ASSESSMENT OF THE EFFECTS OF KIDNAPPING INCIDENCE ON LAND USE AND LAND COVER ALONG KADUNA-ABUJA EXPRESSWAY
Keywords:
Image, Kidnapping, Land Cover, Satellite, Vegetation Cover.Abstract
This research examines the effects of kidnapping on land use and land cover (LULC) along the Kaduna-Abuja
expressway, utilizing data from multiple sources. The study employs satellite imagery, including Landsat-7
(ETM) from 2012, Landsat-8 (OLI) from 2017 and 2022, as well as a 2015 Digital Elevation Model (DEM).
Additionally, data on reported kidnapping incidences obtained from the Kaduna State Police Command were
integrated into the analyses using ArcGIS software. The Post-Classification Comparison Method (PCM) was
employed to construct a change matrix, enabling the exploration of temporal variations and dynamics in
LULC within the study area. The findings reveal significant trends in land cover changes over the decade. In
2012, the landscape was predominantly characterized by agricultural lands and vegetation cover, which
together accounted for over 72% of the total land cover. This distribution is attributed to the widespread
abandonment of farmsteads along the expressway due to the threat of kidnapping. By 2017, the dominance of
bare ground, agricultural lands, and vegetation cover persisted, representing over 87% of the observed
changes. A noteworthy decline in built-up areas, approximately 14.3%, during this period led to a slowdown in
urban expansion. In 2023, vegetation cover and bare land remained the dominant land cover types. However,
there was a significant decline in both built-up areas and agricultural parcels, leading to a 6.4% reduction
from 2012 to 2022. This reduction is linked to the increasing prevalence of kidnapping, which has further
influenced land cover dynamics by increasing bare ground and vegetation coverage. The study underscores the
necessity for systematic, biannual, comprehensive, and continuously updated assessments of LULC changes in
the study area as a crucial means for establishing a foundation for informed decision-making and supporting
sustainable development initiatives in the area
