Land Transition and Intensity Analysis of Cropland Expansion in Northern Ghana.

Cropland expansion to meet the growing demand for food and fuel is a driving factor in forest degradation. Over the next few decades, increases in the area of agricultural land are expected to be concentrated in sub-Saharan Africa, which still has large tracts of unexploited land suitable for agricultural production. We analyzed land-cover change in northern Ghana between 1984 and 2015 and compared it with background social factors associated with land change. Maps from three points in time were analyzed to identify the impact of cropland expansion on the distribution of natural vegetation. Three-level intensity analysis revealed that the overall rate of change for the 31-year period was less than that of the first time interval (1984-1999); however, the overall impact on natural vegetation was substantial, and grassland in particular was reduced to a very small proportion of the area over the period. Cropland replaced only grassland during the first time interval, but also began to replace open woodland during the second interval (1999-2015). The in-depth assessment revealed that cropland expansion continued at a steady rate, but the impact on natural vegetation was not uniform across vegetation types; grassland was more vulnerable than woodland, and woodland became increasingly targeted with continual expansion of the agricultural frontier as population increased. Further validation of the socio-cultural factors associated with the observed transitions will help to identify the explicit implications and assist in developing strategies to minimize the impacts of land-use change on regional livelihoods.

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.

Land evaluation for maize based on fuzzy set and interpolation.

The objective of this article is to apply fuzzy set and interpolation techniques for land suitability evaluation for maize in Northern Ghana. Land suitability indices were computed at point observations using the Semantic Import (SI) model, whereas spatial interpolation was carried out by block kriging. Interpolated land suitability shows a high correlation (R2 = 0.87) with observed maize yield at the village level. This indicates that land suitability is closely related to maize yield in the study area. Membership functions were further used to assess the degree of limitation of land characteristics to maize. Sixty percent of the data has membership functions ranging from 0.23 for ECEC to 1.00 for drainage. ECEC, organic C, and clay are the major constraints to maize yield. The use of the fuzzy technique is helpful for land suitability evaluation, especially in applications in which subtle differences in soil quality are of a major interest. Furthermore, the use of kriging that exploits spatial variability of data is useful in producing continuous land suitability maps and in estimating uncertainties associated with predicted land suitability indices.