ATEC (Advanced Technologies for Efficient Crop management)
Browse by
This collection comprises of data supporting manuscripts generated from the ATEC project (Advanced Technologies for Efficient Crop management), which was a collaboration between the School of GeoSciences and SRUC. ATEC evaluates a range of technologies for providing field-scale information for supporting crop management. The project uses data acquired from ground-based measurements, Unmanned Aerial Vehicles (UAVs) and Earth observation satellites. Through model-data fusion approaches, these datasets are combined with crop growth models to develop a novel decision-support system for diagnosing crop nutrient and yield limitations.
Principal Investigator: Prof. Mat Williams
Co-investigators: Andrew Revill, Anna Florence, Steve Hoad, Andrew Barnes, Bob Rees, Alasdair MacArthur.
Items in this Collection
-
ATEC manuscript 4 - supporting data: "The Effect of Antecedence on Empirical Model Forecasts of Crop Yield from Observations of Canopy Properties"
Identification of yield deficits early in the growing season for cereal crops (e.g., Triticum aestivum) could help to identify more precise agronomic strategies for intervention to manage production. We investigated how ... -
ATEC manuscript 3 - supporting data: "Combining Process Modelling and LAI Observations to Diagnose Winter Wheat Nitrogen Status and Forecast Yield"
Climate, nitrogen (N) and leaf area index (LAI) are key determinants of crop yield. N additions can enhance yield but must be managed efficiently to reduce pollution. Complex process models estimate N status by simulating ... -
ATEC manuscript 2 - supporting data: "Quantifying Uncertainty and Bridging the Scaling Gap in the Retrieval of Leaf Area Index by Coupling Sentinel-2 and UAV Observations"
Leaf area index (LAI) estimates can inform decision-making in crop management. The European Space Agency’s Sentinel-2 satellite, with observations in the red-edge spectral region, can monitor crops globally at sub-field ...
RSS 1.0