Course overview
Crop monitoring teams must turn satellite observations, field records and weather data into timely decisions on crop condition, water stress, pest risk, production estimates and programme targeting. This is difficult when imagery has cloud cover, field boundaries are incomplete, crop calendars vary, and decision-makers need results they can verify. Poorly designed maps or indices can misdirect extension services, insurance assessments, irrigation allocations and food-security response.
This course develops the GIS and remote-sensing workflow required to monitor crops from field to district and national scale. Participants prepare farm and administrative boundary data, acquire optical and radar imagery, calculate vegetation and moisture indices, analyse crop phenology, classify land cover, assess anomalies and produce area and condition estimates. The course covers Sentinel-1 and Sentinel-2 data, Landsat imagery, Google Earth Engine, QGIS, field validation, accuracy assessment and reporting methods suited to agricultural programmes.
Teaching combines short technical briefings with guided software work, agricultural case material, group analysis and application planning. Participants work with realistic datasets drawn from irrigated schemes, smallholder production areas and seasonal monitoring programmes. They leave with a completed crop-monitoring analysis package containing mapped crop areas, condition indicators, anomaly findings, validation evidence and a reporting product that can be adapted to their own geography and crop system.
The course suits professionals responsible for agricultural statistics, food-security monitoring, extension planning, irrigation management, climate adaptation, crop insurance, donor-funded agriculture programmes and geospatial analysis. It is particularly relevant where field observations are costly, seasonal information is delayed, or monitoring must cover large and difficult-to-access areas.
