau Mulde, where the polymetallic mineralisations of the West Ore Mountains are located in the catchment area. As a result of the geogenic and anthropogenic processes described above, in the meadows of the Freiberger and the United Mulde, the measures of the Federal Soil Protection and Contaminant Ordinance (BBodSchV) for grassland use (sheep farming) are partially exceeded.", "keywords": ["anorganischer-schadstoff", "boden", "chemie", "chemisches-element", "cu", "de", "geologie", "kupfer", "opendata"]}, "links": [{"href": "https://luis.sachsen.de/boden/geodatendownload.html"}, {"href": "http://data.europa.eu/88u/dataset/caa134ea-ce26-4e82-a48e-8bd5c35c467e~~1"}, {"href": "https://geoportal.sachsen.de/md/caa134ea-ce26-4e82-a48e-8bd5c35c467e"}, {"rel": "self", "type": "application/geo+json", "title": "caa134ea-ce26-4e82-a48e-8bd5c35c467e~~1", "name": "item", "description": "caa134ea-ce26-4e82-a48e-8bd5c35c467e~~1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/caa134ea-ce26-4e82-a48e-8bd5c35c467e~~1"}, {"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": "f3ff636e-ef22-40a3-9a25-1779d864ecf8", "type": "Feature", "geometry": null, "properties": {"license": "http://dcat-ap.de/def/licenses/cc-by/4.0", "updated": "2025-05-27T00:00:00Z", "type": "Dataset", "language": "de", "title": "Soils worthy of protection in Lower Saxony 1 : 50 000 - Soils with high natural soil fertility", "description": "Soils that are particularly worthy of protection include soils that fulfil the natural functions as well as the archiving function to a particular extent. According to soil protection law, impairments of these functions should be avoided (cf. \u00a71 BBodSchG). A key factor in assessing a soil's habitat function is its natural fertility. It characterizes the potential of the soil for the production of biomass. Soils with very high natural soil fertility are considered particularly worthy of protection. They enable land management with low inputs. This in turn contributes to the sustainable safeguarding of the performance of the natural balance. The designated specially protected floors on the basis of the BK50 represent search spaces on a scale. If necessary, these can be differentiated in more detail within the framework of large-scale mapping. The methods for determining the protection of soils in Lower Saxony are described in detail in Geoberichte 8 (Bug et al. 2019) is described. The evaluations are based on the soil map of Lower Saxony 1 : 50 000 (BK50). These are soils with a high to extremely high soil fertility in a national comparison (levels 5-7). In order to meet the different landscapes of Lower Saxony, the analysis is differentiated according to soil regions (cf. georeports 8). The evaluation is carried out using the NIBIS\u00ae evaluation method \u2018soil fertility\u2019 (cf. georeports 19). It determines soil fertility on the basis of the soil water balance and the nutrient supply of a site. The assessment is differentiated for arable, grassland and forest soils over the different effective root space of the vegetation. Soils with a regionally high fertility, but which have only a medium fertility in a national comparison, can only be covered to a limited extent with this approach. For regional or municipal considerations, Geoberichte 26 offers an adapted methodology.", "formats": [{"name": "TIFF"}], "keywords": ["boden", "de", "inspireidentifiziert", "nibis-metadaten", "opendata", "regional", "sgd_boden"], "contacts": [{"organization": "Landesamt f\u00fcr Bergbau, Energie und Geologie (LBEG)", "roles": ["creator"]}]}, "links": [{"href": "https://nibis.lbeg.de/net3/public/ogc.ashx?NodeId=1009&Service=WFS&Request=GetCapabilities&"}, {"href": "http://data.europa.eu/88u/dataset/f3ff636e-ef22-40a3-9a25-1779d864ecf8~~1"}, {"rel": "self", "type": "application/geo+json", "title": "f3ff636e-ef22-40a3-9a25-1779d864ecf8", "name": "item", "description": "f3ff636e-ef22-40a3-9a25-1779d864ecf8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/f3ff636e-ef22-40a3-9a25-1779d864ecf8"}, {"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": "PMC6668394", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:29:51Z", "type": "Journal Article", "created": "2019-07-31", "title": "A new global gridded anthropogenic heat flux dataset with high spatial resolution and long-term time series", "description": "Abstract
