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

iSDAsoil dataset soil texture classes derived from sand, silt and clay fractions 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_texture.class_c_30m_*..*cm_2001..2017_v0.13_wgs84.tif = soil texture class,

Classes:

Code,Name,Value,Color
Cl,clay,1,#d5c36b
SiCl,silty clay,2,#b96947
SaCl,sandy clay,3,#9d3706
ClLo,clay loam,4,#ae868f
SiClLo,silty clay loam,5,#f86714
SaClLo,sandy clay loam,6,#46d143
Lo,loam,7,#368f20
SiLo,silt loam,8,#3e5a14
SaLo,sandy loam,9,#ffd557
Si,silt,10,#fff72e
LoSa,loamy sand,11,#ff5a9d
Sa,sand,12,#ff005b
NODATA,,255,#ffffff

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