Articles | Volume 9, issue 1
https://doi.org/10.5194/soil-9-277-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/soil-9-277-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Accuracy of regional-to-global soil maps for on-farm decision-making: are soil maps “good enough”?
Jonathan J. Maynard
CORRESPONDING AUTHOR
Sustainability Innovation Lab, University of Colorado, Boulder, Colorado, USA
present address: National Soil Survey Center, USDA-NRCS, Tangent, Oregon, USA
Edward Yeboah
Soil Research Institute, Soil Microbiology Division, Council for Scientific and Industrial Research (CSIR),
Kwadaso-Kumasi, Ghana
Stephen Owusu
Department of Soil Science, Institute of Environmental Sciences, Hungarian University of Agriculture and
Life Sciences, Gödöllő, Hungary
Soil Research Institute, Soil Genesis, Survey and Classification Division, Council for Scientific and Industrial
Research (CSIR), Kwadaso-Kumasi, Ghana
Michaela Buenemann
Department of Geography, New Mexico State University, Las Cruces, New Mexico, USA
Jason C. Neff
Sustainability Innovation Lab, University of Colorado, Boulder, Colorado, USA
Jeffrey E. Herrick
Jornada Experimental Range, USDA-ARS, Las Cruces, New Mexico, USA
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- National baseline high-resolution mapping of soil organic carbon in Moroccan cropland areas A. Bouasria et al. 10.1016/j.geodrs.2025.e00941
- Mapping soil fertility properties in central Ethiopia at 100 m spatial resolution M. Redi et al. 10.1016/j.geodrs.2025.e00952
- Development of Mathematical and Computational Models for Predicting Agricultural Soil–Water Management Properties (ASWMPs) to Optimize Intelligent Irrigation Systems and Enhance Crop Resilience B. Tóth et al. 10.3390/agronomy15040942
- Soil Properties Classification in Sustainable Agriculture Using Genetic Algorithm-Optimized and Deep Neural Networks Y. Tynchenko et al. 10.3390/su16198598
- Towards data-driven tropical forest restoration: Uncovering spatial variation, interactions and historical management effects on nutrients along soil depth gradients N. Tasnim et al. 10.1016/j.scitotenv.2024.176756
- Unraveling drivers of maize (Zea mays L.) yield variability in Ghana: A machine learning approach A. Kouame et al. 10.1016/j.compag.2025.110647
- Operational Digital Soil Mapping: Achievements, Challenges and Future Strategies to Go Beyond P. Lagacherie 10.1111/ejss.70139
- How Accurately Is Topsoil Texture Shown on Agricultural Soil Maps? A Case Study of Eleven Fields Located in Poland M. Stępień et al. 10.3390/land13111852
- Assessment of trade-off balance of maize stover use for bioenergy and soil erosion mitigation in Western Kenya K. Jindo et al. 10.3389/fsufs.2025.1409457
- Spatial Downscaling of Global Categorical Soil Information Into Data Suitable for Land-Use Management T. FLYNN 10.2139/ssrn.4496677
- Possibilities of attribution of the content of soil separates according to PTG 2008/USDA to selected granulometric groups of PTG 1956 and distinguished on agricultural soil maps M. Stępień et al. 10.37501/soilsa/193375
- Evaluation of pedotransfer functions to estimate some of soil hydraulic characteristics in North Africa: A case study from Morocco A. Beniaich et al. 10.3389/fenvs.2023.1090688
12 citations as recorded by crossref.
- Ensemble Band Selection for Quantification of Soil Total Nitrogen Levels from Hyperspectral Imagery K. Misbah et al. 10.3390/rs16142549
- Spatial downscaling of global soil texture classes into 30 m images at the province scale T. Flynn & R. Kostecki 10.1016/j.geomat.2024.100028
- National baseline high-resolution mapping of soil organic carbon in Moroccan cropland areas A. Bouasria et al. 10.1016/j.geodrs.2025.e00941
- Mapping soil fertility properties in central Ethiopia at 100 m spatial resolution M. Redi et al. 10.1016/j.geodrs.2025.e00952
- Development of Mathematical and Computational Models for Predicting Agricultural Soil–Water Management Properties (ASWMPs) to Optimize Intelligent Irrigation Systems and Enhance Crop Resilience B. Tóth et al. 10.3390/agronomy15040942
- Soil Properties Classification in Sustainable Agriculture Using Genetic Algorithm-Optimized and Deep Neural Networks Y. Tynchenko et al. 10.3390/su16198598
- Towards data-driven tropical forest restoration: Uncovering spatial variation, interactions and historical management effects on nutrients along soil depth gradients N. Tasnim et al. 10.1016/j.scitotenv.2024.176756
- Unraveling drivers of maize (Zea mays L.) yield variability in Ghana: A machine learning approach A. Kouame et al. 10.1016/j.compag.2025.110647
- Operational Digital Soil Mapping: Achievements, Challenges and Future Strategies to Go Beyond P. Lagacherie 10.1111/ejss.70139
- How Accurately Is Topsoil Texture Shown on Agricultural Soil Maps? A Case Study of Eleven Fields Located in Poland M. Stępień et al. 10.3390/land13111852
- Assessment of trade-off balance of maize stover use for bioenergy and soil erosion mitigation in Western Kenya K. Jindo et al. 10.3389/fsufs.2025.1409457
- Spatial Downscaling of Global Categorical Soil Information Into Data Suitable for Land-Use Management T. FLYNN 10.2139/ssrn.4496677
2 citations as recorded by crossref.
- Possibilities of attribution of the content of soil separates according to PTG 2008/USDA to selected granulometric groups of PTG 1956 and distinguished on agricultural soil maps M. Stępień et al. 10.37501/soilsa/193375
- Evaluation of pedotransfer functions to estimate some of soil hydraulic characteristics in North Africa: A case study from Morocco A. Beniaich et al. 10.3389/fenvs.2023.1090688
Latest update: 02 Jul 2025
Short summary
Accurate information on soil properties is critical for identifying soil limitations and the management practices needed to improve crop yields on smallholder farms. This study evaluated the accuracy of soil map information for agronomic decision-making. Based on four publicly available soil maps in Ghana, we found that soil map data significantly overestimated crop suitability, potentially leading to ineffective agronomic investments by smallholder farmers.
Accurate information on soil properties is critical for identifying soil limitations and the...