LAND USE LAND COVER CHANGE DETECTION AND DEFORESTATION MODELING: IN DELOMENA DISTRICT OF BALE ZONE, ETHIOPIA

Previous studies failed to provide information about causes and impacts of deforestation including deforestation prediction. This study aimed at investigating spatiotemporal dynamics and to predict deforestation. Three periodsLandsat images were download and preprocessed using ENVI 4.3. Supervised classification technique was employed for image classification. Land Change Modular was used to predict deforestation based on transition between 2000 and 2010 along three driving variables. Qualitative data were collected using PRA and Key informant interviews. Those data were analyzed and narrated along different thematic topics. Six land-use land-cover classes were classified for three periods. The forest areas were 91,339, 73,274 and 70,481 hectors in year 2000, 2010 and 2015, respectively. Forest area was reduced by 20% between 2000 and 2010 at annual rate of 2%. Between 2010 and 2015 a forest area was lost by 4% with annual rate of 1%. Deforestation rate was greater than global rates and was lower than rates of south eastern African countries. Farmland expansion was a major cause of deforestation contributed to the annual forest loss by 4.9% and 36% over different periods. In 2030 about 33,243 hectors of a forest area would be expected to disappear that implied emission of about seventeen million ton of carbon dioxide. Fuelwoods shortage and loss of biodiversity were perceived as impacts of deforestation. Farmland and settlement were found increasing at expense of vegetation. Forest plantation, supply of fuel efficient technology and community mobilization were recommended that would be emphasized by the forestry sector based at the district office. 4