Geospatial evaluation of land suitability of agricultural mechanization and irrigation in Agago district.

Abstract

Agricultural productivity in Uganda remains constrained by limited adoption of mechanization and irrigation, particularly in rural districts such as Agago. This study aimed to evaluate the land suitability for agricultural mechanization and irrigation in Agago District using geospatial analysis and multicriteria decision-making techniques. High-resolution spatial data on topography, soil properties, land cover, water availability, and infrastructure were collected from authoritative sources, including the USGS, HWSD, MODIS, and UBOS. The study employed the Analytic Hierarchy Process (AHP) to

assign weights to key factors influencing mechanization and irrigation potential. Using ArcGIS 10.8.2, individual suitability maps for mechanization and irrigation were developed and then integrated to create a combined land suitability model.

The results revealed that 13.31% of the district is highly suitable for both mechanization and irrigation, 76.26% is moderately suitable, 10.26% is marginally suitable, and only 0.17% is unsuitable. Validation of the model through laboratory analysis of soil pH and texture at selected ground-truth locations showed a high level of accuracy, with an R² of 0.92 and an 88% agreement rate between predicted and observed values. These findings underscore the reliability of geospatial modeling in guiding agricultural land-use planning and investment prioritization. The study concludes that Agago District holds significant potential for sustainable agricultural transformation through targeted mechanization and irrigation interventions. The generated suitability maps offer a critical decision-support tool for policymakers, extension officers, and development partners working toward climate-resilient agriculture in Northern Uganda.