Exploring global anthropogenic heat and its effects on climate change is necessary and meaningful to gain a better understanding of human\uffe2\uff80\uff93environment interactions caused by growing energy consumption. However, the variation in regional energy consumption and limited data availability make estimating long-term global anthropogenic heat flux (AHF) challenging. Thus, using high-resolution population density data (30 arc-second) and a top-down inventory-based approach, this study developed a new global gridded AHF dataset covering 1970\uffe2\uff80\uff932050 based historically on energy consumption data from the British Petroleum (BP); future projections were built on estimated future energy demands. The globally averaged terrestrial AHFs were estimated at 0.05, 0.13, and 0.16\uffe2\uff80\uff89W/m2 in 1970, 2015, and 2050, respectively, but varied greatly among countries and regions. Multiple validation results indicate that the past and future global gridded AHF (PF-AHF) dataset has reasonable accuracy in reflecting AHF at various scales. The PF-AHF dataset has longer time series and finer spatial resolution than previous data and provides powerful support for studying long-term climate change at various scales.Arctic and alpine tundra ecosystems are large reservoirs of organic carbon1,2. Climate warming may stimulate ecosystem respiration and release carbon into the atmosphere3,4. The magnitude and persistency of this stimulation and the environmental mechanisms that drive its variation remain uncertain5\uffe2\uff80\uff937. This hampers the accuracy of global land carbon\uffe2\uff80\uff93climate feedback projections7,8. Here we synthesize 136 datasets from 56 open-top chamber in situ warming experiments located at 28 arctic and alpine tundra sites which have been running for less than 1\uffe2\uff80\uff89year up to 25\uffe2\uff80\uff89years. We show that a mean rise of 1.4\uffe2\uff80\uff89\uffc2\uffb0C [confidence interval (CI) 0.9\uffe2\uff80\uff932.0\uffe2\uff80\uff89\uffc2\uffb0C] in air and 0.4\uffe2\uff80\uff89\uffc2\uffb0C [CI 0.2\uffe2\uff80\uff930.7\uffe2\uff80\uff89\uffc2\uffb0C] in soil temperature results in an increase in growing season ecosystem respiration by 30% [CI 22\uffe2\uff80\uff9338%] (n\uffe2\uff80\uff89=\uffe2\uff80\uff89136). Our findings indicate that the stimulation of ecosystem respiration was due to increases in both plant-related and microbial respiration (n\uffe2\uff80\uff89=\uffe2\uff80\uff899) and continued for at least 25\uffe2\uff80\uff89years (n\uffe2\uff80\uff89=\uffe2\uff80\uff89136). The magnitude of the warming effects on respiration was driven by variation in warming-induced changes in local soil conditions, that is, changes in total nitrogen concentration and pH and by context-dependent spatial variation in these conditions, in particular total nitrogen concentration and the carbon:nitrogen ratio. Tundra sites with stronger nitrogen limitations and sites in which warming had stimulated plant and microbial nutrient turnover seemed particularly sensitive in their respiration response to warming. The results highlight the importance of local soil conditions and warming-induced changes therein for future climatic impacts on respiration.Monthly rainfall erosivity maps (R-factor maps) of Switzerland with a spatial resolution of 100 m. The maps show the spatial and seasonal variability of rainfall erosivity in MJ mm ha\u207b\u00b9 h\u207b\u00b9 month\u207b\u00b9. Light shades of blue indicate a low erosive impact of rainfall and dark shades a high impact.
The monthly R-factors are based on precipitation measurements from 87 automatic gauging stations with measurement intervals of 10 minutes (average measuring period of 19.5 years per station). The stations cover all agricultural zones in Switzerland. To exclude the influence of snow, temperatures are also recorded at an hourly resolution for 71 stations or are derived from the nearest station.
