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A new map of agricultural land in Africa builds towards a soil information system

Expert Contributions 30 Jun 2021 - 09:36 SAST

A new map of agricultural land in Africa builds towards a soil information system

Expert Contributions 30 Jun 2021 - 09:36 SAST

By Jeroen Huising and Eunice Wangui Mwangi, EU2020-Soils4Africa

Soils4Africa aims to develop a continental-scale Soil Information System, built upon a baseline of primary soil data collected from 20 000 locations across Africa. The project aims to produce a baseline which can be used for informing and monitoring of sustainable intensification in Africa. As part of the process it has mapped agricultural land on the continent.

Good quality soil information is essential for planning the most efficient use of fertilisers, choosing the right seed varieties, and determining the best water management measures for an area.

Existing soil databases for Africa often are compilations of datasets generated for different purposes, and therefore based on a variety of methods for soil sampling and analysis. Generally, the data were collected using purposive sampling and analysed using conventional soil laboratory methods. As such, they rarely provide direct measurements based on sound (geo)statistical sampling frames. Further, the available data is seldom shared as open data. These compounding factors introduce a strong bias in the data and thereby preclude accurate assessment of the occurrence of soil constraints, quantification of risk factors and reliable assessments of change in soil health/quality.

The Soils4Africa project, which started in 2020 and is scheduled for completion by the end of 2024, will develop a soil information system that uses a sampling framework, uniform methodologies for data gathering, accompanied with thorough documentation of the methodologies. The project will develop a methodology that can also be used for continental scale soil quality monitoring in the future, as well as for national level data collection and soil monitoring.

Mapping agricultural land for baseline data

Part of the process is mapping agricultural land in Africa as the basis for the selection of the 20 000 sites where the project will collect soil samples, and which will be analysed to produce the baseline data for a continental-level soil information system. The system will help improve the targeting and monitoring of interventions to boost sustainable intensification of agriculture in Africa.  

The difficulty is that land use in Africa is very mixed, and agricultural land is found across various land cover types. To more accurately identify agricultural land, the project uses fractional cover, or ‘cropland probability’, where pixels with Cropland Probability higher than a certain threshold will be considered to be croplands and considered as potential soil sampling sites.

Making use of fractional cover

The Copernicus dataset already includes the category “cropland,” (by definition part of agricultural land) as well as information about “fractional cover”, or the percentage of a particular pixel under a particular kind of land cover (for example, 30% of a 100 x 100 m pixel could be forest and 20% could be shrubland). 

The Soils4Africa map takes into account how fractional cover varies over an area to establish rules for interpreting its land cover data to determine whether it is under agricultural use and for what purpose. These rules were validated by comparing it with ground level information on land use (or land use pattern) for specific areas drawn from the interpretation of satellite imagery from Google Earth.

For example, ground-level observation shows that forest cover upwards of 30% in a given area when matched by shrubland cover of over 30%, is characterized by woody vegetation with a smooth canopy. Therefore, such an area is more likely to be under plantations rather than natural forest. Thus, such an area should be counted as agricultural land, even if less than 15% of it is under crops.

The inference rules used for the map are presented in this report. They can be applied to other land cover datasets, provided that they are validated and adjusted to account for any differences between their land cover classification system and that of the Copernicus Global Land Cover map.

Copernicus data for Africa is organised into tiles of 20 x 20 arc degrees. The inference rules were formed based on Copernicus data and Google Earth imagery mainly for the area enclosed within Tiles 1, 2, and 7 (covering central and west Africa), and results were validated for the remaining tiles. The rules were then extrapolated to data from other tiles to derive the map of agricultural land over the rest of the continent. 

A map that paves the way for a soil information system

On 23 February 2021, the Soils4Africa project released a map of agricultural land of continental Africa, depicting the distribution of agricultural land (i.e. growing crops, grazing livestock, and various other agricultural uses).

The map is based on Copernicus Global Land Cover data which shows actual land cover (forests, grasslands, croplands, lakes, wetlands, built-up area) at 100 x 100 m resolution. The land cover data was overlaid on high resolution satellite imagery, which is then used to determine the land use (by visual interpretation) associated with the various land cover patterns on the Copernicus Global Land Cover map.

Besides its high quality and high resolution, Copernicus land cover data offers time series satellite imagery. More importantly, the Copernicus Global Land Service is a continuous process and its datasets are updated annually. This means that the Soils4Africa map of agricultural land can be updated every time the land cover data for the new year becomes available (the map is currently based on 2019 data). 

The map is available in Geotiff file format, in a 100 x 100 m resolution and can be downloaded from: https://www.soils4africa-h2020.eu/serverspecific/soils4africa/images/Documents/MAL_AFRICA.rar 

Bear in mind, the map is under review and subject to changes if deemed necessary. Production of the map was led by The International Institute of Tropical Agriculture (IITA) and Regional Centre for Mapping of Resources for Development (RCMRD).