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zenodo44/100

Globally-gridded data for manuscript: Global stocks and capacity of mineral-associated soil organic carbon

Supporting globally-gridded data products for manuscript: Georgiou K., Jackson R. B., Vindu&scaron;ková O., Abramoff R. Z., Ahlström A., Feng W., Harden J. W., Pellegrini A. F. A., Polley H. W., Soong J. L., Riley W. J., Torn M. S. Global stocks and capacity of mineral-associated soil organic carbon. Nature Communications, 2022. We leveraged data from a global synthesis of soil fractionation measurements (DOI: 10.5281/zenodo.5987415) along with ancillary data on climate, vegetation, and soil characteristics to produce spatially-explicit global estimates of mineral-associated soil organic carbon stocks (MOC) and mineralogical carbon capacity (MOCmax) in non-permafrost, non-desert mineral soils. Globally-gridded datasets are given in kgC/m2 for topsoil (0-30cm) and subsoil (30-100cm) at 0.5 degree by 0.5 degree spatial resolution.

opencc-by-4.0Dec 2021View details →

zenodo44/100

Synthesis data for manuscript: Global stocks and capacity of mineral-associated soil organic carbon

Supporting synthesis data for manuscript: Georgiou K., Jackson R. B., Vindu&scaron;ková O., Abramoff R. Z., Ahlström A., Feng W., Harden J. W., Pellegrini A. F. A., Polley H. W., Soong J. L., Riley W. J., Torn M. S. Global stocks and capacity of mineral-associated soil organic carbon. Nature Communications, 2022. We performed an observational synthesis of soil fractionation data constituting 1,144 globally-distributed soil profiles from 78 studies that reported fractionation and bulk measurements of organic carbon across depths. This dataset includes measurements of mineral-associated, particulate, and bulk soil organic carbon, as well as ancillary data on edaphic, climate, and vegetation characteristics. We also performed a separate observational synthesis of soil carbon accrual from manipulation and chronosequence studies, which included changes in carbon stocks or concentrations, bulk density, experimental duration, and edaphic properties. This latter synthesis included 103 observations from 34 studies that spanned crop, pasture, grassland, and forest ecosystems across climates and soil types. Further details for both syntheses can be found in the methods and supplementary materials of the associated manuscript.