A comparison of the 12 monthly R-factor maps shows that the summer months (June, July and August) have the highest rainfall erosivity values during the year. The Southern Alps (canton of Ticino), the mountain zones of the Northern Alps and parts of the valley zone have particularly high R-factors in this period. A proportion of 62% of Switzerland's annual rainfall erosivity is recorded between June and September. Identifying regions and periods in which rainfall with an increased erosive impact occurs enables targeted erosion control and a better understanding of the dynamics of erosion processes over the course of a year.
The development of monthly rainfall erosivity maps of Switzerland is described in detail in 'Regionalization of monthly rainfall erosivity patterns in Switzerland' by Schmidt et al. (Hydrology and Earth System Sciences: 20. 2016. pp. 4359\u20134373).", "formats": [{"name": "HTML"}], "keywords": ["amenagement-antierosif", "aufbewahrungs-und-archivierungsplanung-aap-bund", "aumento-delle-precipitazioni", "bgdi-bundesgeodaten-infrastruktur", "boden", "bodenerosion", "ch", "conservation-and-archiving-planning-aap-confederation", "controllo-dellerosione", "e-geoch", "erosion", "erosion-control", "erosion-du-sol", "erosione", "erosione-del-suolo", "erosionsschutz", "fsdi-federal-spatial-data-infrastructure", "ifdg-infrastruttura-federale-dei-dati-geografici", "ifdg-linfrastructure-federale-de-donnees-geographiques", "intensification-des-precipitations", "niederschlagserhohung", "pianificazione-della-conservazione-e-dellarchiviazione-aap-confederazione", "planification-de-la-conservation-et-de-larchivage-aap-confederation", "precipitation-enhancement", "soil", "soil-erosion", "sol", "suolo"], "contacts": [{"organization": "boden@bafu.admin.ch", "roles": ["creator"]}, {"organization": "https://opendata.swiss/organization/bundesamt-fur-umwelt-bafu", "roles": ["publisher"]}]}, "links": [{"href": "https://data.geo.admin.ch/browser/index.html#/collections/ch.bafu.niederschlagserosivitaet/items/niederschlagserosivitaet-feb"}, {"href": "https://map.geo.admin.ch/?layers=ch.bafu.niederschlagserosivitaet-feb"}, {"href": "https://wms.geo.admin.ch/?SERVICE=WMS&VERSION=1.3.0&REQUEST=GetCapabilities&lang=de"}, {"href": "https://wmts.geo.admin.ch/EPSG/3857/1.0.0/WMTSCapabilities.xml?lang=de"}, {"href": "https://www.researchgate.net/publication/309429881_Regionalization_of_monthly_rainfall_erosivity_patterns_in_Switzerland"}, {"href": "http://data.europa.eu/88u/dataset/053bcacc-0ae4-4e03-9a79-9e0ecb56cd77-bundesamt-fur-umwelt-bafu"}, {"rel": "self", "type": "application/geo+json", "title": "053bcacc-0ae4-4e03-9a79-9e0ecb56cd77-bundesamt-fur-umwelt-bafu", "name": "item", "description": "053bcacc-0ae4-4e03-9a79-9e0ecb56cd77-bundesamt-fur-umwelt-bafu", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/053bcacc-0ae4-4e03-9a79-9e0ecb56cd77-bundesamt-fur-umwelt-bafu"}, {"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": "05593b3b-b1f0-4601-bd44-9c4247324f78", "type": "Feature", "geometry": null, "properties": {"updated": "2024-06-28T00:00:00Z", "type": "Dataset", "language": "de", "title": "Floor overview map 1:200.000 Bavaria", "description": "The soil overview map of Bavaria 1:200,000 (B\u00dcK200-BY) was created by merging the soil overview map of the Federal Republic of Germany (B\u00dcK200), which is available nationwide in individual sheet sections and via the BGR. For the overall coverage of Bavaria, the individual sheets of the B\u00dcK200 were joined together, leaf boundaries were dissolved, individual areas were revised again and the contents of the respective map legends were merged, revised and streamlined. The B\u00dcK200-BY is available nationwide and cut-free, with a Bavarian-specific general legend. Differences in content to the individual sheets of the B\u00dcK200 are small and usually desired due to the regional approach. The B\u00dcK200 is based on the aggregation and generalisation of the overview map 1:25,000 (\u00dcBK25), which is also available nationwide. A dataset of reference profiles for the individual legend units is available.", "formats": [{"name": "Information"}], "keywords": ["boden", "bodenkarte", "de", "gdiby", "opendata", "umweltatlas"], "contacts": [{"organization": "Bayerisches Landesamt f\u00fcr