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.
