Journal of
Horticulture and Forestry

  • Abbreviation: J. Hortic. For.
  • Language: English
  • ISSN: 2006-9782
  • DOI: 10.5897/JHF
  • Start Year: 2009
  • Published Articles: 285

Article in Press

Assessment of Forest Cover Changes in and Around Jorgo Wato Forest, West Wollega, Oromia, Western Ethiopia

Fikadu Kitaba Tola, Gudina Legese Feyisa, Debela Hunde Feyssa

  •  Received: 18 February 2019
  •  Accepted: 21 November 2019
Detecting and identifying the changes in land cover provides the updated information about forest cover changes. Identifying forest cover change is also necessary information for planning and management of sustainable use of natural resources. This study was conducted to detect the dynamics of forest cover change in and around Jorgo Wato forest, West Wollega zone of Oromia National Regional State. In order to assess forest cover changes, the whole study period was categorized into three periods; 1986-1995, 1995-2006 and 2006-2016.Satellite images of Landsat TM, ETM+and OLI/TIRS were used in this study. Support Vector Machine of supervised classification and post classification was used for image classification, and results the overall accuracy of up to 99.65%,and both Maximum Producer’s and User’s accuracies were100% while Kappa statistic ranged between 98.59% and 99.18%. The result of change analysis revealed that,dense forestsclass were experienced positive changefrom 20.3% in 1986 to 44.33% in 2016 whereas sparse forests and shrubs have declinedfrom 37.02% in 1986 to 24.27% in 2016, and farmlands and others from 42.59% in 1986 to 31.26% in 2016 variation through 30 years. An important implication of the observed changes is due to expansion of coffee plantations and plantations of different tree species by the community during Dergue regime (1974-1991) and by Oromia Forest and Wildlife Enterprise till now. Not only focusing on plantation forests rather focusing on more diverse species is better than focusing too few/single species is the main motivation for protection and sustainable forest management.

Keywords: Accuracy, assessment, change detection, satellite image