Remote Sensing GIS Based Spatio-temporal temporal Land Use/ Cover Study of Western Ethiopian Highlands –A Case of Jima Arjo District

Abstract

This paper was aimed at studying the  spatio-temporal dynamics of land use/cover over western Ethiopian highlands in the period 1973 to 2006 years (for 33 years) and its future trend. In order to analyze the status of dynamics, the whole study period was  categorized in to three periods; 1973-1986, 1986- 2001 and  2001-2006. Four different time landsat satellite images (1973, 1986, 2001 and 2006) were obtained and classified into the existing seven major land use/cover types (farmland, dense forestland, degraded forestland, open woodland, grassland, wetland and bare land) using remote  sensing-GIS technology. From post-classification   change detection among the image data, Jima Arjo district experienced various levels of land use/cover dynamics. Much of the area has been converted in to farmland ( 170.54 sq. km) with an average expansion of 5.168 sq.km per year. Maximum rate of farmland expansion was recorded during the 1986 to 2001 years period were 151.715 sq. km of the area became farmland. Vegetations showed loss and gain changes.  Forested areas were diminished greatly due to their conversion to other forms of land use/cover across the whole period. Much of the original dense forests (171.16 sq. km of the area) were lost with 5.186 sq.km average annual loss. Extreme forest loss s was recorded during the 1973 to 1986 years period were 112.6 sq. km has been lost. Wetlands were also showed reduction in extent. Of the original 84.52 sq.km wetland, only 0.84 sq.km has been identified at the final study period. Analysis of the land use cover distribution across various slope categories also showed that steep slopes were made farmlands. On the latest image, 7.3814 sq. km area of slope with more than 25 0 and 30.0892 sq. km area with slope range of 12 0 to 25 0 were converted in to farmlands. Vulnerability to change has been modeled and predicted based on the latest land use/cover data. Four levels of vulnerability to change: extremely vulnerable, highly vulnerable, moderately and low vulnerable to change were i identified. Vegetations, particularly degraded forest shared 65.2% of extremely high vulnerability level to change. Almost all the remaining dense forestland became extremely and highly vulnerable to change/transformation.