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Accra and Kumasi are the two major cities in Ghana. Spatial urban expansion has been experienced in transforming different non-urban Land Use Land Cover (LULC) types into urban/built-up areas with a potential direct relationship to temperature rise in the cities. Thus, this dissertation aims to establish the relationship between urban spatial expansion and temperature in Accra and Kumasi metropolis. Multi-source datasets such as remote sensing images, different GIS vector layers, reference maps and historical temperature datasets were used for this retrospective study. This research was grouped under three components: environmental science, environmental technology, as well as environmental management and planning. From the environmental science component, LULC maps were produced for different years to assess the trend of temporal change in the various LULC classes in the two metropolises. Remote sensing indices and land surface temperature were retrieved from the remote sensing images to determine their correlations. Temperature time series was analysed by calculating temperature indices and determining temporal trends to reveal changes in air temperature to detect urban warming and its impacts. From the environmental technology, the novel random forest algorithm was utilised to classify the satellite images of both cities since previous works have utilised other traditional classifiers. The satellite imageries were used for point-based estimation of temperature to determine Urban Heat Islands (UHIs) hotspots. For environmental management and planning, spatial urban expansion techniques were utilised to ascertain trends in urban/built-up areas, especially in both cities' sub-metropolitan zones. For prescient purposes, future LULC modelling was implemented to provide insights into the proportions of the various LULC changes in 2025. The analysis identified two salient findings: increased urban/built-up areas at the expense of agricultural and forestlands throughout the study period and the positive correlation between spatial urban expansion and temperature. This indicated warming up of urban temperature in both cities. The major findings in this dissertation provided evidence of how integrated datasets and research techniques can be utilised for LULC changes to determine the relationship between spatial urban expansion and temperature at local scales. Institutions such as metropolitan assemblies and policymakers may adopt the concepts demonstrated in this work to rapidly assess urban environments and investigate the relationship between spatial urban expansion and temperature.
Central Africa is a band of land stretching from the Atlantic Ocean to the Horn of Africa between 18º N 0.75º S and 18º W 44º E. The climate of this region shows a transition zone from the Sahara Desert in the north to the wet tropical Guinean coast and equatorial continental interior in its south. In such transition zones, drought is a common occurrence; of great concern is the progressive drying of the region from the 1970s and into the 1980s. This thesis aims to investigate whether climate change has occurred in Central Africa in the 2nd half of the 20th century. The reanalysis data from the National Centres for Environmental Prediction (NCEP) was used to analyse trends of temperature and precipitation over Central Africa with the linear regression model and patterns of precipitation using principal component analysis. The results of the trend analyses revealed an average increase in temperature of 0.15K/ decade and an average decrease in precipitation of -91 mm/decade for the period 1948-2004 over the whole study area. A regional trend analysis of box averaged data (2.5° in latitude and longitude) revealed an increased precipitation over the Northern part,” the Sahel”, and a marked decrease in precipitation and an increase in temperature over the Eastern parts of the study areas especially in countries such as Somalia, Sudan and Ethiopia. To quantify the changes in temperature and precipitation for different climatic periods (1951-1980, 1961-1990 and 1971-2000), 30-year trend analyses were also performed. Results revealed a relatively stable temperature trend and fluctuations in the precipitation trend over the three 30 year climate periods. Principal component analysis produces a decomposition of the data field into spatial patterns (eigenvectors) and a temporal time series describing the temporal importance of these patterns. For precipitation over Central Africa, three patterns stand out for 60.39% of the total variance in the precipitation over Central Africa. The individual principal components explain 37.6%, 12.1%, and 10.7% respectively of the total variance. The first principal component captures progressive drying in Central Africa, the second principal component captures the different seasons within Central Africa and the third principal component captures the movement of the Intertropical Convergence Zone over Central Africa. Apart from explaining the current precipitation patterns over Central Africa, the use of principal component analysis in this study has demonstrated that a limited number of spatial patterns are basis for African weather, coordinate system for present day climate with maximum variance contribution along the first axis, maximum of the remaining variance along the second axis with subsequent axes explaining less variance can be used to explain precipitation variability within Central Africa. The same method can be used to explain temporal differences between climate change scenarios and present day climate.