opencc-by-4.0Dec 2021View details →

zenodo44/100

Soil carbon stock, litter decomposition, and weather data from Ethiopian forests

Introduction 100 sampling units (SU) were selected from the total of 631 SUs of the Forest Reference Level submission 2017 (FRL 2017). The sampling was designed unbiased for total growing stock per SU, altitude,and mean litter depth per SU. The actual field sampling succeeded on 98 of the pre-selected SUs due to accessibility restrictions. Soil profile sampling Soil sampling was performed from November 2017 till mid-January 2018. Samples were taken from undisturbed soil from depths of 0-10 cm, 10-20 cm, and 20-30 cm below the organic layer. Volumetric samples of 107.5 cm3 were taken vertically, using a 10 cm long conically shaped corer with a cutting lower edge diameter of 37 mm and upper diameter of 40 mm.  Composite samples were formed by combining the volumetric samples taken from different depths of two parallel soil profiles. The samples were transported to EEFRI Soil Laboratory in Addis Ababa after 1-4 weeks of sampling at distant locations.    Soil physical characteristics The soil samples were air-dried, homogenized, and subjected to oven-drying at 105°C until constant mass. Total bulk density was determined using the total dry mass and volume of the composite samples.  Organic carbon content (C % by wet oxidation method), and soil physical characteristics: moisture content, bulk density of the total sample, and bulk density of fine fraction (particles passing the 2 mm sieve). The mass of the coarse fraction was weighed. The soil fine fraction was also subjected to laser diffraction for more accurate particle size analysis for proportions of clay, silt, and sand.    In addition to this 28 samples were also analyzed for C content in the laboratory of Natural Resources Institute Finland to determine C content by LECO CHN analyzer. This was done to calibrate the bulk of wet digestion-based estimates (Fig. 1). Before analysis, the soils were tested for the presence of inorganic C.   For Figure 1. See Soil_C_Ethiopia.pdf Figure 1. Comparison of results from wet oxidation (Walkley-Black) and dry oxidation (CHN analyzer). The dotted line shows the theoretical 1:1 match between the axis, the solid line shows linear regression (intercept = 0) between the methods. The estimated slope value of 1.165 was used in adjusting the wet digestion results to match those obtained by dry oxidation: OCadj = 1.165 * OCwet. Based on a linear regression between the wet and dry oxidation analysis results, a correction factor of 1.165 was applied to adjust the organic C% obtained by wet digestion. The adjusted data are shown in the file “SOC_Ethiopia_2017-2018.csv”.   SOC stocks were calculated by multiplying the proportion of organic C with BD of fine earth, after which the result was corrected for stoniness, a visually estimated proportion of large stones (S, value from 0 to 1) in the soil profile that could not be included in the volumetric soil samples (FAO VS-FAST). \(SOCstock = C_{org} * BD_{fe} * (1-S)\) Soil organic carbon stock data Files: “SOC_Ethiopia_2017-2018.csv” and “SOC_Ethiopia_2017-2018.xlsx” The file includes soil characteristics from layers of 0-10 cm, 10-20 cm, and 20-30 cm below the loose organic layer on top of the soil. The data are used for SOC stock estimation in the respective layers as described above. In the .csv file individual columns are for  LAT is the latitude of the sampling site corresponding to FieldCode and SU_nr LON is the longitude of the sampling site corresponding to FieldCode and SU_nr <ul> <li>The coordinates are expressed as decimal degrees of the WGS84 system</li> </ul> FieldCode refers to the Region and Sampling Unit number of the Ethiopian NFI (see below)  SU_nr is the Sampling Unit number of the Ethiopian NFI Region is the name of the administrative region where the sample was taken Biome is the name of the forest biome type where the sample was collected BiomeSimplified is the name of a biome with some close types combined DepthRange is the upper and lower limit of the soil sample in the field, cm StoninessVFAST is a percentage of stones (VS-FAST by FAO) in the ca. 40 cm deep soil profile exposed during the sampling FreshMassInField is the mass of the total composite soil sample of the given layer, g, primarily indicative of checking the correct number of subsamples in composite NrComposites is the number of subsamples included in the composite for each soil layer CorerVolume is a constant of 107.5 cm3 because only one type of corer was used for undisturbed, volumetric sampling CompositeVolume is the volume of the composite sample for each soil depth layer CoarseFractionMass is the dry mass, g of soil particles > 2mm that did not pass the sieve, but were included in the sample volume FE_DryMass is oven-dry mass, g of the fine fraction that passed the 2 mm sieve. BDtot is total bulk density, g m-3, calculated for the composite sample BDfe is the bulk density of the fine earth fraction, g m-3 OC_adj is organic carbon (OC) content (%) in the composite sample, adjusted according to the comparison between dry and wet oxidation methods (Fig. 1) SOCfe is SOC stock calculated for soil fine earth fraction, t ha-1 in the 10 cm deep soil layer SOCfe_stoniness is SOC stock of the fine earth fraction, t ha-1 in the 10 cm deep soil layer, adjusted for stoniness. The correction assumes that the volume occupied by larger stones would be void of OC.    Litter stock data File: “Litter_Ethiopia_2017-2018.csv” The file includes measurements of litter layer on Ethiopian NFI Sampling Unit (SU) sites where sampling for SOC stock determination was done. The depth of the litter layer was measured in the SU’s of the NFI, and this data contains in addition to depth also a volumetric sample of the litter layer. The dry bulk density was used to calculate the carbon stocks in the litter pool.   