iSDAsoil: soil extractable Phosphorus for Africa predicted at 30 m resolution at 0-20 and 20-50 cm depths

iSDAsoil dataset soil extractable Phosphorus (P) 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.p_mehlich3_m_30m_*..*cm_2001..2017_v0.13_wgs84.tif = predicted soil extractable Phosphorus mean value,
• sol_log.p_mehlich3_md_30m_*..*cm_2001..2017_v0.13_wgs84.tif = predicted soil extractable Phosphorus 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.p_mehlich3 
R-square: 0.486 
Fitted values sd: 0.687 
RMSE: 0.707 

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

Residuals:
    Min      1Q  Median      3Q     Max 
-3.2892 -0.3942 -0.0637  0.2614  4.9466 

Coefficients:
               Estimate Std. Error t value Pr(>|t|)    
(Intercept)    3.378801   3.143200   1.075    0.282    
regr.ranger    0.861655   0.011099  77.631  < 2e-16 ***
regr.xgboost   0.066139   0.013091   5.052 4.38e-07 ***
regr.cubist    0.157674   0.008886  17.744  < 2e-16 ***
regr.nnet     -1.649621   1.442240  -1.144    0.253    
regr.cvglmnet  0.013628   0.010407   1.310    0.190    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.7066 on 53493 degrees of freedom
Multiple R-squared:  0.486,	Adjusted R-squared:  0.486 
F-statistic: 1.012e+04 on 5 and 53493 DF,  p-value: < 2.2e-16

To back-transform values (y) to ppm use the following formula:

ppm = expm1( y / 10 )

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