Predicting field scale yield: An integrated approach using high resolution satellite data and biophysical modelling

Yield impacts across the entire supply chain. Therefore the accurate prediction of yield at field or within field scales are critical information needed to aid farmers in making more informed decisions on crop production and thus to enhance their ability to better deal with a progressively changing and more extreme climate regimes.

In this presentation we discussed an integrated approach more accurately predict wheat yields at field scales. This approach fully utilises high spatial and temporal resolution remote sensing from Sentinel-2 and crop stress simulated from a biophysical model. Validation of the model across a diverse range of environments and its implications for industry are discussed.

Dr Yan Zhao

Centre for Crop Science, QAAFI, The University of Queensland

Dr Zhao's current research focusing on the development of integrated approaches from earth observations to predicting crop yield, crop area, crop production and crop physiological characteristics at high spatial and temporal resolutions. Dr. Zhao received his PhD in natural science from the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences in 2013. After completing his PhD, his research has mainly focused on applying remote sensing for understanding the ecosystem dynamics and the impacts of climate change and human interventions.