Land-cover change trajectories in northern Ghana.
Land-cover change trajectories are an emergent property of complex human-environment systems such as the land-use system. An understanding of the factors responsible for land change trajectories is fundamental for land-use planning and the development of land-related policies. The aims of this study were to characterize and identify the spatial determinants of agricultural land-cover change trajectories in northern Ghana. Land-cover change trajectories were defined using land-cover maps prepared from Landsat Thematic Mapper dataset acquired in 1984, 1992, and 1999. Binary logistic regression was used to model the probability of observing the trajectories as a function of spatially explicit biophysical and socioeconomic independent variables. Population densities generally increased along the continuum of land-use intensity, whereas distance from market and roads generally decreased along this continuum. Apparently, roads and market serve as incentives for settlement and agricultural land use. An increase in population density is an important spatial determinant only for trajectories where the dominant change process is agricultural extensification. A major response to population growth is an increase in cultivation frequency around the main market. Agricultural intensification is highly sensitive to accessibility by roads. The increase in land-use intensity is also associated with low soil quality. These results suggest the need for policies to restore soil fertility for agricultural sustainability. The models also provide a means for identifying functional relationships for in-depth analyses of land-use change in Ghana.
Braimoh
Ademola K
AK
Center for Development ResearchUniversity of Bonn, Walter Flex Strasse 3, 53113, Bonn, Germany. braimoh@ias.unu.edu
Vlek
Paul L G
PL
D000383:Agriculture; D003247:Conservation of Natural Resources; D004777:Environment; D005544:Forecasting; D005869:Ghana; D006801:Humans; D008962:Models, Theoretical; D011156:Population Density; D012044:Regression Analysis