The depth of the litter layer was measured in the field. Litter from the respective spot was sampled quantitatively from a frame of 0.01m2 of area for litter dry mass estimate. The organic C stock in a litter (L) was calculated as,   \(L = {M\over z} * {C_{om}\over A}, \)   where M = Dry mass of the litter sample, g z = Depth of the litter layer in the field, m Com = Conversion factor from dry organic matter to carbon (C), 0.5 A = area of quantitative collection of litter (0.01 m2)   In the .csv file individual columns are for LAT, LON is the GPS coordinates (decimal degrees of WGS84) for the Sampling Units (SU_ID) SU_ID is the Sampling Unit identification number of the Ethiopian NFI FieldCode refers to the Region and Sampling Unit number of the Ethiopian NFI (see below) Region is the name of the administrative region where the sample was taken Litter_dry is the dry mass, g of the litter sample Area_m2 is the area, m2 of litter sampling MeanLitterDepth is the mean depth of the litter layer at the sampling area CDensityLitter is the dry bulk density of the litter, g m-2 multiplied by the assumed organic C proportion of the oven-dry litter materials (0.50) LitterCStock_tha is the litter stock, t ha-1 calculated from the C density of the litter layer   Litter bag data (decomposition and quality) The leaves and twigs were sampled from 2 species (Juniperus and Podocarpus) and 3 locations of the elevation gradient in the Chilimo forest (Table 1). The forest was considered an old-growth with Juniperus procera and Podocarpus falcatusbeing the main species forming the tree canopy. The sites form an elevation gradient (Table 1).   Table 1. Geographical locations of the study sites in the Chilimo forest.   <table> <tbody> <tr> <td> id </td> <td> Latitude (deg.) </td> <td> Longitude (deg.) </td> <td> Elevation (m a.s.l) </td> </tr> <tr> <td> 1 </td> <td> 9.0672 </td> <td> 38.1443 </td> <td> 2500 </td> </tr> <tr> <td> 2 </td> <td> 9.0712 </td> <td> 38.1556 </td> <td> 2670 </td> </tr> <tr> <td> 3 </td> <td> 9.0869 </td> <td> 38.1684 </td> <td> 2800 </td> </tr> </tbody> </table>   The dying and dead leaves were sampled directly from the trees later referred to as “fresh” and from the branches found on the ground, referred to as “old”. The old leaves were assumed to be dead for around 3 months. The diameter of the branches/twigs was less than 1 cm in diameter. The samples were first sorted and air-dried in an elevated temperature of the greenhouse and thereafter oven-dried in the oven overnight at 45 °C.  The samples were analyzed for acid, water, ethanol dissolved,and undissolved fractions (AWEN) (Table 2) and for the decomposition rates of the litter installed into the litter bags corresponding to each of the Chilimo sites.    Table 2. Acid, water, ethanol (A, W, E, respectively) dissolved and undissolved fractions (N) from the litter components of the dominant tree species in the Chilimo forest. <table> <tbody> <tr> <td> Litter type </td> <td> Species </td> <td> A </td> <td> W </td> <td> E </td> <td> N </td> </tr> <tr> <td> leaves fresh </td> <td> Juniperus  </td> <td> 0.45 </td> <td> 0.13 </td> <td> 0.1 </td> <td> 0.33 </td> </tr> <tr> <td> leaves fresh </td> <td> Podocarpus  </td> <td> 0.42 </td> <td> 0.28 </td> <td> 0.05 </td> <td> 0.25 </td> </tr> <tr> <td> leaves old </td> <td> Juniperus  </td> <td> 0.44 </td> <td> 0.07 </td> <td> 0.08 </td> <td> 0.41 </td> </tr> <tr> <td> leaves old </td> <td> Podocarpus  </td> <td> 0.44 </td> <td> 0.09 </td> <td> 0.05 </td> <td> 0.42 </td> </tr> <tr> <td> twigs </td> <td> Juniperus  </td> <td> 0.61 </td> <td> 0.04 </td> <td> 0.02 </td> <td> 0.32 </td> </tr> <tr> <td> twigs </td> <td> Podocarpus  </td> <td> 0.56 </td> <td> 0.15 </td> <td> 0.02 </td> <td> 0.27 </td> </tr> </tbody> </table>   A sufficient amount of litter was placed into the litter bags (polyurethane mesh 1 mm) and the mesh bags were installed on top of the soil surface under the forest canopy (later referred to as “canopy”) and in the forest gap caused by harvesting (later referred as “open”). The installation of the litter bags (for each species 3 replicates of each litter type for each site and canopy type for the 3 periods, in total 12 litter bags for leaves and 6 bags for twigs) was done on 22.9.2017. The mesh bags were left on the ground, protected from grazing by the fence, and retrieved subsequently on 12.10.2017, 31.10.2017, and 12.12.2017. Despite the efforts took few samples were lost. The retrieved samples were oven-dried and initial mass and mass loss data for each period and litter type with a detailed description of the variables can be found in the file “litter.chilimo_07.02.22.xlsx”.   Soil temperature data During the period from 22.9.2017 to 12.12.2017, we monitored the soil temperature at 5 cm depth under the canopy and in the open canopy on all Chilimo sites continuously every 4 hours intervals with the Maxim iButton temperature loggers. However, some sensors were lost. Daily means and their standard deviation of the continuous temperatures can be found in the file “soil.temp.chilimo_07.02.22.xlsx”.   Processed weather data The air temperature and precipitation data for 98 sampling units corresponding to soil carbon data originated from 73 weather stations located across Ethiopia and were obtained from Ethiopian Meteorological Agency (http://www.ethiomet.gov.et/). Sampling units were joined with weather data by the closest proximity to their corresponding weather stations. Precipitation was unaltered. The air temperature required correction by elevation is described in more detail in Lehtonen et al. (2020). The monthly values of air temperature and precipitation with an accompanied readme description of the variables can be found for 98 sampling units in the file “sampling.units98_meteo_07.02.22.xlsx” and the Chilimo study sites in the file “monthly.weather.chilimo_07.02.22.xlsx”. The monthly values in the file "sampling.units98_meteo_07.02.22.xlsx" correspond to long-term average over the period from 1986 to 2017.     References:   Lehtonen, A., Ťupek, B., Nieminen, T.M., Balázs, A., Anjulo, A., Teshome, M., Tiruneh, Y. and Alm, J., 2020. Soil carbon stocks in Ethiopian forests and estimations of their future development under different forest use scenarios. Land Degradation & Development, 31(18), pp.2763-2774.   FRL 2017. https://redd.unfccc.int/files/ethiopia_frel_3.2_final_modified_submission.pdf

