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The effectiveness of the mapping and assessment of Quality of Life (QoL) in the identification of problemareas and in monitoring development policies makes it a suitable method in poverty studies. In an attemptto enhance QoL as a strategy for poverty alleviation decision-making, this research has adopted theanalytical tool of Geographical Information System (GIS). Twelve indicators were used to assess the QoLof Egor Local Government Area (LGA), Edo State, Nigeria. These indicators were grouped into threedifferent domains of life (social, economic and physical). Spatial autocorrelation check was performed onthe indicators to determine the spatial prediction method that was used to map each indicator. Of all theseindicators, only two were spatially auto-correlated. The two indicators were mapped using the InverseDistance Weighting (IDW). The other indicators were mapped using the voronoi polygons. The twelvemodels were used to model and assess QoL with the utilization of Multi-Criteria Decision Analysis. Theweights used for the combination of the various mapped indicators were given by the respondents. TheQoL model was cross-validated using leave-one-out (LOO) cross-validation method. The result showedthat the QoL of 61.53% of the geographic space of Egor LGA was below average, 17.94% was extremelypoor, and 14.55% was average, while the classes above average and excellent were not on the QoLmodel. In addition, the research identified priority development areas and concluded that the QoL of thepeople of Egor LGA was poor and required urgent conscious intervention by all development partnersincluding the government.

This research demonstrated the use of satellite imagery in detecting changes in land use/ land cover on the fringes of urban areas. Satellite data of the same geographical area, recorded over a decade, were used to identify changes in the pattern of land use/land cover. The study used multi date satellite imageries namely, Landsat MSS 1978 and SPOT5 2007. The images were separately classified and then compared using ILWIS 3.3 and Erdas Imagine 9.3 Versions. The land use/land cover statistics results obtained from the two classifications process showed that built-up areas, sand, water bodies, and open/barren land were found to have been increasing at alarming rate while agricultural land and scrubs were encroached upon by other land use/land cover types. The study showed that land use/land cover change was better captured and monitored through the use of satellite imagery that served as a means of efficiently updating digital databases as shown in the research.Keywords: Remote sensing, GIS, Urban-rural interaction, Planning, Land use, Satellite imagery, Change detection