Monitoring Tree Crops through Earth Observation data
Monitoring Tree Crops Condition
This research theme aims to
Review the current scientific literature on the methods of monitoring various stressors (i.e., water stress, pests, and diseases) of tree crops from EO data.
Identify biophysical variables (i.e., canopy water content, Leaf Area index) that can be generated from EO data and used to monitor/quantify changes in tree crop vigor linked to the stressor.
In discussion with key stakeholders, identify pilot areas for testing the methods for monitoring tree crops' health and condition in Australia.
Design algorithms (leveraging machine and deep learning techniques) for processing EO data to monitor various tree crop stressors and identification of anomalies.
Using crop biophysical properties to monitor tree crops' conditions
Data retrieved from satellite imagery and dynamic analytics of crop biophysical properties such as leaf area index (LAI), leaf chlorophyll content (LCC), leaf water content (LCW), and the fraction absorbed photosynthetically active radiation (fAPAR) are used to monitor crop health in near real-time.
Multiyear time series crop biophysical properties for benchmarking crop growth
