A spatial assessment of land suitability for maize farming in Kenya

Many developing nations are faced with severe food insecurity partly because of their overdependence on rainfed agriculture. In Kenya, climate system variations that impact staple food crops like maize ultimately threaten the nation's food security. This study applied analytical hierarchy process, a multi-criteria decision-making technique, and remote sensing, performed within a Geographic Information Systems framework, in developing a land suitability model for maize farming in Kenya under the changing climatic conditions. Levels of suitability were delineated using soil, climate and topographic variables. Local farmers' knowledge was also incorporated to propose context-specific climate change adaptation practices in agriculture. The study revealed that majority (55.6%) of the land is marginally suitable. Significant changes in weather and climate were also revealed, and these generally translated to lower maize crop yields. Finally, diversification, proper timing, soil fertility retention and restoration and better-quality seeds were found to be the most practical adaptation measures.

Automated summary

This study utilized analytical hierarchy process and remote sensing to develop a land suitability model for maize farming in Kenya, addressing the impact of climate change on crop yields. Proposed climate change adaptation practices in agriculture were based on local farmers' knowledge, with diversification, timing, fertility retention, and seeds quality identified as practical measures.