Remote sensing (RS) techniques based on multispectral satellite-acquired data have demonstrated an unequalled potential to detect, quantify, monitor, and map land degradation. However, RS data alone do not provide information on how land degradation affects the socio-political aspects and the economy of the population living in the affected regions. We developed the Continuous Cycle of Land Degradation (CCoLD) to quantify the severity of the land degradation in the Upper East Region (UER) of Ghana and combined it with the RS-based Normalized Difference Vegetation Index (NDVI) using Global Inventory Modeling and Mapping Studies (GIMMS) NDVI, ground data, and food-production data. In addition, we carried out a field study in the UER, a semi-arid transitional region that plays an important food-production role in Ghana, and compared the results with multi-temporal RS imagery. As well as the general ground measurements, the field study included questionnaires asking local residents to assess the impact of land degradation on their quality of life. The RS data show widespread localized degradation; the field study, supported by crop-production data, also suggests overall extensive land degradation. However, field evidence suggests ecological succession where locally adapted horsetail grasses were displaced by environmentally efficient, short-lived, quick-maturing, and dense grasses. A convergence of evidence suggests that land degradation is in the advanced stage and that more focused, community-based efforts would be needed to combat land degradation and restore the ecosystem's integrity.
All Science Journal Classification (ASJC) codes
- Earth-Surface Processes