iSDAsoil: soil effective Cation Exchange Capacity (eCEC) for Africa predicted at 30 m resolution at 0-20 and 20-50 cm depths

iSDAsoil dataset soil effective Cation Exchange Capacity (eCEC) log-transformed predicted at 30 m resolution for 0–20 and 20–50 cm depth intervals. Data has been projected in WGS84 coordinate system and compiled as COG. Predictions have been generated using multi-scale Ensemble Machine Learning with 250 m (MODIS, PROBA-V, climatic variables and similar) and 30 m (DTM derivatives, Landsat, Sentinel-2 and similar) resolution covariates. For model training we use a pan-African compilations of soil samples and profiles (iSDA points, AfSPDB, and other national and regional soil datasets). Cite as:

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). https://doi.org/10.1038/s41598-021-85639-y

To open the maps in QGIS and/or directly compute with them, please use the Cloud-Optimized GeoTIFF version.

Layer description:

sol_log.ecec.f_tot_mehlich3_m_30m_*..*cm_2001..2017_v0.13_wgs84.tif = predicted soil eCEC mean value,

sol_log.ecec.f_mehlich3_md_30m_*..*cm_2001..2017_v0.13_wgs84.tif = predicted soil eCEC model (prediction) errors,

Model errors were derived using bootstrapping: md is derived as standard deviation of individual learners from 5-fold cross-validation (using spatial blocking). The model 5-fold cross-validation (mlr::makeStackedLearner) for this variable indicates:

Variable: log.ecec.f
R-square: 0.754
Fitted values sd: 0.729
RMSE: 0.417

Random forest model:
Call:
stats::lm(formula = f, data = d)

Residuals:
Min 1Q Median 3Q Max
-3.2877 -0.1888 0.0097 0.2023 3.1494

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.807991 1.806781 1.554 0.1202
regr.ranger 1.046105 0.004845 215.911 < 2e-16 ***
regr.xgboost -0.016558 0.005912 -2.801 0.0051 **
regr.cubist 0.031843 0.005063 6.289 3.21e-10 ***
regr.nnet -1.142820 0.713071 -1.603 0.1090
regr.cvglmnet -0.027630 0.005607 -4.928 8.34e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.4166 on 66380 degrees of freedom
Multiple R-squared: 0.7538, Adjusted R-squared: 0.7538
F-statistic: 4.065e+04 on 5 and 66380 DF, p-value: < 2.2e-16

To back-transform values (y) to cmol(+)/kg use the following formula:

cmol(+)/kg = expm1( y / 10 )

To submit an issue or request support please visit https://isda-africa.com/isdasoil