An ensemble estimate of Australian soil organic carbon using machine learning and process-based modelling

Wang, Lingfei; Abramowitz, Gab; Wang, Ying-Ping; Pitman, Andy; Viscarra Rossel, Raphael A.

doi:https://doi.org/10.5194/soil-10-619-2024

Articles | Volume 10, issue 2

https://doi.org/10.5194/soil-10-619-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/soil-10-619-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 10, issue 2

Original research article

|

10 Sep 2024

Original research article |

| 10 Sep 2024

An ensemble estimate of Australian soil organic carbon using machine learning and process-based modelling

Lingfei Wang, Gab Abramowitz, Ying-Ping Wang, Andy Pitman, and Raphael A. Viscarra Rossel

Data sets

Soil and Landscape Grid National Soil Attribute Maps - Clay (3" resolution) - Release 2. v5. CSIRO Brendan Malone and Ross Searle https://doi.org/10.25919/hc4s-3130

Soil and Landscape Grid National Soil Attribute Maps - Bulk Density - Whole Earth - Release 2 Brendan Malone https://doi.org/10.25919/gxyn-pd07

MODIS/Terra Net Primary Production Gap-Filled Yearly L4 Global 500m SIN Grid V061 S. Running and M. Zhao https://doi.org/10.5067/MODIS/MOD17A3HGF.061

Model code and software

Wanglingfei170/MIMICS: MIMICS-Australia (v1.0-MIMICS-Aus) Lingfei Wang https://doi.org/10.5281/zenodo.13638194

Short summary

Effective management of soil organic carbon (SOC) requires accurate knowledge of its...