opencc-by-4.0May 2022View details →

zenodo44/100

Soil carbon and nitrogen stock data for dominant geomorphological terrain units in Qarlikturvik Valley, Bylot Island, Arctic Canada

Dataset for the manuscript 'The distribution of soil carbon and nitrogen stocks among dominant geomorphological terrain units in Qarlikturvik Valley, Bylot Island, Arctic Canada.' to appear in the 'Journal of Geophysical Research: Biogeosciences'.

opencc-by-4.0Jun 2022View details →

zenodo44/100

Data to support the publication "Impact of agricultural management on soil aggregates and associated organic carbon fractions: Analysis of long-term experiments in Europe"

Raw data: Experimental plot ids and information, mass distribution of all aggregate fractions after wet sieving, Sand content of each fraction to conduct the sand correction, mass distribution of all fractions after isolating the micro-aggregates held within the macroaggregates, yields per treatment, carbon content per fraction (raw data) All data per plot: SOC content, MAOM and POM content of each fraction presented in the fractionation scheme included in the manuscript, together with the mass of the relative fractions.

opencc-by-4.0Sep 2022View details →

zenodo44/100

Soil Carbon Dynamics in Soybean Cropland and Forests in Mato Grosso, Brazil

These files contain the carbon content, radiocarbon, and stable isotope data for soils collected to 2 m deep in forest and soybean cropland in Mato Grosso, Brazil.

opencc-by-4.0Dec 2017View details →

zenodo44/100

Data from "Into the unknown: The role of post-fire soil erosion in the carbon cycle"

