Geospatial Analysis of Land Use/Cover Dynamics in Awka Metropolis, Nigeria: A Sub-pixel Approach

Abstract

This study aimed at characterizing the urban Land Use/Cover (LU/C) types and their spatio-temporal changes in Awka Metropolis, Anambra State from a sub-pixel perspective. The study made use of Landsat satellite imageries for three epochs (1986, 2001 and 2016) covering a total of 30 years. The Ridd Model of Vegetation (V), Impervious surfaces (I), Soil (S) and Water (W) was employed by applying the Linear Spectral Mixture Analysis (LSMA) to characterize satellite image fractions for each epoch. Cellular Automata Markov (Ca-Markov) chain and the Land Change Modeller (LCM) were used to predict future LU/C for the year 2031 and the transition of each LU/C categories between 2016 and 2031, respectively. ArcGIS 10.5 and Idrisi Selva software were used for the analyses. The findings of this study indicated that vegetation reduced over the years from 181.79 sq.km in 1986 to 110.89 sq.km in 2016 while impervious surface on the other hand increased from 16.79 sq.km in 1986 to 73.34 sq.km in 2016. Areas classified as soil experienced an increase from 26.15 sq.km to 36.519 sq.km within the same period while (exposed) water fractions increased from 0.961 sq.km in 1986 to 2.748 sq.km in 2016. The prediction analysis performed revealed that by the year 2031, Awka Metropolis will be reduced to about 88.20 sq.km of vegetation; impervious surfaces is expected to increase by an additional 17.780 sq.km in 2031; soil cover also predicted to increase to 42.75 sq.km in 2031. The transition map produced in this study (between 2016 and 2031) did not only locate areas expected to transform from each LU/C category to another or areas where they may persist but also indicated that the transition of vegetation to impervious surface was most pronounced than any other category of LU/C. LU/C changes of this nature have been held as a principal cause of Urban Heat Islands (UHIs), high urban surface temperature and a major proponent of climate change. The study therefore recommends the use of sub-pixel approach in characterizing LU/C fractions especially when the level of objectivity is highly needed and/or in the modelling of non-linear and chaotic environmental phenomena, e.g. Land Surface Temperature (LST), soil moisture, erosion and flood vulnerability, etc.