Land suitability analysis is a prerequisite to achieving optimum utilization of the available land resources for sustainable agricultural production. Comprehensive, reliable and timely information on agricultural resources is very necessary for a country like Kenya, where agriculture is the mainstay of our national economy. Within Kenya, the demand for rice continues to grow as more Kenyans make changes in their eating habits, and as urban population increases but the production is very low. Lack of knowledge on best combination of factors that suit production of rice has contributed to the low production. The aim of this study was to develop a suitability map for rice crop based on physical and climatic factors of production using a Multi-Criteria Evaluation (MCE) & GIS approach. The study was carried out in Kirinyaga, Embu and Mberee counties of Central and Eastern province in Kenya. Biophysical variables of soil (soil pH, soil texture and soil drainage), climate (humidity and temperature) and topography were considered for suitability analysis. All data were stored in Arc GIS 9.3 environment and the factor maps were generated. For Multi-Criteria Evaluation (MCE), Pairwise Comparison Matrix was applied and the suitable areas for rice crop were generated and graduated. The current land use / land cover map of the area was developed from a scanned survey map of the rice growing areas in the region. According to the present land use/cover map, the rice cultivated area was 13,369 ha. Finally, we overlaid the land use/cover map with the suitability map for rice production to identify differences and similarities between the present and potential land use. However, the crop-land evaluation results of the present study identified that in the study area, 75 percent of total rice crop currently being used was under highly suitable areas and 25 percent was under moderately suitable areas. The results showed that the potential area for rice growing is 86,364 ha and out of this only 12% is under rice cultivation. This research provided information at local level that could be used by farmers to select cropping patterns and suitability.
This post was written by Joseph Kihoro Mwangi, John Njoroge, and Hunja Murage
(Jomo Kenyatta University of Agriculture and Technology). Contact Joseph Kihoro Mwangi at firstname.lastname@example.org for more information.