OEMC project use case: Tools for Digitalisation of Agriculture in Ethiopia

Lack of decision-making tools in developing countries thwarts nationwide policies being made. Ethiopia possesses abundant natural resources and agriculture is the largest economic sector. National (biophysical) KPIs are required to continue developing the country, reduce hunger and have a further positive effect on climate change. Earth observation (EO) is a method of detection and monitoring and suitable for tracking large scale land management. However, limited access and capacity to leverage EO data are a significant barrier. Therefore, this use case will focus on integrating ground data and EO data and capacity-building. We will create cost-effective machine learning models in the domain of land use / land cover, biodiversity, biomass and soil degradation. By the collaboration, we hope to deliver tailored tools that could be taken up in the longer term.  Stakeholder needs:  A system to monitor and digitalize gully erosion in Ethiopia.  The observational data of soil moisture, aboveground biomass, and bare soil fraction to monitor the performance of watersheds within Ethiopia's National Sustainable Land Management flagship Program (SLMP) scheme. Planned implementation: Joint publication with stakeholders in Ethiopia A developed procedure to outline and estimate gully erosion Observational data collection for SLMP watershed in Ethiopia  Implementation steps include:  Form a working group with Ministry of Agriculture in Ethiopia and Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) Develop the procedure to digitalise the gully site by high resolution satellite imagery Combine SLMP watershed location data with observational data Publish two joint papers. One describes the digitalisation of gully erosion and the other combines time-series observational data to evaluate SLMP project performance under disturbances.