Modelling the suitability of agroecological zones for sorghum cultivation based on GIS multi-criteria analysis in Western Kenya

This study assessed the agroecological suitability of sorghum cultivation using Geographic Information Systems (GIS) integrated with Multi-Criteria Decision Analysis (MCDA), specifically a weighted-overlay approach. Key biophysical factors, such as rainfall, temperature, soil pH, soil texture, slope, elevation, and land use/land cover, were standardised, weighted, and overlaid to generate a composite suitability map. The results showed that 16.9% (221,194.96 ha) of the study area was highly suitable for sorghum cultivation, 74.6% (974,249.53 ha) moderately suitable, 8.4% (109,194.75 ha) marginally suitable, and only 0.1% (668.33 ha) unsuitable. Suitable zones were mainly concentrated in Busia and western Siaya, while moderately suitable areas dominated Kakamega, Bungoma, Vihiga, and Trans Nzoia. Marginal suitability was observed in the high-altitude slopes of Mount Elgon and northern Trans Nzoia, while unsuitable areas were confined to waterlogged lowlands near Lake Victoria. The study concludes that Western Kenya has substantial potential for sorghum expansion, particularly in mid-altitude agroecological zones. It is recommended that sorghum promotion be prioritised in suitable and moderately suitable areas, complemented by soil fertility restoration, improved drought- and cold-tolerant varieties, and integration of GIS-based planning into county agricultural policies.

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Publication Details

Journal
International Journal of Image and Data Fusion
Published
2026-10-30
DOI
https://doi.org/10.1080/19479832.2026.2752253
Primary Topic
Soil and Land Suitability Analysis
Type
article
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article

Modelling the suitability of agroecological zones for sorghum cultivation based on GIS multi-criteria analysis in Western Kenya

Oluwatoyin S. Ayanlade, Felix Ndukson Buba, PhilIip Olalekan Ayoola, Owiti Pauline Atieno
International Journal of Image and Data Fusion
Soil and Land Suitability Analysis
article

Modelling the suitability of agroecological zones for sorghum cultivation based on GIS multi-criteria analysis in Western Kenya

Oluwatoyin S. Ayanlade, Felix Ndukson Buba, PhilIip Olalekan Ayoola, Owiti Pauline Atieno
article en

Abstract

This study assessed the agroecological suitability of sorghum cultivation using Geographic Information Systems (GIS) integrated with Multi-Criteria Decision Analysis (MCDA), specifically a weighted-overlay approach. Key biophysical factors, such as rainfall, temperature, soil pH, soil texture, slope, elevation, and land use/land cover, were standardised, weighted, and overlaid to generate a composite suitability map. The results showed that 16.9% (221,194.96 ha) of the study area was highly suitable for sorghum cultivation, 74.6% (974,249.53 ha) moderately suitable, 8.4% (109,194.75 ha) marginally suitable, and only 0.1% (668.33 ha) unsuitable. Suitable zones were mainly concentrated in Busia and western Siaya, while moderately suitable areas dominated Kakamega, Bungoma, Vihiga, and Trans Nzoia. Marginal suitability was observed in the high-altitude slopes of Mount Elgon and northern Trans Nzoia, while unsuitable areas were confined to waterlogged lowlands near Lake Victoria. The study concludes that Western Kenya has substantial potential for sorghum expansion, particularly in mid-altitude agroecological zones. It is recommended that sorghum promotion be prioritised in suitable and moderately suitable areas, complemented by soil fertility restoration, improved drought- and cold-tolerant varieties, and integration of GIS-based planning into county agricultural policies.

International Journal of Image and Data FusionVol. 17(1)
African Regional Centre for Space Science and Technology Education in English (NG), Obafemi Awolowo University (NG)
Openalex Percentile: Top 9%
Soil and Land Suitability Analysis
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Modelling the suitability of agroecological zones for sorghum cultivation based on GIS multi-criteria analysis in Western Kenya — Oluwatoyin S. Ayanlade, Felix Ndukson Buba, et al. · International Journal of Image and Data Fusion (2026) | TGRS Research Map | TGRS