SOIL MORPHOLOGY

SoilGridsTM (hereafter SoilGrids) is a system for global digital soil mapping that uses state-of-the-art machine learning methods to map the spatial distribution of soil properties across the globe. SoilGrids prediction models are fitted using over 230 000 soil profile observations from the WoSIS database and a series of environmental covariates. Covariates were selected from a pool of over 400 environmental layers from Earth observation derived products and other environmental information including climate, land cover and terrain morphology.

[last updated in 2017]

Knowledge of soil properties such as organic carbon content, clay content and pH is vital for agriculture and climate change analysis in Africa. ISRIC has launched a new type of freely accessible soil property maps for Africa. The maps contain predictions of seven soil properties at six standard depths at 1 km resolution. The soil property maps as well as the software to generate them are available for download under a Creative Commons licence.

ISRIC—World Soil Information is compiling legacy soil profile data for Sub-Saharan Africa, as a project activity of the Globally integrated-Africa Soil Information Service (AfSIS) project; SEE LINK BELOW from ISRIC.

The representation of land surface processes in hydrological and climatic models critically depends on the soil water characteristics curve (SWCC) that defines the plant availability and water storage in the vadose zone. Despite the availability of SWCC datasets in the literature, significant efforts are required to harmonize reported data before SWCC parameters can be determined and implemented in modeling applications. In this work, a total of 15,259 SWCCs from 2,702 sites were assembled from published literature, harmonized, and quality-checked.

Contains the following layers
a.    Clay
b.    Course fragment content  
c.    Rootzone depth
d.    Rootzone soil texture
e.    Sand content
f.    Soil Morphons
g.    Soter soil map
h.    Zambia soils.