The Africa Soil Information Service (AfSIS) Web Map Service supports the Open Geospatial Consortium (OGC) OpenGIS Web Map Service (WMS) Implementation Specifications and dynamically produces maps of georeferenced data. Support of this international standard opens the AfSIS map collection to users who can access its contents via machine-to-machine interaction. View our online maps here.

The need to maintain the health of the soil resource base as an imperative for sustainable development is increasingly being recognized. Science and technological developments in remote sensing are providing new opportunities for low cost and efficient applications for characterizing and monitoring the health of the soil resource base. We are pleased to introduce this spectral library of world soils, which will provide a valuable resource for research and applications for sensing soil quality both in the laboratory and from space.

Hydrologically Corrected / Adjusted SRTM Digital Elevation Model (AfrHySRTM)

AfrHySRTM is an adjusted elevation raster in which any depressions in the source Digital Elevation Model (DEM) have been eliminated (filled), but allowing for internal drainage since some landscapes contain natural depressions. These landscapes have their own internal drainage systems, which are not connected to adjacent watersheds. Null cells (drains) were placed in depressions exceeding a depth limit of 20 m and with no less than 1000 cells (pixels) during the DEM adjustment process.

The development of evidence-based soil management recommendations involves the derivation of descriptive and quantitative models to predict the performance of specific Integrated Soil Fertilty Management (ISFM) recommendations under varied, soil, climatic and socio-economic conditions. ISFM technologies relate to fertilizer application rates, soil organic matter management, use of legumes, and tillage operations in cropping systems.

There currently are no consistent, large-area (hundreds of square kilometers and larger) mechanisms for testing the efficacy of fertilizer use, conservation tillage, integrated soil fertility management, erosion control, livestock stocking, and agroforestry interventions in SSA.

There are some notable problems associated with using soil legacy data for soil mapping and surveillance. For the most part, soil legacy data were not purposely sampled to cover large areas using statistical sampling criteria and randomization procedures, and are thus not representative of the overall condition of soils in SSA. Most traditional soil surveys emphasized management invariant sub-soil properties that may not reflect changes in soil health and degradation.

ICRAF-ISRIC VNIR Soil Spectral Library now available here.

AfSIS has produced large-area mosaics of radiometrically calibrated, orthorectified LandsatMSS,TM and ETM+ images. We have also developed SRTM terrain model derivatives (e.g. terrain units, slopes, curvatures, contributing areas, compound topographic and erosion/deposition indices and watershed delineations).

Digital soil mapping is the creation of spatial soil information systems using field and laboratory methods coupled with spatial and non-spatial soil inference systems (Lagacherie, McBratney and Voltz, 2006). A digital soil map is a spatial database of soil properties that is based on a statistical sample of landscapes or regions and that permits functional interpretation, spatial prediction and mapping of soil properties relevant to soil management and policy decisions.

AfSIS uses a variety of free and open source software (FOSS) for Web-based services, data management, and statistical analysis.

 Mobile Data Entry Using CyberTracker Software

A GPS-based data entry system has been developed and deployed for AfSIS sentinel landscape field surveys. This system uses CyberTracker software, which is an efficient way of gathering geo-referenced information. Field data are backed up to a field computer and external drives in field and regularly transmitted to the central AfSIS data repository at the World Agroforestry Centre (ICRAF) and the Tropical Soil Biology and Fertility Institute (TSBF), Nairobi. The data entry system includes efficient electronic workflows that are specifically adapted to the AfSIS field surveys, and have been extensively tested in field.