Umwelt", "roles": ["creator"]}]}, "links": [{"href": "https://www.lfu.bayern.de/gdi/wms/boden/buek200by?REQUEST=GetCapabilities&SERVICE=WMS"}, {"href": "https://www.lfu.bayern.de/umweltdaten/geodatendienste/index.htm"}, {"href": "http://data.europa.eu/88u/dataset/05593b3b-b1f0-4601-bd44-9c4247324f78"}, {"rel": "self", "type": "application/geo+json", "title": "05593b3b-b1f0-4601-bd44-9c4247324f78", "name": "item", "description": "05593b3b-b1f0-4601-bd44-9c4247324f78", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/05593b3b-b1f0-4601-bd44-9c4247324f78"}, {"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": "056096e9-7e88-410e-b6a2-17754e4bc9b7", "type": "Feature", "geometry": null, "properties": {"updated": "2025-05-27T00:00:00Z", "type": "Dataset", "language": "de", "title": "Soils worthy of protection in Lower Saxony 1 : 50 000 - Rare soils", "description": "Die Karte zeigt die Bewertung der Schutzw\u00fcrdigkeit von B\u00f6den in Niedersachsen im Hinblick auf ihre Seltenheit. Zu den besonders schutzw\u00fcrdigen B\u00f6den z\u00e4hlen B\u00f6den, welche die nat\u00fcrlichen Funktionen sowie die Archivfunktion in besonderem Ma\u00dfe erf\u00fcllen. Beeintr\u00e4chtigungen dieser Funktionen sollen nach Bodenschutzrecht vermieden werden (vgl. \u00a71 BBodSchG). Als selten werden B\u00f6den gekennzeichnet, die infolge ungew\u00f6hnlicher Kombinationen der Standort-bedingungen (Ausgangsgestein, Klima, Relief) seltene Eigenschaften oder Auspr\u00e4gungen aufweisen (Bug et al. 2019). Um eine vielf\u00e4ltige Bodenlandschaft und damit ein Mosaik unterschiedlicher Standorteigenschaften zu erhalten, ist der Schutz seltener B\u00f6den fachlich geboten. Die ausgewiesenen besonders schutzw\u00fcrdigen B\u00f6den auf Basis der BK50 stellen ma\u00dfstabsbedingt Suchr\u00e4ume dar. Diese k\u00f6nnen bei Bedarf im Rahmen von gro\u00dfma\u00dfst\u00e4bigen Kartierungen detaillierter ausdifferenziert werden. Die Seltenheit von B\u00f6den wird in Niedersachsen in der Kulisse der besonders schutzw\u00fcrdigen B\u00f6den basierend auf der BK50 \u00fcber eine geringe fl\u00e4chenhafte Verbreitung sowie \u00fcber lokale oder regionale Besonderheiten abgebildet. Dem liegt neben einer statistischen Auswertung der Fl\u00e4chenanteile auch eine expertenbasierte Einsch\u00e4tzung zugrunde (Bug et al. 2019). Grundlage der Auswertungen ist die Bodenkarte von Niedersachsen 1 : 50 000 (BK50).", "formats": [{"name": "TIFF"}], "keywords": ["boden", "de", "inspireidentifiziert", "nibis-metadaten", "opendata", "regional", "sgd_boden"], "contacts": [{"organization": "Landesamt f\u00fcr Bergbau, Energie und Geologie (LBEG)", "roles": ["creator"]}]}, "links": [{"href": "https://nibis.lbeg.de/net3/public/ogc.ashx?NodeId=1012&Service=WFS&Request=GetCapabilities&"}, {"href": "http://data.europa.eu/88u/dataset/056096e9-7e88-410e-b6a2-17754e4bc9b7~~1"}, {"rel": "self", "type": "application/geo+json", "title": "056096e9-7e88-410e-b6a2-17754e4bc9b7", "name": "item", "description": "056096e9-7e88-410e-b6a2-17754e4bc9b7", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/056096e9-7e88-410e-b6a2-17754e4bc9b7"}, {"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": "056fedb4-93f8-4c0f-a586-044feea6362c", "type": "Feature", "geometry": null, "properties": {"updated": "2025-09-02T09:57:21", "type": "Dataset", "language": "de", "title": "INSPIRE Soil / Relative binding strength for heavy metals up to 1m tread depth BB", "description": "The interoperable INSPIRE dataset contains data from the LBGR on the relative binding strength for heavy metals up to 1m profile depth Brandenburg, transformed into the INSPIRE target scheme soil. The dataset is provided via an interoperable display and download service. --- The compliant INSPIRE data set contains data about the relative sorption strength for heavy metals for the depth up to 1 m in the State of Brandenburg from the LBGR, transformed into the INSPIRE annex schema Soil. The data set is provided via compliant view and download services.", "formats": [{"name": "WFS_SRVC"}], "keywords": ["High value dataset", "adsorptionsvermo\u0308gen", "bboxbebb", "boden", "bodenkunde", "bodenschutz", "brandenburg", "de", "depthinterval", "derivedsoilprofile", "erdbeobachtung-und-umwelt", "geologie", "inspireidentifiziert", "interoperabel", "interoperability", "interoperable-daten", "om_observation", "opendata", "ph-wert", "process", "regional", "relative-bindungssta\u0308rke-fu\u0308r-schwermetalle", "schwermetall", "soil", "soilderivedobject", "soillayer", "sorption-strength-for-heavy-metals", "sorptionstrengthheavymetals"], "contacts": [{"organization": "Landesamt