Abstract
Land cover (LC) change is an integrative indicator of changes in ecosystems due to anthropogenic or natural forcings. There is a significant interest in the investigation of spatio-temporal patterns of LC transitions, and the causes and consequences thereof. While the advent of satellite remote sensing techniques have enhanced our ability to track and measure LC changes across the globe, significant gaps remain in disentangling specific factors that influence, or in certain cases, are influenced by, LC change. This study aims to investigate the relative influence of regional-scale bioclimatology and local-scale anthropogenic factors in driving LC and environmental change in Ghana. This analysis builds upon previous research in the region that has highlighted multiple drivers of LC change in the region, especially via drivers such as deforestation, urbanization, and agricultural expansion. It used regional-scale remotely sensed, demographic, and environmental data for Ghana across 20 years and developed path models on causal factors influencing LC transitions in Ghana. A two-step process is utilized wherein causal linkages from an exploratory factor analysis (EFA) are constrained with literature-based theoretical constructs to implement a regional-scale partial least squares path model (PLSPM). The PLSPM reveals complex interrelationships among drivers of LC change that vary across the geography of Ghana. The model suggests strong effects of local urban expansion on deforestation and vegetation losses in urban and peri-urban areas. Losses of vegetation are in turn related to increases in local heating patterns indicative of urban heat island effects. Direct effects of heat islands are however masked by strong latitudinal gradients in climatological factors. The models confirm that decreases in vegetation cover results in increased land surface albedo that is indirectly related to urban and population expansion. These empirically-estimated causal linkages provide insights into complex spatio-temporal variations in potential drivers of LC change. We expect these models and spatial data products to form the basis for detailed investigations into the mechanistic underpinnings of land cover dynamics across Ghana. These analyses are aimed at building a template for methods that can be utilized to holistically design spatially-disaggregated strategies for sustainable development across Ghana.
Highlights
Patterns of land cover change (LCC) are often integrative indicators of climatic, environmental, and anthropogenic effects across the globe
Results obtained from the exploratory factor analysis (EFA) provided a strong basis for formulating hypotheses on the likely causal factors driving LCC across Ghana
We utilized information from the EFA to formulate the structure of the partial least squares path model (PLSPM) that might be representative of observed patterns in greenness and bioclimatology
Summary
Patterns of land cover change (LCC) are often integrative indicators of climatic, environmental, and anthropogenic effects across the globe. Changes in land cover (LC) have been found to be correlated to measurable indicators such as erosion, population expansion, industrial growth, surface heating, and soil quality (Teuling et al, 2010; Kuenzer et al, 2014; Rahaman et al, 2020). Direct human activity, such as increased agricultural land use, has been a significant component of change throughout history in natural LC dynamics (Malhi et al, 2013; Lewis et al, 2015; AddoFordjour and Ankomah, 2017). Detrimental practices have been a complicated problem to address, in part due to difficulties in identifying definitive long-term consequences of these interferences (Frondoni et al, 2011; Malhi et al, 2013)
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