FG Hydrologie
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The Accra Metropolis of Ghana has experienced rapid urban expansion over the past decades. Agricultural and forest-lands have been transformed into urban/built-up areas. This study analysed urban expansion and its relationship with the temperature of Accra from 1986 to 2022. Multi-source datasets such as remote sensing (RS) and other ancillary data were utilised. Land use land cover (LULC) maps were produced employing the random forests classifier. Land surface temperature (LST) and selected d(RS) Indices were extracted. Regression techniques assessed the interplay between LST and remote sensing indices. The LULC maps revealed increasing trends in the urban/built-up areas at the expense of the other LULC types. The analysis from the LST and the RS indices revealed a direct relationship between temperature and urban/built-up areas and an inverse relationship between temperature and vegetation. Thus, spatial urban expansion has modified the urban temperature of Accra. The integrated utilisation of RS and GIS demonstrated to be an efficient approach for analysing and monitoring urban expansion and its relationship with temperature.
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.