Sand Content In % (Kg / Kg) At 6 Standard Depths (0, 10, 30, 60, 100 And 200 Cm) At 250 M Resolution ...

Sand content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution. Based on machine learning predictions from global compilation of soil profiles and samples. Processing steps are described in detail here . Antartica is not included. To access and visualize maps us...

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Bibliographic Details
Main Author: Hengl, Tomislav
Format: Dataset
Language:English
Published: Zenodo 2018
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.1476852
https://zenodo.org/record/1476852
id ftdatacite:10.5281/zenodo.1476852
record_format openpolar
spelling ftdatacite:10.5281/zenodo.1476852 2023-06-11T04:07:19+02:00 Sand Content In % (Kg / Kg) At 6 Standard Depths (0, 10, 30, 60, 100 And 200 Cm) At 250 M Resolution ... Hengl, Tomislav 2018 https://dx.doi.org/10.5281/zenodo.1476852 https://zenodo.org/record/1476852 en eng Zenodo https://dx.doi.org/10.5281/zenodo.1476851 Open Access Creative Commons Attribution Share-Alike 4.0 https://creativecommons.org/licenses/by-sa/4.0 info:eu-repo/semantics/openAccess LandGIS sand fraction soil texture Dataset dataset 2018 ftdatacite https://doi.org/10.5281/zenodo.147685210.5281/zenodo.1476851 2023-05-02T11:03:53Z Sand content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution. Based on machine learning predictions from global compilation of soil profiles and samples. Processing steps are described in detail here . Antartica is not included. To access and visualize maps use: https://landgis.opengeohub.org All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: sol = theme: soil, sand.wfraction = variable: sand weight fraction, usda.3a1a1a = determination method: laboratory method code, m = mean value, 250m = spatial resolution / block support: 250 m, b10..10cm = vertical reference: 10 cm depth below surface, 1950..2017 = time reference: period 1950-2017, v0.1 = version number: 0.1, ... : {"references": ["USDA-NRCS, (2014) Laboratory Methods Manual (SSIR 42). U.S. Department of Agriculture, Natural Resources Conservation Service, National Soil Survey Center.", "Hengl T, Mendes de Jesus J, Heuvelink GBM, Ruiperez Gonzalez M, Kilibarda M, Blagoti\u0107 A, et al. (2017) SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 12(2): e0169748."]} ... Dataset antartic* DataCite Metadata Store (German National Library of Science and Technology) Gonzalez ENVELOPE(-58.250,-58.250,-63.917,-63.917)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic LandGIS
sand fraction
soil texture
spellingShingle LandGIS
sand fraction
soil texture
Hengl, Tomislav
Sand Content In % (Kg / Kg) At 6 Standard Depths (0, 10, 30, 60, 100 And 200 Cm) At 250 M Resolution ...
topic_facet LandGIS
sand fraction
soil texture
description Sand content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution. Based on machine learning predictions from global compilation of soil profiles and samples. Processing steps are described in detail here . Antartica is not included. To access and visualize maps use: https://landgis.opengeohub.org All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: sol = theme: soil, sand.wfraction = variable: sand weight fraction, usda.3a1a1a = determination method: laboratory method code, m = mean value, 250m = spatial resolution / block support: 250 m, b10..10cm = vertical reference: 10 cm depth below surface, 1950..2017 = time reference: period 1950-2017, v0.1 = version number: 0.1, ... : {"references": ["USDA-NRCS, (2014) Laboratory Methods Manual (SSIR 42). U.S. Department of Agriculture, Natural Resources Conservation Service, National Soil Survey Center.", "Hengl T, Mendes de Jesus J, Heuvelink GBM, Ruiperez Gonzalez M, Kilibarda M, Blagoti\u0107 A, et al. (2017) SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 12(2): e0169748."]} ...
format Dataset
author Hengl, Tomislav
author_facet Hengl, Tomislav
author_sort Hengl, Tomislav
title Sand Content In % (Kg / Kg) At 6 Standard Depths (0, 10, 30, 60, 100 And 200 Cm) At 250 M Resolution ...
title_short Sand Content In % (Kg / Kg) At 6 Standard Depths (0, 10, 30, 60, 100 And 200 Cm) At 250 M Resolution ...
title_full Sand Content In % (Kg / Kg) At 6 Standard Depths (0, 10, 30, 60, 100 And 200 Cm) At 250 M Resolution ...
title_fullStr Sand Content In % (Kg / Kg) At 6 Standard Depths (0, 10, 30, 60, 100 And 200 Cm) At 250 M Resolution ...
title_full_unstemmed Sand Content In % (Kg / Kg) At 6 Standard Depths (0, 10, 30, 60, 100 And 200 Cm) At 250 M Resolution ...
title_sort sand content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution ...
publisher Zenodo
publishDate 2018
url https://dx.doi.org/10.5281/zenodo.1476852
https://zenodo.org/record/1476852
long_lat ENVELOPE(-58.250,-58.250,-63.917,-63.917)
geographic Gonzalez
geographic_facet Gonzalez
genre antartic*
genre_facet antartic*
op_relation https://dx.doi.org/10.5281/zenodo.1476851
op_rights Open Access
Creative Commons Attribution Share-Alike 4.0
https://creativecommons.org/licenses/by-sa/4.0
info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.5281/zenodo.147685210.5281/zenodo.1476851
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