By: Alo A. A.; Nwatu J. U.;
Abstract:
Urban Green Space (UGS) provides economic, ecological and social benefits to the populace across the globe.
However, there is dearth of information on the dynamic of UGS caused by proximate drivers (PD) in Ibadan
metropolis of Oyo State, Nigeria having flooded the direct drivers. Therefore, this study was designed to assess UGS
changes and the PD that contribute to the changes in the last 34 years. Landsat images of 1984 (TM), 2001 (ETM+)
and 2018 (OLI), coordinates of bench mark places of Ibadan metropolis were obtained. Geometric correction and
principal component analysis were carried out on the satellite images. Land cover classification was achieved using
maximum likelihood classifier method. Shapefile of Ibadan metropolis was super imposed on the classified images
for land use/land cover assessment and Kappa statistics was used to carry out accuracy assessment on the image
classification. The change detection analysis was carried out on the classified images using geometric geoalgorithm
of ArcGIS. Urban green space change (dependent variable) and Proximate Distance (distance from; UGS edges,
roads, built-up area and elevation) were extracted from the Landsat images using the distance command in IDRISI
with Cramer's V test of association analysis. Four land use/land cover categories were identified; urban green space,
built-up, water body and bare-soil. The UGS and water body decreased from 126,344 ha (85.36%) and 233.01ha
(0.16%) to 100,481.20 ha (67.88%) and 136.17ha (0.09%) respectively from 1984 to 2018. On the other hand, builtup area and bare-soil increased from 9,250.72 ha (6.25%) and 12,193 ha (8.23%) to 32,227.16 ha (21.77%) and
15,176.20 ha (10.25%) respectively from 1984 to 2018. Distance from built-up (0.59) and UGS edges (0.56) are the
dominant PD of UGS dynamics. About 25,863 ha of green space at rate of 760 ha per annum is given up to built-up
area and bare-soil between 1984 and 2018. Urban green space decreased with increase in built-up area. The dominant
proximate drivers influencing the changes were the distance from the built-up area and urban green space edges.
Keywords: Urban green spaces; change detection; proximate drivers; land use change;
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