f\u00fcr Bergbau, Geologie und Rohstoffe Brandenburg (LBGR)", "roles": ["creator"]}]}, "links": [{"href": "https://inspire.brandenburg.de/services/so_boschwerm1m_wfs?REQUEST=GetCapabilities&SERVICE=WFS"}, {"href": "https://inspire.brandenburg.de/services/so_boschwerm1m_wms?REQUEST=GetCapabilities&SERVICE=WMS"}, {"href": "http://data.europa.eu/88u/dataset/056fedb4-93f8-4c0f-a586-044feea6362c~~1"}, {"rel": "self", "type": "application/geo+json", "title": "056fedb4-93f8-4c0f-a586-044feea6362c", "name": "item", "description": "056fedb4-93f8-4c0f-a586-044feea6362c", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/056fedb4-93f8-4c0f-a586-044feea6362c"}, {"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": "05ab7dfa-9155-4575-a0a3-fdffd52f05d3-bundesamt-fur-umwelt-bafu", "type": "Feature", "geometry": null, "properties": {"updated": "2019-06-27T00:00:00", "type": "Dataset", "title": "Monthly soil erosion risk maps for Swiss permanent grassland, with average soil loss in tons/(ha*month), July", "description": "Monthly soil erosion risk maps for Swiss permanent grassland with a spatial resolution of 100m. The maps show the average soil loss in tons per hectare and month. Shades of green, yellow and red mean a low, average and high risk of erosion, respectively.The monthly soil erosion risk maps were calculated using the Revised Universal Soil Loss Equation (RUSLE). For this RUSLE application, the monthly dynamic of the rainfall erosivity factor (R-factor) and cover and management factor (C-factor) was considered as follows: A(month)= R(month)*K*C(month)*L*S*P where A(month) is the soil loss in tons per hectare and month and R(month) and C(month) are the monthly R-factor (MJ mm ha\u207b\u00b9 h\u207b\u00b9 month\u207b\u00b9) and C-factor (dimensionless). The other erosion factors are soil erodibility (K-factor), slope length (L-factor), slope steepness (S-factor) and support practices (P-factor). The RUSLE factors were tailored to the specific environmental conditions of Swiss permanent grassland. The P-factor was included in the calculation as a constant with value 1 due to a lack of spatial information on grazing management and its effect on soil erosion.", "formats": [{"name": "HTML"}], "keywords": ["amenagement-antierosif", "atmospharische-bedingungen", "atmospheric-conditions", "aufbewahrungs-und-archivierungsplanung-aap-bund", "bgdi-bundesgeodaten-infrastruktur", "boden", "bodenerosion", "ch", "conditions-atmospheriques", "condizioni-atmosferiche", "conservation-and-archiving-planning-aap-confederation", "controllo-dellerosione", "e-geoch", "erosion", "erosion-control", "erosion-du-sol", "erosione", "erosione-del-suolo", "erosionsschutz", "fsdi-federal-spatial-data-infrastructure", "gesundheit-und-sicherheit", "human-health-and-safety", "ifdg-infrastruttura-federale-dei-dati-geografici", "ifdg-linfrastructure-federale-de-donnees-geographiques", "pianificazione-della-conservazione-e-dellarchiviazione-aap-confederazione", "planification-de-la-conservation-et-de-larchivage-aap-confederation", "salute-umana-e-sicurezza", "sante-et-securite-des-personnes", "soil", "soil-erosion", "sol", "suolo"], "contacts": [{"organization": "boden@bafu.admin.ch", "roles": ["creator"]}, {"organization": "https://opendata.swiss/organization/bundesamt-fur-umwelt-bafu", "roles": ["publisher"]}]}, "links": [{"href": "https://data.geo.admin.ch/browser/index.html#/collections/ch.bafu.erosion-gruenland_bodenabtrag/items/erosion-gruenland_bodenabtrag_jul"}, {"href": "https://map.geo.admin.ch/?layers=ch.bafu.erosion-gruenland_bodenabtrag_jul"}, {"href": "https://wms.geo.admin.ch/?SERVICE=WMS&VERSION=1.3.0&REQUEST=GetCapabilities&lang=de"}, {"href": "https://wmts.geo.admin.ch/EPSG/3857/1.0.0/WMTSCapabilities.xml?lang=de"}, {"href": "https://www.tandfonline.com/doi/full/10.1080/17445647.2019.1585980"}, {"href": "http://data.europa.eu/88u/dataset/05ab7dfa-9155-4575-a0a3-fdffd52f05d3-bundesamt-fur-umwelt-bafu"}, {"rel": "self", "type": "application/geo+json", "title": "05ab7dfa-9155-4575-a0a3-fdffd52f05d3-bundesamt-fur-umwelt-bafu", "name": "item", "description": "05ab7dfa-9155-4575-a0a3-fdffd52f05d3-bundesamt-fur-umwelt-bafu", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/05ab7dfa-9155-4575-a0a3-fdffd52f05d3-bundesamt-fur-umwelt-bafu"}, {"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": "06AF1400-76F1-471A-A38F-2CAFFADEDDA8", "type": "Feature", "geometry": null, "properties": {"updated": "2020-02-11T00:00:00Z", "type": "Dataset", "language": "de", "title": "Boden\u00fcbersichtskarte 