There is a newer version of the record available.

Published October 30, 2018 | Version v0.1
Dataset Open

Soil organic carbon content in x 5 g / kg at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution

  • 1. Envirometrix Ltd

Description

Soil organic carbon content in × 5 g / kg (to convert to % divide by 2) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution. Predicted from a global compilation of soil points. 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,
  • organic.carbon = variable: soil organic carbon content in x 5 g / kg,
  • usda.6a1c = 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,

Files

sol_organic.carbon_usda.6a1c_m.png

Files (17.4 GB)

Name Size Download all
md5:abde57f16684141a3cdcb54627a5402d
970.1 kB Preview Download
md5:8b493d310a0e9b93b16e45b4c242a693
2.3 kB Download
md5:fcc204e8818686f7e621cfc2b2499b05
1.7 GB Preview Download
md5:bc9d5580302d9647698097d85195a053
1.6 GB Preview Download
md5:3ed234457b17bce04fbc0b1e7add09ff
1.4 GB Preview Download
md5:79a1e1d7ce1bfa755d0312c2976f2b5d
1.3 GB Preview Download
md5:390ad3173de2a27bb8b7551eaf87bce1
1.5 GB Preview Download
md5:42263f71df93d72a537a219c7c8085ec
1.4 GB Preview Download
md5:46ddde65172ba2b08d361d81921a99d7
1.6 GB Preview Download
md5:6b75792404cb3bc4f224e400b1409338
1.5 GB Preview Download
md5:b18ff99cbee3fc430ef1944066e85b92
1.3 GB Preview Download
md5:b4c5850eb1472d8d7e09ac2a590d23d6
1.3 GB Preview Download
md5:f516dda70786d6602fb194a0d462fade
1.4 GB Preview Download
md5:5ddd10f17292fbc28acbe4a924a57af1
1.3 GB Preview Download

Additional details

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, Blagotić A, et al. (2017) SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 12(2): e0169748.