On farm spatial and temporal data sets – for management and monitoring on arable farms

On farm spatial and temporal data sets – for management and monitoring on arable farms FB11 Farmers, agronomists, and ag-tech professionals seeking to better understand and apply spatial and temporal data in precision agriculture An intermediate course best suited to those who are able to demonstrate some practical experience A half day online course TBC David Clarke, Soils and Farming Systems Specialist and Joseph Martlew, Research Agronomist, Niab

Classroom module 1 (half day) –

•    Yield maps; interpreting spatial variability in productivity 
•    NIR protein and N sensors; assessing grain quality and nitrogen dynamics 
•    Fuel use/work rate maps: what can these data sets tell us about our soils and systems  
•    Satellite data - NDVI, biomass, crop health monitoring 
•    Soil monitoring spatially  
     o    Gridded soil - detailed point-based data 
     o    Management zone soil - zone-based soil variability 
     o    Soil ECa - moisture and texture insights 
     o    Gamma ray spectrometry and emerging technologies 
     o    Lidar - elevation, slope, and water flow modeling 
•    Legacy/third party data sets - integrating historical or external data for added context 

At the end of this course, you will be able to:

•    Identify the types of spatial and temporal data relevant to agriculture 
•    Describe how these datasets can support informed on-farm decision-making 
•    Source and evaluate relevant spatial datasets for agricultural use 
•    Explain how spatial data analysis can inform and improve farm management practices