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Retention measured according to the New Zealand method (g/100g). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
Soil pH x 10 in H2O at 7 standard depths (to convert to pH values divide by 10) predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: NA.
Soil organic carbon stock in tons per ha for ICCP depth intervals predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: t / ha.
Coarse fragments volumetric in cm3/dm3 (vol‰) at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for each 1000 m cell.
Gravimetric content of organic carbon and inorganic carbon in the fine earth fraction* (g/kg). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
The International Soil Carbon Network (ISCN) is a science-based network that facilitates data sharing, assembles databases, identifies gaps in data coverage, and enables spatially explicit assessments of soil carbon in context of landscape, climate, land use, and biotic variables.
Version 1.2 of describes a harmonized dataset of derived soil properties for the world. It was created using the soil distribution shown on the 1:5 million scale FAO-Unesco Soil Map of the World (DSMW), rasterised at 5 by 5 arcminutes, and soil property estimates derived from the ISRIC-WISE soil profile database, version 3.1. The dataset considers 19 soil variables that are commonly required for agro-ecological zoning, land evaluation, crop growth simulation, modelling of soil gaseous emissions, and analyses of global environmental change. It presents ‘best’ estimates for: soil drainage class, organic carbon content, total nitrogen, C/N ratio, pH (H2O), CECsoil, CECclay, effective CEC, base saturation, aluminium saturation, calcium carbonate content, gypsum content, exchangeable sodium percentage (ESP), electrical conductivity, particle size distribution (i.e. content of sand, silt and clay), content of coarse fragments (less than 2 mm), bulk density, and available water capacity (-33 to -1500 kPa). These estimates are presented by FAO soil unit for fixed depth intervals of 20 cm up to 100 cm depth (or less when appropriate) for so-called virtual profiles. The associated soil property values were derived from analyses of some 10,250 profiles held in WISE using a scheme of taxonomy-based taxotransfer rules complemented with expert-rules. The type of rules used to derive the various soil property values have been flagged in the database to provide an indication of the possible confidence in the derived data. Most map units on the DSMW are complex, comprising up to eight different soil units. Assessments and model applications that use the derived soil properties therefore should consider the full map unit composition and depth range. The soil property values presented here should be seen as best estimates based on the current selection of soil profiles in WISE, the procedure for clustering the measured data, taxotransfer scheme used for deriving soil, properties, and the spatial data of the digital Soil Map of the World. The derived information may be used for exploratory assessments at a broad scale (greater than 1:5 million; 5 by 5 arcminutes and coarser), pending the global update of the information on world soil resources at more detailed scales, upon due consideration of the underlying generalisations and assumptions. Note: A more recent assessment, at a resolution of 30arcsec (WISE30sec), is available at: http://data.isric.org/geonetwork/srv/eng/catalog.search#/metadata/dc7b283a-8f19-45e1-aaed-e9bd515119bc
Bulk density (fine earth) in kg / cubic-meter at 7 standard depths predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: kg / m3.
Ability of a 1:2 soil water extract to conduct electrical current (dS/m). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
Capacity of the fine earth fraction* to hold exchangeable cations at the pH of the soil (ECEC). Conventionally approximated by summation of exchangeable bases (Ca2+, Mg2+, K+, and Na+) plus 1 N KCl exchangeable acidity (Al3+ and H+) in acidic soils (cmol(c)/kg). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
Capacity of the fine earth fraction* to hold exchangeable cations, estimated by buffering the soil at 'pH8' (cmol(c)/kg). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
Soil moisture content by volume, at tension 10 kPa (pF 2.0) (cm³/100cm³). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
Determined with a very strong acid (aqua regia and sulfuric acid/nitric acid) (mg/kg). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
Total nitrogen in cg/kg at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for each 5000 m cell.