Wildfires directly emit 2.1 Pg carbon (C) to the atmosphere annually. The net effect of wildfires on the C cycle, however, involves many interacting source and sink processes beyond these emissions from combustion. Among those, the role of post-fire enhanced soil organic carbon (SOC) erosion as a C sink mechanism remains essentially unquantified. Wildfires can greatly enhance soil erosion due to the loss of protective vegetation cover and changes to soil structure and wettability. Post-fire SOC erosion acts as a C sink when off-site burial and stabilization of C eroded after a fire, together with the on-site recovery of SOC content, exceed the C losses during its post-fire transport. Here we synthesize published data on post-fire SOC erosion and evaluate its overall potential to act as longer-term C sink. To explore its quantitative importance, we also model its magnitude at continental scale using the 2017 wildfire season in Europe. Our estimations show that the C sink ability of SOC water erosion during the first post-fire year could account for around 13% of the C emissions produced by wildland fires. This indicates that post-fire SOC erosion is a quantitatively important process in the overall C balance of fires, and highlights the need for more field data to further validate this initial assessment. Here we provide the post-fire SOC erosion dataset ("Post-fire SOC erosion rates" file) used for calculating the SOC ratio of eroded sediments implemented in the RUSLE modelling; as well as the list of data sources ("List of data sources" file).

opencc-by-4.0May 2024View details →

zenodo44/100

Gridded spatial information on soil organic carbon content, density and stock in Hungary for 1992 and 2000

Predictive soil organic carbon (SOC) content, density, and stock maps, along with the associated prediction uncertainty, are provided for the years 1992 and 2000, for the entire territory of Hungary. The maps refer to the topsoils (0–30 cm) with a spatial resolution of 100⨯100 m. The uncertainty associated with the SOC property maps is expressed by the lower and upper limits of the 90% prediction interval (PI), the range of values within which the true value is expected to occur 9 times out of 10. This means that there are two maps to each SOC property map, quantifying its prediction uncertainty. It should be added that all maps have been masked with open water bodies, as these areas are not relevant for soils. For more details / to cite this dataset please use: <a href="https://doi.org/10.1038/s41597-024-04158-3">Szatmári, G., Laborczi, A., Mészáros, J., Takács, K., Benő, A., Koós, S., Bakacsi, Z., & Pásztor, L. (2024). Gridded, temporally referenced spatial information on soil organic carbon for Hungary. Scientific Data 11, 1312.</a> Custom code used for digital soil mapping and validation is available on GitHub: <a href="https://github.com/GaborSzatmari/HU-SOC-mapping" target="_blank" rel="noopener">https://github.com/GaborSzatmari/HU-SOC-mapping</a> Description of the files: The resulting maps are shared as GeoTIFF files. The coordinate reference system is the Hungarian Unified National Projection System (HD72/EOV; EPSG: 23700) (<a href="https://epsg.io/23700" target="_blank" rel="noopener">https://epsg.io/23700</a>). The table below provides further information on the published maps. Note that the first file (00_Overview.jpg) gives an overview of the SOC property maps. <table> <tbody> <tr> <td> SOC property maps </td> <td> Unit </td> <td> Year </td> <td> Filename </td> </tr> <tr> <td> SOC content map </td> <td> [g ∙ kg-1] </td> <td> 1992 </td> <td> SOCc_0_30cm_1992_pred.tif </td> </tr> <tr> <td> SOC content, lower limit of the 90% PI </td> <td> [g ∙ kg-1] </td> <td> 1992 </td> <td> SOCc_0_30cm_1992_q05.tif </td> </tr> <tr> <td> SOC content, upper limit of the 90% PI </td> <td> [g ∙ kg-1] </td> <td> 1992 </td> <td> SOCc_0_30cm_1992_q95.tif </td> </tr> <tr> <td> SOC density map </td> <td> [kg ∙ m-3] </td> <td> 1992 </td> <td> SOCd_0_30cm_1992_pred.tif </td> </tr> <tr> <td> SOC density, lower limit of the 90% PI </td> <td> [kg ∙ m-3] </td> <td> 1992 </td> <td> SOCd_0_30cm_1992_q05.tif </td> </tr> <tr> <td> SOC density, upper limit of the 90% PI </td> <td> [kg ∙ m-3] </td> <td> 1992 </td> <td> SOCd_0_30cm_1992_q95.tif </td> </tr> <tr> <td> SOC stock map </td> <td> [tons ∙ ha-1] </td> <td> 1992 </td> <td> SOCs_0_30cm_1992_pred.tif </td> </tr> <tr> <td> SOC stock, lower limit of the 90% PI </td> <td> [tons ∙ ha-1] </td> <td> 1992 </td> <td> SOCs_0_30cm_1992_q05.tif </td> </tr> <tr> <td> SOC stock, upper limit of the 90% PI </td> <td> [tons ∙ ha-1] </td> <td> 1992 </td> <td> SOCs_0_30cm_1992_q95.tif </td> </tr> <tr> <td> SOC content map </td> <td> [g ∙ kg-1] </td> <td> 2000 </td> <td> SOCc_0_30cm_2000_pred.tif </td> </tr> <tr> <td> SOC content, lower limit of the 90% PI </td> <td> [g ∙ kg-1] </td> <td> 2000 </td> <td> SOCc_0_30cm_2000_q05.tif </td> </tr> <tr> <td> SOC content, upper limit of the 90% PI </td> <td> [g ∙ kg-1] </td> <td> 2000 </td> <td> SOCc_0_30cm_2000_q95.tif </td> </tr> <tr> <td> SOC density map </td> <td> [kg ∙ m-3] </td> <td> 2000 </td> <td> SOCd_0_30cm_2000_pred.tif </td> </tr> <tr> <td> SOC density, lower limit of the 90% PI </td> <td> [kg ∙ m-3] </td> <td> 2000 </td> <td> SOCd_0_30cm_2000_q05.tif </td> </tr> <tr> <td> SOC density, upper limit of the 90% PI </td> <td> [kg ∙ m-3] </td> <td> 2000 </td> <td> SOCd_0_30cm_2000_q95.tif </td> </tr> <tr> <td> SOC stock map </td> <td> [tons ∙ ha-1] </td> <td> 2000 </td> <td> SOCs_0_30cm_2000_pred.tif </td> </tr> <tr> <td> SOC stock, lower limit of the 90% PI </td> <td> [tons ∙ ha-1] </td> <td> 2000 </td> <td> SOCs_0_30cm_2000_q05.tif </td> </tr> <tr> <td> SOC stock, upper limit of the 90% PI </td> <td> [tons ∙ ha-1] </td> <td> 2000 </td> <td> SOCs_0_30cm_2000_q95.tif </td> </tr> </tbody> </table>