1:200.000 (B\u00dcK200) - CC5510 Siegen", "description": "Die Boden\u00fcbersichtskarte 1:200.000 (B\u00dcK200) wird von der Bundesanstalt f\u00fcr Geowissenschaften und Rohstoffe (BGR) in Zusammenarbeit mit den Staatlichen Geologischen Diensten (SGD) der Bundesl\u00e4nder im Blattschnitt der Topographischen \u00dcbersichtskarte 1:200.000 (T\u00dcK200) erarbeitet und in 55 einzelnen Kartenbl\u00e4ttern herausgegeben. Die digitale, blattschnittfreie Datenhaltung bildet eine detaillierte, bundesweit einheitliche und fl\u00e4chendeckende Informationsgrundlage f\u00fcr L\u00e4nder \u00fcbergreifende Aussagen zu Bodennutzung und Bodenschutz. \u00dcber den aktuellen Bearbeitungsstand des Kartenwerks informieren die Internetseiten der BGR zum Thema Boden. Die Verbreitung und Vergesellschaftung der B\u00f6den auf dem Gebiet dieses Kartenblattes wird anhand von 84 Legendeneinheiten (gegliedert nach Bodenregionen und Bodengro\u00dflandschaften) beschrieben. Jede Legendeneinheit beinhaltet bodensystematische Informationen (Bodensubtyp) und Informationen zum Bodenausgangsgestein sowohl f\u00fcr die Leitb\u00f6den als auch f\u00fcr deren Begleiter. Im Zuge der Bearbeitung des B\u00dcK200-Nachbarblattes Frankfurt a.M.-West wurde der LBG-Datensatz von Siegen am s\u00fcdlichen Blattrand in Teilen ver\u00e4ndert (Stand 29. April 2008). Im Zuge der Bearbeitung des B\u00dcK200-Nachbarblattes K\u00f6ln wurde der LBG-Datensatz von Siegen am westlichen Blattrand angepasst. Die alte LE 58 aus der BGL 11.1 wurde der BGL 6.3 als neue LE 15 zugeordnet (Stand 23. Januar 2012). Im Rahmen der Qualit\u00e4tssicherung wurde der LBG-Datensatz von Siegen am \u00f6stlichen Blattrand leicht ver\u00e4ndert (Stand 03. Dezember 2013).", "formats": [{"name": "PDF"}], "keywords": ["ackerbauliches-ertragspotential", "boden", "bodenart", "bodenausgangsgestein", "bodenauslaugung", "bodenbearbeitung", "bodenbelastung", "bodenbildung", "bodenbiologie", "bodenchemie", "bodendegradation", "bodendekontamination", "bodeneigenschaften", "bodenerosion", "bodenfeuchtigkeit", "bodenform", "bodenfruchtbarkeit", "bodenfunktion", "bodengefu\u0308ge", "bodengesellschaft", "bodengestaltung", "bodengruppe", "bodengu\u0308te", "bodenhorizont", "bodeninformationssystem", "bodenkarte", "bodenluft", "bodenmechanik", "bodenmineralogie", "bodennutzbarkeit", "bodennutzung", "bodenphysikalische-eigenschaften", "bodenprofil", "bodenskelett", "bodensubstrat", "bodensystematik", "bodentyp", "bodenverbreitung", "de", "durchla\u0308ssigkeit", "effektive-durchwurzelungstiefe", "fachinformationssystem", "hessen", "nordrhein-westfalen", "opendata", "rheinland-pfalz", "siegen", "soil"], "contacts": [{"organization": "Bundesanstalt f\u00fcr Geowissenschaften und Rohstoffe (BGR)", "roles": ["creator"]}]}, "links": [{"href": "https://download.bgr.de/bgr/Boden/BUEK200/5510/jpg/buek200_5510.zip"}, {"href": "https://download.bgr.de/bgr/Boden/BUEK200/5510/pdf/buek200_5510.zip"}, {"href": "https://download.bgr.de/bgr/Boden/BUEK200/5510/png/buek200_5510.zip"}, {"href": "https://download.bgr.de/bgr/Boden/BUEK200/5510/shp/buek200_5510.zip"}, {"href": "https://download.bgr.de/bgr/Boden/BUEK200/5510/tiff/buek200_5510.zip"}, {"href": "http://data.europa.eu/88u/dataset/06af1400-76f1-471a-a38f-2caffadedda8"}, {"rel": "self", "type": "application/geo+json", "title": "06AF1400-76F1-471A-A38F-2CAFFADEDDA8", "name": "item", "description": "06AF1400-76F1-471A-A38F-2CAFFADEDDA8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/06AF1400-76F1-471A-A38F-2CAFFADEDDA8"}, {"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": "06e73eeb-4581-7b33-e103-3a129093d809", "type": "Feature", "geometry": null, "properties": {"updated": "2025-03-13T00:00:00Z", "type": "Dataset", "title": "KWasser SL WMS 23/24 \u2013 K water erosion hazard class", "description": "The backdrop