Roger A. Lawes1, Joanne Chai2, Yang Chen1, Randall J. Donohue3, Gonzalo Mata1, Zvi Hochman4, Franz Waldner4, Chris Sharman5, Roger Butler6
1 CSIRO Agriculture and Food, Underwood Ave, Floreat WA 6014, Australia; firstname.lastname@example.org,
2 CSIRO Data61, Underwood Ave, Floreat WA 6014, Australia,
3 CSIRO Land and Water, GPO Box 1700, Canberra, ACT 2061, Australia;
4 CSIRO Agriculture and Food, 306 Carmody Rd, St Lucia QLD 4067, Australia;
5 CSIRO Data61, College Rd, Sandy Bay TAS 7005, Australia.
6 CSIRO Data61, 1 Technology Court, Pullenvale, Qld 4069, Australia.
To successfully assess crop yield across Australia there is a need to monitor what has been sown and its progress as the season evolves. Crop type and species need to be identified at the paddock scale to calculate areas. Crop models then need to be applied to each individual paddock to generate a yield estimate. Finally, the information needs to be packaged at a resolution of interest. To generate state and national scale crop monitoring capability, a co-ordinated, multifaceted data gathering, data training, image capture, data acquisition and crop modelling operations were developed. Crop yield forecasting required new modelling techniques, as existing approaches were overwhelmed by the volume of data. We describe the detailed process of how we monitor and forecast crop production across the Australian landscape. Near real time crop monitoring products are now available across the Australian continent. This paper describes the overarching workflow of crop monitoring, forecasting and data dissemination to assist agribusiness to respond to the prevailing climate.