Integrating socio-economic and environmental data in relation to environmental degradation: a case study of the East African Rift Valley, Ethiopia
2005
Enrico Feli, | Laura Gallizia Vuerich, | Paola Ganis | Zerihun Woldu
The response of the environment to human induced degradation in a pilot study area of the Rift Valley of Eastern Africa was analyzed by integrating information of various sources using GIS. The information integrated consisted of socioeconomic, geological, land cover, land use, potential and actual rate of soil erosion and remote sensing and related physical and biological variables. The composite of data matrices consisting of 35 Kebeles, the smallest administrative units in the area and various descriptors were polled into one with variables in rows and Kebeles in columns. The Kebeles were classified into homogeneous clusters using agglomerative hierarchical classification methods. The classification produced groups of contagious Kebeles along similarities in geology. Canonical correlation analyses were also performed to test the relationship among the various groups of variables. The sub-matrices of groups of variables were significantly correlated (P = 0.0). The study indicated that geology has a strong bearing on the results of the classification suggesting that human impact has not yet passed beyond the influences of natural forces and that resources are not fully depleted to the extent that people may be forced to occupy marginal and less productive areas. The results of the study imply that the environment can be rehabilitated by reducing human pressure as an entry point of intervention and maintaining the mosaic of patches of vegetation interconnected by corridors among agricultural fields through participation approach. This can be realized mainly by facilitating easy access to other renewable energy sources and off farm employments.
اظهر المزيد [+] اقل [-]الكلمات المفتاحية الخاصة بالمكنز الزراعي (أجروفوك)
المعلومات البيبليوغرافية
تم تزويد هذا السجل من قبل Ethiopian Institute of Agricultural Research