Uncertainty analytics toolbox
Project vision: to help land managers make better decisions through novel analytics that assist in quantifying, visualising and communicating uncertainty
‘Uncertainty’ can be described as a situation involving imperfect or unknown information. By definition, making decisions in agriculture and land management about what to do (such as when to plant a crop) involves risk, because some things (such as next month’s rainfall) aren’t known. Land managers make their ‘best guesses’ or use predictions as they look to the future but these will be imperfect, unknown or incomplete.
A suite of analytics workflows, or ‘toolbox’, that quantifies, visualises and communicates uncertainty for agricultural problems would enable decision makers to better understand risk and make more informed decisions.
With our digital powerhouse of expertise in core statistics, machine learning and software engineering, coupled with our skills in the agricultural sector, Digiscape has a unique opportunity to develop a high-end product tailored for agriculture like no other organisation can.
The Digiscape uncertainty analytics toolbox will better quantify predictions and forecasts of agricultural systems in space and time. It will tell us how outputs from models can be judged, where models break down, where more monitoring data needs to be collected or where expert information is needed.
While the quantification of uncertainty in some modelling domains is not new, the development of a toolbox of analytics that incorporate workflows with multiple sources of input at different spatial and temporal resolutions is extremely novel – not to mention challenging.
This project is led by Dr Petra Kuhnert.