GIS Based Analysis of the Extent and Dynamic of Forest Cover Changes Between 1990–2017 Using Geospatial Techniques: In Case of Gog District, Gambella Regional State, Western Ethiopia

  • Obang Owar
  • Sintayehu Legesse
  • Dessalegn Obsi
Conference paper
Part of the Southern Space Studies book series (SOSPST)


This research study examines the causes of forest cover change, the rate of land use land cover change in Gog district, Gambella regional state between 1990 and 2017 using Geospatial techniques. Landsat TM image 1990, ETM+ 2002 and OLI-TIRS 2017 were used to generate land cover map. Field observation, Focused group discussions, Key informants interviews and remotely sensed data were used to analyze the causes and rate of land use land cover change.

An explanatory sequential approach of mixed research design was used in this study where maximum likelihood technique of the supervised classification was used to classify land cover categories using ERDAS Imagine 2014 software. Six land cover classes including bare land, farmland, water, bush land, forest cover and grass land were used for classifications.

Out of the six classes, the results show a dramatic increase of farm land from (4%) in 2002 to (23%) in 2017 with annual expansion rate (24.86%) per annum, where forest cover declined from (23%) in 2002 to (18.11%) in 2017 with annual decreasing rate (−1.41%) per annum. The accuracy assessment report for 2017 map shows an overall accuracy (83%) and Cohen kappa coefficient (82%) of the classification.

This massive declined in forest cover was mainly due to commercial farm land expansion, forest fire, population growth, illegal logging, charcoal extraction, fuel wood collection and poor management of the natural resource in the study area. The wider expansions of large scale commercial agriculture become the leading cause for forest cover change in the study area.

These dramatic change in forest cover has further resulted in soil erosion, loss of soil fertility, migration of animals towards neighborhood countries which in turn leads to low agricultural productivity and low livelihood status of the rural community in Gog district. Thus the government bodies are expected to carry out large scale plantation, create awareness and teach the communities about the benefit of forest resources.


Geospatial techniques Extent, Forest cover Land use Land cover, change, Gog district 



The author acknowledges Gog district and Jimma University (JU) for their support.


  1. Center for International Forestry Research. A new landscape for forestry. Annual report 2015 (CIFOR), Bogor, Indonesia (2016)Google Scholar
  2. Central Statistical Agency: Population census and housing data for Gambella regional state: statistical abstract. FDRE, Addis Ababa, Ethiopia (2007)Google Scholar
  3. Congalton, R., Green, K.: Assessing the accuracy of remotely sensed data: principles and practices, 2nd edn. Taylor and Francis, Boca Raton, FL (2009)Google Scholar
  4. Ethiopian Forest Action Program: The challenge for development: final draft consultant report. Ministry of natural resources development and environmental protection. Addis Ababa, Ethiopia (1994)Google Scholar
  5. Food & Agricultural Organization. Global forest resource assessment. In: FAO Forestry paper 163, Main Report, Rome, Italy (2010)Google Scholar
  6. Food & Agricultural Organization. Global forest resource assessment 2015. How have the world forest changed? Rome, Italy (2015)Google Scholar
  7. Food & Agricultural Organization. State of the world forests 2016. Forest and agriculture: land use challenges and opportunities. Rome, Italy (2016)Google Scholar
  8. Fung, F., Le Drew, L.: The determination of optimal Threshold Levels for change detection using various Accuracy Indices. Photogramm Eng Remote Sens. 54, 1449–1454 (1988)Google Scholar
  9. Gambella Investment Agency. The state of large scale land investment in Gambella regional state, Ethiopia (2017)Google Scholar
  10. Geist, H.J., Lambin, E.F.: Proximate causes and underlying driving forces of tropical deforestation: tropical forests are disappearing. Biosciences. 52, 143–150 (2002)CrossRefGoogle Scholar
  11. Jensen, J.R.: Introduction to digital image processing: a remote sensing perspective. Taylor & Francis, New Jersey (1996)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Obang Owar
    • 1
  • Sintayehu Legesse
    • 2
  • Dessalegn Obsi
    • 2
  1. 1.Department of Geography and Environmental StudiesMizan-Tepi UniversityMizanEthiopia
  2. 2.Department of Natural Resources ManagementJimma UniversityJimmaEthiopia

Personalised recommendations