of erosion 2023/24 according to the CAP Conditionalities Regulation of 9. December 2022:Culture erosion 2023/24 according to the CAP Conditionalities Regulation of 9 December 2022 December 2022", "formats": [{"name": "WMS_SRVC"}], "keywords": ["boden", "ccw", "cross-compliance", "de", "erosion", "hvd", "infomapaccessservice", "inspireidentifiziert", "kwasser", "landwirtschaft", "opendata", "saarland"]}, "links": [{"href": "https://geoportal.saarland.de/mapbender/php/wms.php?inspire=1&layer_id=46709&withChilds=1&REQUEST=GetCapabilities&SERVICE=WMS"}, {"href": "http://data.europa.eu/88u/dataset/06e73eeb-4581-7b33-e103-3a129093d809"}, {"rel": "self", "type": "application/geo+json", "title": "06e73eeb-4581-7b33-e103-3a129093d809", "name": "item", "description": "06e73eeb-4581-7b33-e103-3a129093d809", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/06e73eeb-4581-7b33-e103-3a129093d809"}, {"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": "07388e86-f38b-469a-9910-6e24af66bbf5", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[11.07, 47.83], [11.07, 47.83], [11.07, 47.83], [11.07, 47.83], [11.07, 47.83]]]}, "properties": {"themes": [{"concepts": [{"id": "climatologyMeteorologyAtmosphere"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "environmental factors"}, {"id": "water"}, {"id": "Soil analysis"}, {"id": "Soil"}, {"id": "soil amendments"}, {"id": "Soil biology"}, {"id": "Temperature profile"}, {"id": "moisture content"}, {"id": "Temperature"}, {"id": "Soil temperature"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "soil profile"}, {"id": "soil moisture"}, {"id": "temperature"}], "scheme": "GEMET - Concepts, version 2.4"}, {"concepts": [{"id": "farming systems"}, {"id": "Grassland management"}, {"id": "Grassland soils"}, {"id": "grasslands"}, {"id": "permanent grasslands"}, {"id": "agriculture"}, {"id": "agricultural practices"}, {"id": "Climatic change"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "Boden"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}, {"concepts": [{"id": "opendata"}], "scheme": "Individual"}], "rights": "Restrictions applied to assure the protection of privacy or intellectual property, and any special restrictions or limitations or warnings on using the resource or metadata. (e.g. Reports, articles, papers, scientific and non-scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \u201cData re-used from the BonaRes Data Centre www.bonares.de. This data were created as part of BonaRes Module A-Project - SUSALPS's research activities.\u201d Although every care has been taken in preparing and testing the data, BonaRes Module A-Project- SUSALPS and BonaRes Data Centre cannot guarantee that the data are correct; neither does BonaRes Module A-Project-SUSALPS and BonaRes Data Centre accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The BonaRes Module A-Project-SUSALPS and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data. The access to this data is restricted during embargo time. If prior access is requested, contact the data owner/author.)", "updated": "2020-02-14", "type": "Dataset", "created": "2018-12-05", "language": "eng", "title": "SUSALPS temperature and volumetric soil water content Graswang Subplot 1 in Fendt intensiv", "description": "Grassland is a precious good. Grassland contributes to food security by providing fodder for dairy and beef farming, storing nutrients and increasing biodiversity. These functions that secure the fertility and yields of soil are jeopardized by climate change, especially in monane and alpine areas. In SUSALPS, scientists, authorities and farmers work together to investigate the influence of climate change on i) plant biodiversity, ii) C and N storage, iii) greenhouse gas exchange, iv) socio economic conditions that influence decision making of farmers. A central experimental aspect is the translocation of soil mesocosms from higher elevation to lower elevation (Esterberg site at 1200m, Graswang site at 860m, Fendt at 600m, Bayreuth at 300m). To reflect the spatial heterogeneity of soils, mesocosms from three different subplots approx. 