Soil moisture content by volume, at tension 33 kPa (pF 2.5) (cm³/100cm³). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-20244. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
Predicted probability in percent per class predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: probability. Legend: 1: "Haplic Acrisols", 2: "Haplic Acrisols (Alumic)", 3: "Haplic Acrisols (Ferric)", 4: "Haplic Acrisols (Humic)", 5: "Plinthic Acrisols", 6: "Vetic Acrisols", 7: "Haplic Albeluvisols", 8: "Histic Albeluvisols", 9: "Umbric Albeluvisols", 10: "Cutanic Alisols", 11: "Haplic Alisols", 12: "Aluandic Andosols", 13: "Haplic Andosols", 14: "Vitric Andosols", 15: "Albic Arenosols", 16: "Ferralic Arenosols", 17: "Haplic Arenosols", 18: "Haplic Arenosols (Calcaric)", 19: "Hypoluvic Arenosols", 20: "Protic Arenosols", 21: "Haplic Calcisols", 22: "Haplic Calcisols (Sodic)", 23: "Luvic Calcisols", 24: "Petric Calcisols", 25: "Endogleyic Cambisols", 26: "Ferralic Cambisols", 27: "Haplic Cambisols", 28: "Haplic Cambisols (Calcaric)", 29: "Haplic Cambisols (Chromic)", 30: "Haplic Cambisols (Dystric)", 31: "Haplic Cambisols (Eutric)", 32: "Haplic Cambisols (Humic)", 33: "Haplic Cambisols (Sodic)", 34: "Leptic Cambisols", 35: "Vertic Cambisols", 36: "Calcic Chernozems", 37: "Haplic Chernozems", 38: "Luvic Chernozems", 39: "Haplic Cryosols", 40: "Turbic Cryosols", 41: "Vitric Cryosols", 42: "Petric Durisols", 43: "Acric Ferralsols", 44: "Haplic Ferralsols", 45: "Haplic Ferralsols (Rhodic)", 46: "Haplic Ferralsols (Xanthic)", 47: "Umbric Ferralsols", 48: "Haplic Fluvisols", 49: "Haplic Fluvisols (Arenic)", 50: "Haplic Fluvisols (Calcaric)", 51: "Haplic Fluvisols (Dystric)", 52: "Haplic Fluvisols (Eutric)", 53: "Calcic Gleysols", 54: "Haplic Gleysols", 55: "Haplic Gleysols (Dystric)", 56: "Haplic Gleysols (Eutric)", 57: "Mollic Gleysols", 58: "Umbric Gleysols", 59: "Calcic Gypsisols", 60: "Haplic Gypsisols", 61: "Calcic Histosols", 62: "Cryic Histosols", 63: "Fibric Histosols", 64: "Hemic Histosols", 65: "Sapric Histosols", 66: "Calcic Kastanozems", 67: "Haplic Kastanozems", 68: "Haplic Leptosols", 69: "Haplic Leptosols (Eutric)", 70: "Lithic Leptosols", 71: "Mollic Leptosols", 72: "Rendzic Leptosols", 73: "Haplic Lixisols", 74: "Haplic Lixisols (Chromic)", 75: "Haplic Lixisols (Ferric)", 76: "Albic Luvisols", 77: "Calcic Luvisols", 78: "Gleyic Luvisols", 79: "Haplic Luvisols", 80: "Haplic Luvisols (Chromic)", 81: "Haplic Luvisols (Ferric)", 82: "Leptic Luvisols", 83: "Stagnic Luvisols", 84: "Vertic Luvisols", 85: "Alic Nitisols", 86: "Haplic Nitisols (Rhodic)", 87: "Haplic Phaeozems", 88: "Leptic Phaeozems", 89: "Luvic Phaeozems", 90: "Endogleyic Planosols", 91: "Haplic Planosols (Dystric)", 92: "Haplic Planosols (Eutric)", 93: "Luvic Planosols", 94: "Solodic Planosols", 95: "Acric Plinthosols", 96: "Lixic Plinthosols", 97: "Gleyic Podzols", 98: "Haplic Podzols", 99: "Aric Regosols", 100: "Calcaric Regosols", 101: "Haplic Regosols (Dystric)", 102: "Haplic Regosols (Eutric)", 103: "Haplic Regosols (Sodic)", 104: "Leptic Regosols", 105: "Gypsic Solonchaks", 106: "Haplic Solonchaks", 107: "Haplic Solonchaks (Sodic)", 108: "Calcic Solonetz", 109: "Gleyic Solonetz", 110: "Haplic Solonetz", 111: "Mollic Solonetz", 112: "Luvic Stagnosols", 113: "Haplic Umbrisols", 114: "Leptic Umbrisols", 115: "Calcic Vertisols", 116: "Haplic Vertisols", 117: "Haplic Vertisols (Eutric)", 118: "Mollic Vertisols"
This uniform soil data set for the development of pedotransfer functions was developed at the request of the Global Soil Data Task (GSDT) of the Data and Information System (DIS) of the International Geosphere Biosphere Programme (IGBP). The necessary chemical and physical soil data have been derived from ISRIC's Soil Information System (ISIS) and the soil CD-ROM of the Natural Resources Conservation Service (USDA-NRCS). Analytical data were clustered into functional groups based on soil textural class (FAO) and calculated activity of the clay size minerals. Samples from organic and allophanic soils were flagged as separate categories. The file contain analytical data for 131,472 soil samples, originating from 20,920 profiles. Being based on available data, there are several gaps in the measured data
Soil moisture content by weight, at tension 6 kPa (pF 1.8) (g/100g). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
Depth to bedrock (R horizon) up to 200 cm predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: cm.
