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The uptake of conservation agriculture and farm mechanization in Southern Africa has been slow and low. As a result, most smallholder farmers continue to grow crops under degraded soils using conventional tools and human powered farm operations. This leads to low productivity. Therefore, spatially visualizing areas where conservation agriculture and farm mechanization can be targeted can be crucial to guide targeting and scaling. In this study, a geographical information systems-based multicriteria analysis using the analytical hierarchical process was used to map the suitability of conservation agriculture and farm mechanization in Malawi, Zambia, and Zimbabwe. This included biophysical (soil, rainfall, temperature, slope, elevation, land use and biomass) and socioeconomic (population density, farming system and livestock ownership) as recommended domains. The Super Decision software 3.2.0 was used to generate the final weights through pairwise comparison. ArcGIS Pro 2.6 through fuzzy functions was used to standardise and generate the maps. The results show that over 95% of the land area in Zimbabwe, 73% in Zambia, and 67% in Malawi are suitable for conservation agriculture and farm mechanization. Malawi, however, has a bigger proportion of land (1%) among the three countries with low suitability. There are regional differences with Lilongwe and Balaka in Malawi; Southern, Central, Eastern and Western provinces in Zambia; and Matebeleland South and North, Mashonaland West, Midlands and Masvingo provinces in Zimbabwe being the most suitable for conservation agriculture and farm mechanization. After validation, the suitability map based on varying weights showed higher levels of reliability, resulting in context-specific suitability maps and that the mapping process was robust. Thus, the suitability maps generated from this study can be used for targeting conservation agriculture and farm mechanization by stakeholders and decisionmakers in the three countries.
