Field based research on dieback of woody weeds species in Australia, particularly parkinsonia (Parkinsonia aculeata), prickly acacia (Vachellia nilotica), Mesquite (Prosopis spp.), mimosa (Mimosa pigra) among others, relies upon visual assessment of indicators of disease or stress. Among these, foliage cover and extent of branch dieback assessed individually (Sacdalan 2015, Diplock 2016, Haque 2016) or in combination (Galea & Beilby 2009 & 2010) are standard approaches towards measuring dieback using categorical visual assessment classes.
The use of unmanned aerial vehicles (UAVs) and the development of lightweight and affordable multispectral cameras are finding their place in crop agronomy, providing a means for developing crop stress maps. This type of analysis can assist with problem diagnosis related to disease, insect damage, water stress and nutrient issues as well as measuring yield potential.
On-ground assessment of individual wild growing trees for both foliage cover and extent of dieback is somewhat problematic due to the effects of tree crowding and variation in light quality throughout the day. Overhead high resolution multispectral imagery provides a new opportunity to evaluate dieback induced stress; particularly in sites where a time series approach to observations are required. Simultaneous geo-located (GPS) canopy images photographed in green (550nm), red (660nm), red edge (735nm) near infrared (790nm) and full colour (RGB) are assembled into a mosaic, which when analysed, give a measure of plant stress using standardised approaches such as normalized difference vegetation index (NDVI). NDVI is a tool extensively used in satellite image and data capture methodologies; however the level of resolution offered by UAV mounted multispectral equipment provides a far greater degree of resolution, and potentially a more effective approach to studying population dieback events.