This project aims to develop a software-based tool to remotely map crop type (wheat, barley, chickpea, lentils, sorghum and mungbean) and development stage at the sub-paddock scale. The project will combine remote sensing, crop simulation modelling, machine learning and field validation datasets to develop an approach that captures data on crop type and developmental stage every five days at a 10-metre spatial resolution using satellite imagery. Knowing the likely area of crop emergence and phenological stage will provide growers and advisers with information that will assist them optimise management decisions.
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