Ag Analytics to Support Small-Holder Farmers and Digital Agriculture in Kenya
Kilimo project combines geospatial and agronomic technologies in order to timely assess acreage, production and global input need estimates. Kilimo supports counties, their GIS departments and extension services, to digitize the fields, monitor the crops, assess the crop production and bring advice to farmers on farming practices.
Kilimo drives impact on the design and implementation of agricultural policies with county geospatial statistics, farm evidence to increase farmers’ income and agricultural production resilience to climate change. A proof-of-concept deployed in Kenyan Vihiga County in 2020-2021 with the French Ministry of Economy & Finance financial support has demonstrated Kilimo project capacity to embark more small-holder farmers and extension officers.
Increasing agricultural productivity and building trust in subsidy programs while preserving the environment and optimizing resources are at stake in Kenya as in the agricultural policies of many countries. The challenge is mostly felt in emerging and low-income countries, where half of the population, mostly women, rely on agriculture for a living. Small holder farmers (SHF) provide livelihoods for more than 2 billion people and produce about 80% of the food in sub-Saharan Africa and Asia (AGRA, 2017). Extension advisory services need to be enhanced in order to support their SHF farmer communities.
Maize is a staple food and a vital crop in Kenya. Knowing better maize acreage and production at county and district level is essential for assessing food and nutrition security, ending hunger and optimizing the whole value chain.
In addition, in a context of climate change, the country's challenge is focused on increasing the sustainable and environmental agricultural maize production, supporting the development of agro-ecological practices and applying climate-smart technologies for agriculture.
Solution
The KILIMO solution, generated by a consortium of Kenyan and European companies (LocateIT, Airbus, itk, GE-Data), aims at tackling these issues by synergistically connecting geospatial imagery services, soil and crop modelling as well as digital agriculture management system.
KILIMO outputs support knowledgeable decision making at providing:
- Agricultural geostatistics at district level from satellite-derived crop mapping, staple crop acreage & maize production estimates, as well as global need estimate for fertilizer.
- Farm evidence at field level, with Field Finder machine-learning algorithm and very high-resolution satellite imagery delineating fields automatically, cross usage of crop map & field delineation and satellite-derived Crop Analytics.
- Custom farming advice based on performance and sustainability, with FieldSim extension service management uses crop modelling to organize crop itineraries and lively predict practice impact on yield and soil carbon balance translated into simple SMS farming advice.
KILIMO project aims at supporting the definition, the implementation and the assessment of agricultural policies, as well as digital transition at different levels:
For Kenyan farmers
To facilitate the work on their small farms, through technology transfer and skill exchange, receive customized advices, traceability of input usage and dynamic production previsions.
For extension officers
To support farmer registration and subsidy attribution thanks to field polygons and crop map, crop monitoring at field level and detection of anomalies to better support their farmer community, assessing the crop production and bringing advice to farmers on farming practices.
For Kenyan government
To empower local authorities, with aggregated outcomes at federal level, to build trust by monitoring every step in the implementation of agricultural policies and increase agricultural production resilience to climate change.
Testimony
VIHIGA
“For the first time, farmers will know the surface of their land thanks to satellite imagery. It will be easier to reach farmers and to provide them with in-season recommendations at the right time thanks to satellite crop monitoring and the FieldSim® app. Thanks to the cartography and geolocation, we will be able to find farmer clusters and identify a group leader for each location”
Extension Officer, Vihiga – Kenya
Satellite derived agricultural analytics to detect cultivated areas, field boundaries & monitor crops. API to fuel crop model, county geostatistics, farm evidence.
Climate-smart agronomic expertise for fertilizer attribution, agricultural practice advices down to farmers.
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