Gravimetric content of less than X mm soil material in the fine earth fraction* (e.g. X = 0.002 mm as specified in the analytical method description) (g/100g). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
ABSTRACT: The World Soil Information Service (WoSIS) provides quality-assessed and standardized soil profile data to support digital soil mapping and environmental applications at broad scale levels. Since the release of the ‘WoSIS snapshot 2019’ many new soil data were shared with us, registered in the ISRIC data repository, and subsequently standardized in accordance with the licenses specified by the data providers. The source data were contributed by a wide range of data providers, therefore special attention was paid to the standardization of soil property definitions, soil analytical procedures and soil property values (and units of measurement). We presently consider the following soil chemical properties (organic carbon, total carbon, total carbonate equivalent, total Nitrogen, Phosphorus (extractable-P, total-P, and P-retention), soil pH, cation exchange capacity, and electrical conductivity) and physical properties (soil texture (sand, silt, and clay), bulk density, coarse fragments, and water retention), grouped according to analytical procedures (aggregates) that are operationally comparable. For each profile we provide the original soil classification (FAO, WRB, USDA, and version) and horizon designations as far as these have been specified in the source databases. Three measures for 'fitness-for-intended-use' are provided: positional uncertainty (for site locations), time of sampling/description, and a first approximation for the uncertainty associated with the operationally defined analytical methods. These measures should be considered during digital soil mapping and subsequent earth system modelling that use the present set of soil data. DATA SET DESCRIPTION: The 'WoSIS 2023 snapshot' comprises data for 228k profiles from 217k geo-referenced sites that originate from 174 countries. The profiles represent over 900k soil layers (or horizons) and over 6 million records. The actual number of measurements for each property varies (greatly) between profiles and with depth, this generally depending on the objectives of the initial soil sampling programmes. The data are provided in TSV (tab separated values) format and as GeoPackage. The zip-file (446 Mb) contains the following files: - Readme_WoSIS_202312_v2.pdf: Provides a short description of the dataset, file structure, column names, units and category values (this file is also available directly under 'online resources'). The pdf includes links to tutorials for downloading the TSV files into R respectively Excel. See also 'HOW TO READ TSV FILES INTO R AND PYTHON' in the next section. - wosis_202312_observations.tsv: This file lists the four to six letter codes for each observation, whether the observation is for a site/profile or layer (horizon), the unit of measurement and the number of profiles respectively layers represented in the snapshot. It also provides an estimate for the inferred accuracy for the laboratory measurements. - wosis_202312_sites.tsv: This file characterizes the site location where profiles were sampled. - wosis_2023112_profiles: Presents the unique profile ID (i.e. primary key), site_id, source of the data, country ISO code and name, positional uncertainty, latitude and longitude (WGS 1984), maximum depth of soil described and sampled, as well as information on the soil classification system and edition. Depending on the soil classification system used, the number of fields will vary . - wosis_202312_layers: This file characterises the layers (or horizons) per profile, and lists their upper and lower depths (cm). - wosis_202312_xxxx.tsv : This type of file presents results for each observation (e.g. “xxxx” = “BDFIOD” ), as defined under “code” in file wosis_202312_observation.tsv. (e.g. wosis_202311_bdfiod.tsv). - wosis_202312.gpkg: Contains the above datafiles in GeoPackage format (which stores the files within an SQLite database). HOW TO READ TSV FILES INTO R AND PYTHON: A) To read the data in R, please uncompress the ZIP file and specify the uncompressed folder. setwd("/YourFolder/WoSIS_2023_December/") ## For example: setwd('D:/WoSIS_2023_December/') Then use read_tsv to read the TSV files, specifying the data types for each column (c = character, i = integer, n = number, d = double, l = logical, f = factor, D = date, T = date time, t = time). observations = readr::read_tsv('wosis_202312_observations.tsv', col_types='cccciid') observations ## show columns and first 10 rows sites = readr::read_tsv('wosis_202312_sites.tsv', col_types='iddcccc') sites profiles = readr::read_tsv('wosis_202312_profiles.tsv', col_types='icciccddcccccciccccicccci') profiles layers = readr::read_tsv('wosis_202312_layers.tsv', col_types='iiciciiilcc') layers ## Do this for each observation 'XXXX', e.g. file 'Wosis_202312_orgc.tsv': orgc = readr::read_tsv('wosis_202312_orgc.tsv', col_types='iicciilccdccddccccc') orgc Note: One may also use the following R code (example is for file 'observations.tsv'): observations <- read.table("wosis_202312_observations.tsv", sep = "\t", header = TRUE, quote = "", comment.char = "", stringsAsFactors = FALSE ) B) To read the files into python first decompress the files to your selected folder. Then in python: # import the required library import pandas as pd # Read the observations data observations = pd.read_csv("wosis_202312_observations.tsv", sep="\t") # print the data frame header and some rows observations.head() # Read the sites data sites = pd.read_csv("wosis_202312_sites.tsv", sep="\t") # Read the profiles data profiles = pd.read_csv("wosis_202312_profiles.tsv", sep="\t") # Read the layers data layers = pd.read_csv("wosis_202312_layers.tsv", sep="\t") # Read the soil property data, e.g. 'cfvo' (do this for each observation) cfvo = pd.read_csv("wosis_202312_cfvo.tsv", sep="\t") CITATION: Calisto, L., de Sousa, L.M., Batjes, N.H., 2023. Standardised soil profile data for the world (WoSIS snapshot – December 2023), https://doi.org/10.17027/isric-wdcsoils-20231130 Supplement to: Batjes N.H., Calisto, L. and de Sousa L.M., 2023. Providing quality-assessed and standardised soil data to support global mapping and modelling (WoSIS snapshot 2023). Earth System Science Data, https://doi.org/10.5194/essd-16-4735-2024.
Volumetric Water Content at 33kPa suction in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers.
Bulk density of the fine earth fraction*, field moist (kg/dm³). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
Derived available soil water capacity (volumetric fraction) with FC = pF 2.3 at 7 standard depths predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: v%.
The GLASOD project (1987-1990), carried out for UNEP, has produced a world map of human-induced soil degradation. Data were compiled in cooperation with a large number of soil scientists throughout the world, using uniform Guidelines and international correlation. The status of soil degradation was mapped within loosely defined physiographic units (polygons), based on expert judgement. The type, extent, degree, rate and main causes of degradation have been printed on a global map, at a scale of 1:10 million, and documented in a downloadable database. Information about the areal extent of human-induced soil degradation can be found in an explanatory note.
Soil organic carbon stock in tons per ha for 6 standard depth intervals predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: t / ha.
Model outputs were updated on Dec 20, 2017. This project used a machine learning data-driven model to predict the distribution of soil carbon under mangrove forests globally. Specifically this dataset contains: 1) a compilation of georeferenced and harmonized soil profile data under mangroves compiled from literature, reports and unpublished contributions 2) global mosaics of soil carbon stocks to 1m and 2m depths produced at 100 m resolution 3) tiled predictions of soil carbon stocks produced at 30 m resolution 4) shape file containing the tiling system 5) shape file containing country boundaries used for calculating national level statistics. For detailed methodologies, please see the scientific paper (https://doi.org/10.1088/1748-9326/aabe1c).
Cation exchange capacity of soil in cmolc/kg at 7 standard depths predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: cmolc / kg.
Volumetric Water Content at 10kPa suction in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. This map is the result of resampling the mean SoilGrids 250 m predictions (Turek et al. 2021) for each 5000 m cell.
Surface area is a country's total area, including areas under inland bodies of water and some coastal waterways.
Coarse fragments volumetric in % at 7 standard depths predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: v%.
Volumetric Water Content at 1500kPa suction in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. This map is the result of resampling the mean SoilGrids 250 m predictions (Turek et al. 2021) for each 1000 m cell.
Data.gov Metadata:https://catalog.data.gov/dataset/national-flood-hazard-layer-nfhl GIS Web Services for the FEMA National Flood Hazard Layer (NFHL) Metadata:https://hazards.fema.gov/femaportal/wps/portal/NFHLWMS