Davide Cammerano

Spatial integration between remote sensing and crop simulation modelling for wheat nitrogen management

The spatial integration of crop simulation modelling and remote sensed imagery has proven to be a useful tool in optimising nitrogen (N) fertilisation rate on wheat. While remote sensed data has been able to provide a snapshot of the crop status at a particular time, it has not been able to explain the causes of crop spatial variability.

Davide’s research will use crop simulation models to consider the effects of weather, soil and management practices on crop growth to gain a better understanding of yield variability and N concentrations in wheat. Davide believes that different N application rates can help farmer’s increase their net income to 114.1 Euro/ha for zone A and 164.4 Euro/ha for the zone B with respect to conventional fertiliser application.

Davide’s research falls into the CRC’s Program 2 research area.

Objectives:

• Study wheat nitrogen (N) response in rainfed environments using a crop model to identify optimal N rates
• Use remote sensing to quantify biophysical properties of wheat at different scales and at different growth stages and estimate N concentrations in wheat
• Use spatially integrating remote sensing and crop simulation modelling as an N fertilization management tool.

For more information, email Davide.