Introduction
In recent years, the utilization of Earth Observation (EO) related technologies has revolutionized agricultural management by providing near real-time and high-resolution satellite data that aid in mapping of agricultural activities, monitor crop health, soil conditions, and weather patterns. The insights derived from the application of EO technologies in making data-driven decisions have the potential to significantly contribute to the improvements of crop productivity and reduction of farm input costs. EO can play a crucial role in enhancing food security in the country by offering early warnings for droughts, floods, and other environmental threats that affect the agriculture sector
About the Project
The Kenya Space Agency (KSA) is leading an innovative pilot project in Murang’a
County,
partnering with stakeholders across the agricultural sector to develop a workflow
aimed
at characterizing and monitoring land use, especially in agriculture. Murang’a
County
offers an ideal pilot environment, with its diverse climatic and agro-ecological
zones,
ranging from highlands to lowlands, supporting a wide variety of crops. Among the
main
crops cultivated here are maize, coffee, tea, avocado, mango, and bananas, which
provide
substantial economic value. However, the county’s farmers face challenges from
unpredictable weather patterns, soil degradation, and limited access to agricultural
extension services.
Leveraging Earth Observation (EO) technology, KSA aims
to
transform these challenges into opportunities by providing data driven insights.
These
insights
are expected to empower farmers and decision-makers with
tools to optimize crop health, monitor soil conditions, and respond proactively to
adverse weather events. This project holds great promise to boost Murang’a County’s
agricultural output, enabling more efficient management of crops and resources while
ultimately enhancing food security and supporting the livelihoods of local
communities.
Project Products
Land Use land Cover
KSA, with Microsoft AI for Good and Clark University, is using AI to map 2022 land use in Murang’a County. Enhanced by drone imagery, this work provides insights into regional land patterns for better planning.Murang’a LULC
Since November 2023, KSA has partnered with Microsoft AI for Good and Clark University’s Geospatial Analytics Center to develop an AI model that classifies land use in Murang’a County from high-resolution 2022 satellite imagery. Enhanced by drone data from Radiant Earth, PLACE, and Spatial Collective, the model is now in the validation phase. This project delivers precise mapping to track land use changes, supporting informed planning and sustainable development in the region.
Crop Type Mapping
The next phase will develop detailed crop type maps for Murang’a County in partnership with Dedan Kimathi University, JKUAT, Taita Taveta University and CIAT, aiming to create data-driven maps to improve agricultural practices.Crop Type Mapping
From September 2024 to June 2025, KSA will partner with Dedan Kimathi University, JKUAT, Taita University, and CIAT to map crop types across Murang’a County. This phase leverages research expertise to produce accurate, actionable maps that will guide improved agricultural practices over two crop-growing seasons, empowering sustainable farming and resource management.
Crop Monitoring and Yield Estimation
The project’s third phase will use crop maps from the previous phase to monitor crops and estimate yields in Murang’a County. This phase, running from February to June 2025, will leverage initial data gathered during phase two to refine its approach.Crop Monitoring and Yield Estimation
In the third project phase, KSA will monitor crops and estimate yields in Murang’a County using crop maps from phase two. Scheduled from February to June 2025, this phase will benefit from preliminary data collected earlier to enhance crop yield models, supporting informed agricultural planning and productivity improvements.
Project Impact and Expected Outcomes
Increase agricultural efficiency and productivity
Support data-driven policy development for better resource allocation
Reduce farm input costs and environmental impact
Strengthen food security through predictive analytics and early warning systems
Murang’a’s unique blend of climate zones and topographies makes it representative of the broader agro-ecological diversity found in Kenya. By starting here, the project will gather insights that can be adapted and scaled to other regions, providing a foundation for a national approach to agricultural monitoring.
Project Partners
