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Total carbon at soil depths of 0-20 cm and 20-50 cm, predicted mean and standard deviation.
Pixel values must be back-transformed with
In areas of dense jungle (generally over central Africa), model accuracy is low and therefore artifacts such as banding (striping) might be seen.
Soil property predictions were made by Innovative Solutions for Decision Agriculture Ltd. (iSDA) at 30 m pixel size using machine learning coupled with remote sensing data and a training set of over 100,000 analyzed soil samples.
Carbon, total, predicted mean at 0-20 cm depth
Carbon, total, predicted mean at 20-50 cm depth
Carbon, total, standard deviation at 0-20 cm depth
Carbon, total, standard deviation at 20-50 cm depth
Hengl, T., Miller, M.A.E., Križan, J., et al. African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning. Sci Rep 11, 6130 (2021). doi:10.1038/s41598-021-85639-y