African Journal of
Environmental Science and Technology

  • Abbreviation: Afr. J. Environ. Sci. Technol.
  • Language: English
  • ISSN: 1996-0786
  • DOI: 10.5897/AJEST
  • Start Year: 2007
  • Published Articles: 1096

Article in Press


Tokuma Urgessa, Tadesse Hunduma and Marsha Gebrehiwot

  •  Received: 27 December 2021
  •  Accepted: 15 March 2022
In Ethiopia, forest cover changes were registered at local level that adds up to the changes observed at the country wise. Like other part of the country the quick spread of deforestation over latest epochs has resulted in the translation of the majority of the Walmara district forest into isolated bits. Geographic information system (GIS) techniques and remote sensing (RS) from satellite platforms offer a way to identify forest cover change. The main objectives of the study were to observe and map the trends and extents of the forest cover changes and to identify the possible proximate causes during the study periods. Quantum GIS, ENVI and SPSS 16.0 were used for the analysis of the spatial and temporal forest cover change. A supervised image classification technique, Maximum likelihood was applied on Landsat 5, 7 and 8 satellite images of 1985, 2000 and 2017 respectively. The result from the satellite image classifications were demonstrated that forest cover of the district was exhibited area decrement consistently. Forest cover has declined to about 20% of its area in 1985, declining from 9238.41 ha, to 4748.13 ha and then to 1497.87 ha.

Keywords: Walmara wereda, Landsat, QGIS, forest loss, , supervised classification.