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Impact of sustainable land management on vegetation cover using remote sensing

In Magera micro Watershed, Omo Gibe Basin, Ethiopia

19 August 2021


Image showing the three types of land use land cover classes classified in the Magera watershed, including bare land, sparse vegetation, and dense vegetation.
Image showing the three types of land use land cover classes classified in the Magera watershed, including bare land, sparse vegetation, and dense vegetation.

Authors: Aklilu Assefa, Alemseged Tamiru Haile, C T Dhanya, David W Walker, John Gowing, Geoff Parkin

The hydrological impact of many expensive investments on watershed interventions remains unquantified due to a lack of time series data. In this study, remote sensing imagery is utilised to quantify and detect vegetation cover change in the Magera micro-watershed, Ethiopia, where sustainable land management interventions have been implemented.

This study evaluated the gradual changes observed in vegetation cover from 2010 to 2019 (before, during, and after watershed interventions were implemented), and shows that the sustainable land management has an overall positive impact on the study area. These research findings support the applicability and usefulness of time series NDVI values derived from remote sensing images for monitoring the impacts of watershed intervention investments, particularly in data scarce regions.


(Image: "Fig. 3. The three land use land cover classes classified based on thresholds in Magera watershed", in ScienceDirect, under CC BY-NC-ND 4.0)

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