Monitoring Deforestation in South Western Ethiopia Using Geospatial Technologies

Abstract

Maize Deforestation is one among the major environmental problems of our planet earth contributing to land degradation and climate change. Ethiopia had been a home of varied flora and fauna species. However, since recent time most endemic animals and indigenous tree species have dwindled although efforts are there to regain the forest resource through mass mobilization. The study used Landsat image along with institute field survey to monitor the spatio-temporal dynamics of deforestation in the south western parts of Ethiopia. A Supervised maximum likelihood classification algorithm was used along with visual interpretation of the satellite image. According to the result obtained, agricultural land, shrub and woodland and grazing lands were increased by 3715, 511 and 229 hectares respectively at the expense of forest in between 1987 and 2015. In contrast, forest land was reduced by 4455 hectares between the same years and the rate of deforestation is found to be 0.75, 1.48 and 1.119% for the three forest monitoring periods (1987-2001, 2001-2015 and 1987-2015) respectively. The major drivers behind these changes are found to be farmland expansion, biomass fuel, grazing land e and land fragmentation. Population growth and lack of awareness about the long-term consequences of deforestations are also underlying causes. The logistic regression model proposed that deforestation is a function of slope, elevation, and distance to roads, forest edge and aspects. The coefficients for the explanatory variables indicated that the probability of deforestation is negatively related to slope, elevation, and distance from roads, forest edge and aspects. The overall results showed that providing alternative economical access, alternative cook stove technology, creating awareness about the long term impacts of deforestation to rural people; require the attention of government institutions and NGOs.