Articles | Volume 18, issue 2
https://doi.org/10.5194/essd-18-989-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-989-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
06 Feb 2026
Data description article |
| 06 Feb 2026
| 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
OpenGeoHub Foundation, Doorwerth, the Netherlands
Davide Consoli
OpenGeoHub Foundation, Doorwerth, the Netherlands
Xuemeng Tian
OpenGeoHub Foundation, Doorwerth, the Netherlands
Travis W. Nauman
private consultant: Moab, UT, USA
Madlene Nussbaum
University of Utrecht, Utrecht, the Netherlands
Mustafa Serkan Isik
OpenGeoHub Foundation, Doorwerth, the Netherlands
Leandro Parente
OpenGeoHub Foundation, Doorwerth, the Netherlands
Yu-Feng Ho
OpenGeoHub Foundation, Doorwerth, the Netherlands
Rolf Simoes
OpenGeoHub Foundation, Doorwerth, the Netherlands
Surya Gupta
Department of Environmental Sciences, University of Basel, Basel 4056, Switzerland
Alessandro Samuel-Rosa
Universidade Tecnológica Federal do Paraná, Santa Helena, Paraná, Brazil
Taciara Zborowski Horst
Universidade Tecnológica Federal do Paraná, Dois Vizinhos, Paraná, Brazil
José L. Safanelli
Woodwell Climate Research Center, Falmouth, MA, USA
Nancy Harris
World Resources Institute, Washington DC, USA
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Total article views: 9,857 (including HTML, PDF, and XML)
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Cited
10 citations as recorded by crossref.
- Graph-Transformer for Spatiotemporal Soil Moisture Forecasting Using Multimodal Remote Sensing Data M. Saki et al. https://doi.org/10.1109/ACCESS.2026.3669499
- Multi-Scale Driving Mechanisms of the Spatiotemporal Distribution of Soil pH in High-Standard Farmland Within the Hilly Regions of Southern China Z. Zeng et al. https://doi.org/10.3390/agriculture16151685
- Organic carbon loss from the black soil region threatens food security in China J. Chen et al. https://doi.org/10.59717/j.xinn-geo.2026.100213
- HU‐SoilCarbonGrids: An Initiative for Providing Comprehensive Information on Soil Organic Carbon Changes in Hungary G. Szatmári et al. https://doi.org/10.1111/ejss.70292
- Tipping Points in Bacterial Richness Amplify Extracellular Enzyme Activities in Northern Peatlands V. Jassey et al. https://doi.org/10.1111/gcb.71099
- Soil Hydraulic Properties of Europe at 500 m Resolution for Topsoil Using EUPTFv2 and LUCAS Soil Data S. Gupta et al. https://doi.org/10.1002/hyp.70670
- Cloud-Based Mapping of Soil Erosion Susceptibility for Catchment Prioritisation in the Western Balkans Using a Modified Erosion Potential Method I. Milevski et al. https://doi.org/10.3390/land15091655
- Challenges in Tropical Dendrochronology: Perspectives from a 10-Year Effort in Eastern Amazonia D. Granato et al. https://doi.org/10.3959/TRR2026-1
- Recent Advances in Remote Sensing of Soil Science N. Tsakiridis et al. https://doi.org/10.3390/rs18101540
- Machine Learning-Based Spatial Mapping of Soil Organic Carbon and Its Climatic and Topographic Drivers in the Arid Regions Y. Chen et al. https://doi.org/10.3390/rs18162708
10 citations as recorded by crossref.
- Graph-Transformer for Spatiotemporal Soil Moisture Forecasting Using Multimodal Remote Sensing Data M. Saki et al. https://doi.org/10.1109/ACCESS.2026.3669499
- Multi-Scale Driving Mechanisms of the Spatiotemporal Distribution of Soil pH in High-Standard Farmland Within the Hilly Regions of Southern China Z. Zeng et al. https://doi.org/10.3390/agriculture16151685
- Organic carbon loss from the black soil region threatens food security in China J. Chen et al. https://doi.org/10.59717/j.xinn-geo.2026.100213
- HU‐SoilCarbonGrids: An Initiative for Providing Comprehensive Information on Soil Organic Carbon Changes in Hungary G. Szatmári et al. https://doi.org/10.1111/ejss.70292
- Tipping Points in Bacterial Richness Amplify Extracellular Enzyme Activities in Northern Peatlands V. Jassey et al. https://doi.org/10.1111/gcb.71099
- Soil Hydraulic Properties of Europe at 500 m Resolution for Topsoil Using EUPTFv2 and LUCAS Soil Data S. Gupta et al. https://doi.org/10.1002/hyp.70670
- Cloud-Based Mapping of Soil Erosion Susceptibility for Catchment Prioritisation in the Western Balkans Using a Modified Erosion Potential Method I. Milevski et al. https://doi.org/10.3390/land15091655
- Challenges in Tropical Dendrochronology: Perspectives from a 10-Year Effort in Eastern Amazonia D. Granato et al. https://doi.org/10.3959/TRR2026-1
- Recent Advances in Remote Sensing of Soil Science N. Tsakiridis et al. https://doi.org/10.3390/rs18101540
- Machine Learning-Based Spatial Mapping of Soil Organic Carbon and Its Climatic and Topographic Drivers in the Arid Regions Y. Chen et al. https://doi.org/10.3390/rs18162708
Saved (final revised paper)
Latest update: 25 Sep 2026
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.
We used satellite data and thousands of soil samples to create detailed global maps showing how...
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