EGU24-11472, updated on 09 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Geospatial suitability mapping for targeted vegetable production in fragile African regions

Moctar Dembélé1, Mansoor Leh2, Darshana Wickramasinghe2, Naga Velpuri2, Karamoko Sanogo1, Desalegne Tegegne3, Mariangel Garcia Andarcia2, and Petra Schmitter2
Moctar Dembélé et al.
  • 1International Water Management Institute (IWMI), Accra, Ghana (
  • 2International Water Management Institute (IWMI), Colombo, Sri Lanka
  • 3International Water Management Institute (IWMI), Addis Ababa, Ethiopia

Enabling the resilience of local food systems is crucial to ensure a steady supply of nutritious food to people living in fragile and conflict-affected locations. While the majority of interventions often focus on staple crops, there is an increasing tendency by humanitarian organizations to include vegetable production solutions in their programs. However, information on land suitability for vegetable production is usually lacking or available at a coarse spatial resolution, thereby limiting targeted interventions for smallholder farmers.

This study proposes a comprehensive geospatial data-driven framework for mapping suitable areas for vegetable production in Africa using a machine learning algorithm (ML) implemented in Google Earth Engine (GEE) and a Multi-Criteria Decision Analysis (MCA) approach. Mali (West Africa) and Ethiopia (East Africa) are selected as case studies given the current fragility of both countries, and support provided by the USAID's Bureau for Humanitarian Assistance (BHA). Field data of vegetable production locations was collected to train and validate the ML and MCA models. Several publicly available geospatial datasets, including FAO’s WaPOR database, were reviewed to select the predictor variables, which include information on climate, soil, topography, surface water, groundwater, socioeconomics and disaster risks. A suitability map was produced for all vegetables, and separate suitability maps were generated for the top five most cultivated vegetables in Mali and Ethiopia.

Comparison of the ML approach to the MCA approach revealed a lower performance of the former due to the limited availability of field data, thereby highlighting the benefit of expert knowledge in addition to the data-driven approach. The results show that the most suitable areas are found in the region of Segou in Mali (up to 88%), while the region of Oromia has the most suitable areas in Ethiopia (up to 85%). The resulting maps of land suitability for vegetable production serve to develop an irrigation investment targeting tool, which can be used to assist humanitarian organizations in implementing suitable irrigation solutions for vegetables.

How to cite: Dembélé, M., Leh, M., Wickramasinghe, D., Velpuri, N., Sanogo, K., Tegegne, D., Andarcia, M. G., and Schmitter, P.: Geospatial suitability mapping for targeted vegetable production in fragile African regions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11472,, 2024.