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The need to model the landuse pattern for urban development and livability is salient and crucial
considering the rate at which cities are fast growing today. This research work adopted Akure city
as a case study for such modelling using the remote sensing data obtained from Ikonos and
Quickbird satellite images. The images were corrected for atmospheric, geometric and
radiometric distortions, and then subjected to segmentation algorithm of object oriented image
analysis (OBIA) using the eCognition developer 64- 9.01 software. The segmentation result was
exported to ArcGIS 10.3 software environment where each segment was assigned landuse types,
using visual interpretation techniques. Results shows graphic and empirical models of landuse
pattern of the study area generated from the eight landuse classes extracted for each of the years
under study. An accuracy assessment performed on the graphic models were 93.07% and
87.73% respectively to affirm that the graphic models were good for analysis. Findings shows
that the study area had experienced expansion and development as a result of transformation
within and between the land use classes. A total 0.43% areal extent increase within the study
period was observed. Open landuse, Residential landuse and Organised Open landuse classes
with 35.80%, 44.38% and 14.5% respective increase were observed to be the dominant landuse
transformations in the study period while other land use classes were not too significantly
different.The research recommended the adoption of land use pattern modelling and models to
monitor the fast developments to ensure achievable and sustainable urban development and
livability.