SoilGrids250m: Global gridded soil information based on machine learning
SoilGrids250m: Global gridded soil information based on machine learning
About this item
Full title
Author / Creator
Hengl, Tomislav , Mendes de Jesus, Jorge , Heuvelink, Gerard B M , Ruiperez Gonzalez, Maria , Kilibarda, Milan , Blagotić, Aleksandar , Shangguan, Wei , Wright, Marvin N , Geng, Xiaoyuan , Bauer-Marschallinger, Bernhard , Guevara, Mario Antonio , Vargas, Rodrigo , MacMillan, Robert A , Batjes, Niels H , Leenaars, Johan G B , Ribeiro, Eloi , Wheeler, Ichsani , Mantel, Stephan and Kempen, Bas
Publisher
United States: Public Library of Science
Journal title
Language
English
Formats
Publication information
Publisher
United States: Public Library of Science
Subjects
More information
Scope and Contents
Contents
This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse...
Alternative Titles
Full title
SoilGrids250m: Global gridded soil information based on machine learning
Authors, Artists and Contributors
Author / Creator
Mendes de Jesus, Jorge
Heuvelink, Gerard B M
Ruiperez Gonzalez, Maria
Kilibarda, Milan
Blagotić, Aleksandar
Shangguan, Wei
Wright, Marvin N
Geng, Xiaoyuan
Bauer-Marschallinger, Bernhard
Guevara, Mario Antonio
Vargas, Rodrigo
MacMillan, Robert A
Batjes, Niels H
Leenaars, Johan G B
Ribeiro, Eloi
Wheeler, Ichsani
Mantel, Stephan
Kempen, Bas
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_plos_journals_1869029969
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_1869029969
Other Identifiers
ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0169748
