Articles | Volume 18, issue 2
https://doi.org/10.5194/essd-18-989-2026
https://doi.org/10.5194/essd-18-989-2026
Data description paper
 | 
06 Feb 2026
Data description paper |  | 06 Feb 2026

OpenLandMap-soildb: global soil information at 30 m spatial resolution for 2000–2022+ based on spatiotemporal Machine Learning and harmonized legacy soil samples and observations

Tomislav Hengl, Davide Consoli, Xuemeng Tian, Travis W. Nauman, Madlene Nussbaum, Mustafa Serkan Isik, Leandro Parente, Yu-Feng Ho, Rolf Simoes, Surya Gupta, Alessandro Samuel-Rosa, Taciara Zborowski Horst, José L. Safanelli, and Nancy Harris

Data sets

OpenLandMap-soildb Davide Consoli et al. https://doi.org/10.5281/zenodo.15470431

An Open Compendium of Soil Datasets: Soil Observations and Measurements (V1.0.1) T. Hengl and S. Gupta https://doi.org/10.5281/zenodo.15593990

Model code and software

openlandmap/soildb Tomislav Hengl and Xuemeng Tian https://doi.org/10.5281/zenodo.15608971

An Open Compendium of Soil Datasets: Soil Observations and Measurements (V1.0.1) T. Hengl and S. Gupta https://doi.org/10.5281/zenodo.15593990

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Short summary
We used satellite data and thousands of soil samples to create detailed global maps showing how soil changes over time. These maps reveal important patterns in soil health, such as a significant global loss of soil carbon in the past 25 years. Our results help track land degradation and support better land restoration efforts. This work provides a new global tool for understanding and protecting soil, a key resource for food, water, and climate.
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