100-300m apart from each other are translocated. Since temperatures are higher and precipitation is lower in lower elevation, the translocated mesocosms experience climate change. This dataset contains daily average soil temperature and volumetric soil water content in 5 and 15 cm depth. Treatment: Graswang Subplot 1 in Fendt intensiv Device: Decagon 5TM Timescale: Daily average Depths: 5 and 15 cm", "formats": [{"name": "CSV"}], "keywords": ["environmental factors", "water", "Soil analysis", "Soil", "soil amendments", "Soil biology", "Temperature profile", "moisture content", "Temperature", "Soil temperature", "soil profile", "soil moisture", "temperature", "farming systems", "Grassland management", "Grassland soils", "grasslands", "permanent grasslands", "agriculture", "agricultural practices", "Climatic change", "Boden", "opendata"], "contacts": [{"name": "Kiese, Ralf", "organization": "Karlsruhe Institute of Technology (KIT)", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "ralf.kiese@kit.edu"}], "addresses": [{"deliveryPoint": [null], "city": "Garmisch-Partenkirchen", "administrativeArea": null, "postalCode": "82467", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Kiese, Ralf", "organization": "Karlsruhe Institute of Technology (KIT)", "position": null, "roles": ["projectLeader"], "phones": [{"value": null}], "emails": [{"value": "ralf.kiese@kit.edu"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "BonaRes Data Centre", "organization": "Leibniz Centre for Agricultural Landscape Research (ZALF)", "position": "Research Platform 'Data' - WG Geodata", "roles": ["publisher"], "phones": [{"value": "+49 33432 82 171"}], "emails": [{"value": "bonares-datenzentrum@zalf.de"}], "addresses": [{"deliveryPoint": ["Eberswalder Strasse 84"], "city": "M\u00fcncheberg", "administrativeArea": "Brandenburg", "postalCode": "15374", "country": "Germany"}], "links": [{"href": null}]}, {"organization": "Karlsruhe Institute of Technology (KIT)", "roles": ["contributor"]}]}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=07388e86-f38b-469a-9910-6e24af66bbf5", "rel": "download"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/217290dd-a23f-4734-96d5-71b878a2fca8", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "07388e86-f38b-469a-9910-6e24af66bbf5", "name": "item", "description": "07388e86-f38b-469a-9910-6e24af66bbf5", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/07388e86-f38b-469a-9910-6e24af66bbf5"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["2016-08-11T00:00:00Z", "2018-10-09T00:00:00Z"]}}, {"id": "10.1002/jeq2.20119", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:14:30Z", "type": "Journal Article", "created": "2020-07-01", "title": "Global Research Alliance N2O chamber methodology guidelines: Summary of modeling approaches", "description": "AbstractMeasurements of nitrous oxide (N2O) emissions from agriculture are essential for understanding the complex soil\uffe2\uff80\uff93crop\uffe2\uff80\uff93climate processes, but there are practical and economic limits to the spatial and temporal extent over which measurements can be made. Therefore, N2O models have an important role to play. As models are comparatively cheap to run, they can be used to extrapolate field measurements to regional or national scales, to simulate emissions over long time periods, or to run scenarios to compare mitigation practices. Process\uffe2\uff80\uff90based models can also be used as an aid to understanding the underlying processes, as they can simulate feedbacks and interactions that can be difficult to distinguish in the field. However, when applying models, it is important to understand the conceptual process differences in models, how conceptual understanding changed over time in various models, and the model requirements and limitations to ensure that the model is well suited to the purpose of the investigation and the type of system being simulated. The aim of this paper is to give the reader a high\uffe2\uff80\uff90level overview of some of the important issues that should be considered when modeling. This includes conceptual understanding of widely used models, common modeling techniques such as calibration and validation, assessing model fit, sensitivity analysis, and uncertainty assessment. We also review examples of N2O modeling for different purposes and describe three commonly used process\uffe2\uff80\uff90based N2O models (APSIM, DayCent, and DNDC).