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GEOSPATIAL ASSESSMENT OF POVERTY LEVEL OF RESIDENTS IN OSOGBO LOCAL GOVERNMENT AREA, OSUN STATE, NIGERIA

AUTHORS: SOLOMON AYODEJI OLATUNJI1 , ADEYEMI ADEWUMI ADEDEJI2 , BOSEDE FELICIA OYENIYI3 , JOSEPH OPEYEMI OLATUNJI4

1Department of Urban and Regional Planning, Federal University Oye-Ekiti,
Nigeria
solomon.olatunji@fuoye.edu.ng
2Department of Urban and Regional Planning Federal University of
Technology,Minna,Nigeria
dejyem986@gmail.com
3Geographic Information Systems Department, Regional Center for Training in
AerospaceSurveys[RECTAS],Ile-Ife
feliciaoyen@gmail.com
4Department of Entreprenuer, Osun State University Okuku Campus, Osun
State,Nigeria.
josepholatunji56@gmail.com

ABSTRACT

This paper assesses the level of poverty of the residents of Osogbo LGA, Osun State, in order to help policymakers and urban planners make better decisions to reduce urban poverty. In an attempt to determine the level of poverty, this research adopted analytical tool of the Geographical Information System [GIS]. A spatial autocorrelation check was performed on the prepared datasets using Moran’s I test; this was necessary in order to determine the method used in the mapping of the indicators. Hence, the indicators with positive correlation were mapped using spatial interpolation in the Geostatistical Analytical Tools of ArcGIS 10.2. The analysis revealed that in the zone where poverty levels are high, the expenditure/income, nutrition, and health indicators had a mean percentage of 30%, 31%, and 38%, which is also very low, while education and enrolment are above average, so more focus should be on addressing the indicators with low percentages for poverty alleviation in the areas with low poverty levels. The results of the spatial variation in the level of poverty in different locations in the study area will help policymakers in the selection of infrastructure and amenities. It will help the security agents pin down specific areas in the community that will have a high level of security, especially, areas with a high level of poverty.

Keywords: Assessment, Geospatial, Level, Poverty, Residents