opencc-by-4.0Aug 2024View details →

zenodo44/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: WPCT p025, 2016–2020</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li>WPCT mean: <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li>WPCT p025: <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li>WPCT p975: <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

zenodo44/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: WPCT p025, 2020–2022</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li>WPCT mean: <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li>WPCT p025: <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li>WPCT p975: <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

zenodo44/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: WPCT p025, 2008–2012</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li>WPCT mean: <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li>WPCT p025: <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li>WPCT p975: <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

zenodo44/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: WPCT p025, 2012–2016</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li>WPCT mean: <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li>WPCT p025: <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li>WPCT p975: <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

zenodo44/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: WPCT p975, 2020–2022</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li>WPCT mean: <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li>WPCT p025: <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li>WPCT p975: <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

zenodo44/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: WPCT p975, 2016–2020</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li>WPCT mean: <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li>WPCT p025: <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li>WPCT p975: <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

zenodo44/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: WPCT p975, 2012–2016</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li>WPCT mean: <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li>WPCT p025: <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li>WPCT p975: <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

zenodo44/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: WPCT p975, 2008–2012</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li>WPCT mean: <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li>WPCT p025: <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li>WPCT p975: <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

zenodo44/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: WPCT p025, 2004–2008</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li>WPCT mean: <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li>WPCT p025: <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li>WPCT p975: <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

zenodo44/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: WPCT p025, 2000–2004</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li>WPCT mean: <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li>WPCT p025: <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li>WPCT p975: <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

zenodo44/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: WPCT p975, 2004–2008</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li>WPCT mean: <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li>WPCT p025: <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li>WPCT p975: <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

zenodo44/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: WPCT p975, 2000–2004</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li>WPCT mean: <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li>WPCT p025: <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li>WPCT p975: <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated datasets

Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record