iSDAsoil: soil sand content (USDA system) for Africa predicted at 30 m resolution at 0-20 and 20-50 cm depths

iSDAsoil dataset soil sand content in % 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, LandPKS, 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_sand_tot_psa_m_30m_*..*cm_2001..2017_v0.13_wgs84.tif = predicted soil sand content mean value,
• sol_sand_tot_psa_md_30m_*..*cm_2001..2017_v0.13_wgs84.tif = predicted soil sand content 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: sand_tot_psa 
R-square: 0.736 
Fitted values sd: 22.8 
RMSE: 13.7 

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

Residuals:
    Min      1Q  Median      3Q     Max 
-80.626  -5.321   0.221   6.071  88.686 

Coefficients:
               Estimate Std. Error t value Pr(>|t|)    
(Intercept)    6.687471  24.022001   0.278 0.780714    
regr.ranger    1.060521   0.003503 302.742  < 2e-16 ***
regr.xgboost  -0.018718   0.004910  -3.812 0.000138 ***
regr.cubist    0.031749   0.003922   8.096 5.73e-16 ***
regr.nnet     -0.161127   0.422746  -0.381 0.703098    
regr.cvglmnet -0.028217   0.004462  -6.323 2.57e-10 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 13.65 on 122261 degrees of freedom
Multiple R-squared:  0.736,	Adjusted R-squared:  0.736 
F-statistic: 6.818e+04 on 5 and 122261 DF,  p-value: < 2.2e-16

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