Co-Production of a 10-m Cropland Extent Map for Continental Africa using
Sentinel-2, Cloud Computing, and the Open-Data-Cube
Abstract
A central focus for governing bodies in Africa is the need to secure the
necessary food sources to support their populations. It has been
estimated that the current production of crops will need to double by
2050 to meet future needs for food production. Higher level crop-based
products that can assist with managing food insecurity, such as cropping
watering intensities, crop types, or crop productivity, require as a
starting point precise and accurate cropland extent maps indicating
where cropland occurs. Current continental cropland extent maps of
Africa are either inaccurate, have too coarse spatial resolutions, or
are not updated regularly. An accurate, high-resolution, and regularly
updated cropland extent map for the African continent is therefore
recognized as a gap in the current crop monitoring services. Using
Digital Earth Africa’s Open Data Cube platform, and working in
conjunction with multiple regional African geospatial institutions, we
co-develop a 10 metre resolution cropland extent map over the African
continent using a Random Forest machine learning classifier and an
annual time-series of Sentinel-2 satellite images. Members of the
regional African geospatial institutions (RCMRD, OSS, Afrigist,
AGRHYMET, and NADMO) were instrumental in defining the specifications of
the product, in developing and implementing a continental scale
reference data collection strategy, and assisted with iterative model
building. The cropland extent map comes packaged with three layers: a
pixel-based classification, a pixel-based cropland probability layer,
and an object-based segmentation filtered classification. All the
components of Digital Earth Africa’s cropland extent map: models,
reference data, code, and results are open source and freely available
online through Digital Earth Africa’s mapping and analysis platforms. A
fuller description of the dataset, including methods, the validation
results, and how to access the different datasets can be seen on the DE
Africa user guide:
https://docs.digitalearthafrica.org/en/latest/data_specs/Cropland_extent_specs.html