Estimation, monitoring and interactive web mapping of net primary production for rangelands' carrying capacity in Awash Basin

Synergistic use of earth observation (EO) data and machine learning.


GCRF AgriFood Africa Innovation Awards Round 6





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About the project

UK-registered Partner: Deimos Space UK – Alireza Taravat
Africa-registered Partner: Space Science and Geospatial Institute (SSGI) – Berhan Gessesse Awoke

The project aims to develop a groundbreaking method to estimate and monitor the net primary production of rangelands’ carrying capacity in Awash Basin, Ethiopia. Using Earth Observation (EO) data and ResUNet deep learning model, the project seeks to understand the aerial extent, carrying capacity, and pasture quality of rangelands, which cover a significant portion of Ethiopia’s lowlands.

Traditional livestock practices have yielded low production and productivity, with multiple environmental and economic shocks further stunting growth. This initiative aims to address these challenges by creating an interactive web map to visualise the net primary production of rangelands. The insights gained will not only have national implications but will contribute to livestock development on continental and global scales, demonstrating the versatile applications of EO data and deep learning in the agricultural sector.


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