EGU2020-5808
https://doi.org/10.5194/egusphere-egu2020-5808
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Identifying Intensively Managed Coffee Forests in Southwest Ethiopia using Satellite Imagery

Byongjun Hwang1, Kitessa Hundera2, Bizuneh Mekuria3, Adrian Wood1, and Andinet Asfaw3,4
Byongjun Hwang et al.
  • 1University of Huddersfield, Biological and Geographical Sciences, United Kingdom of Great Britain and Northern Ireland (b.hwang@hud.ac.uk)
  • 2Jimma University, Jimma, Ethiopia
  • 3Ethio-Wetlands and Natural Resource Association, Ethiopia
  • 4Farm Africa, Ethiopia

The high forests in southwest Ethiopia, some of the last remaining Afromontane forests in the country, are home to significant forest coffee production. While considered as beneficial in maintaining forests, there have been growing concerns about the degradation caused by intensive coffee production in the forests. However, yet no suitable methods have been developed to map the intensively managed coffee forests. In this study, we explore the feasibility of monitoring the extent of the degradation within the intensively managed coffee forests by using satellite imagery (Landsat-8 and Sentinel-2). For this, we conducted in-situ field canopy photo and tree surveys, and the results were analysed with satellite-derived vegetation indices such as NDVI and NBR. This feasibility study informed us that the detection of the intensively managed forest coffee areas (disturbances caused by this practice) using satellite imagery can be possible, as the dry-season forest structure (canopy, undergrowth) and vegetation indices in the intensively managed coffee forests are significantly distinctive from those in natural forests. This study will contribute to the long-term sustainable management of the coffee forest.

How to cite: Hwang, B., Hundera, K., Mekuria, B., Wood, A., and Asfaw, A.: Identifying Intensively Managed Coffee Forests in Southwest Ethiopia using Satellite Imagery, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5808, https://doi.org/10.5194/egusphere-egu2020-5808, 2020

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