Monitoring in season crop conditions is critical when assessing the food security situation and prompting action to mitigate adverse outcomes in largely rain-fed agricultural systems. The Group of Earth Observation for Global Agricultural Monitoring (GEOGLAM) has been supporting global assessments for partners in the Agricultural market information system (AMIS) and in countries that are at risk of food insecurity with the Crop Monitor for AMIS and Crop Monitor for Early Warning respectively. Africa, and specifically Kenya is dependent on rain-fed agricultural production and with climate variability and change, timely, relevant and accurate information on crop conditions is necessary to ensure appropriate and sometimes lifesaving responses. By implementation of national crop monitors countries can synthesize and customize information to suit their reporting metrics and provide detailed sub-regional assessments in a standardized format that can inform global and regional assessments. Successful implementation and publication of The Kenya Crop Monitor Bulletin by the Kenyan Ministry of Agriculture and Irrigation is already influencing agricultural decision making. The bulletin is being used to inform internal decision making in the ministry; and through dissemination on the ministry’s website, as an important source of information for food security agencies. The report which combines earth observation data and field reports from county officers, is improving the way food security decisions are being made. Specifically, monitoring the spread of diseases and pests such as the Fall Army Worm, assessing the implications of extreme events such as floods and droughts on production, providing expected trends based on the prevailing conditions and the expected yield outlook at the end of the season. Through the bulletin, the government has also been able to assess the impact of subsidies on production and as an early warning report to prompt for mitigation and other responses.

The Kenyan ASALs (Arid and Semi-Arid Lands) through livestock production, contribute to over 12% of the 40% Agricultural GDP with further contribution through the tourism sector. They cover over 70% of the country and are home to both wildlife and pastoral communities. With dependence on rain-fed pastures, better management of the ASALs require near real time information on available resources. While information on vegetation conditions is important, other critical resources such as location of water, extent of unpalatable invasive species and other ancillary information is required for a comprehensive understanding of the condition of the ASALs. The Rangelands Decision Support tool was developed to address lack timely information for decision making in the ASALs which influences management of available pastures in dry and wet seasons, development of proper grazing plans, livestock movement, conflicts and implementation of conservation measures meant to rehabilitate degraded lands, management of scarce water resources and mitigation of the spread of invasive species. The tool automates data processing from acquisition to development of final products that consist of dekadal NDVI and monthly products (NDVI Z score, absolute anomalies and VCI (Vegetation Condition Index)). Users are able to select suitable products for specific assessment and produce maps at their monitoring units in PDF format. This research present a fully operational processing chain for the data incorporated in the tool and case studies demonstrating application of the different indicators for monitoring at different monitoring units.