## 4 Discussion  
The results from this study indicate the potential of high resolution WV imagery for accurately mapping fruit yield (kg-tree\({}^{-1}\)) and average fruit size (g) across multiple avocado orchards and seasons  
Figure 8: Classified yield maps derived from the best fit model of the relationship between VIs and total fruit weight (kg-tree\({}^{-1}\)) for Block 2 in (**a**) 2016 and (**b**) 2017.  
Figure 9: Classified fruit size (g) per tree maps derived from the best fit model of the relationship between VIs and average fruit size (g) per tree for Block 2 in (**a**) 2016 and (**b**) 2017.  
in the Bundaberg region of Queensland, Australia. The low R-squared values achieved using the data for all blocks and all years for both yield parameters, and the subsequent increase in R-squared values when the data for each block was analysed separately, suggests that there is not a consistent relationship across all blocks between yield and canopy reflectance as measured by the selected VL The results suggest that a single 'generic' algorithm is not suitable, and that a site specific algorithm (i.e., for each block) is needed to estimate the yield parameters at the individual block level, a result that is consistent with those presented for apple and pear crops (S  
avocado tree canopies are able to be observed at tree maturity. However, it is also costly to purchase, and a minimum area of 100 m\({}^{2}\) is required to be ordered for tasking to occur. Freely available alternatives are Landsat and Sentinel 2 (25 m and 10-20 m pixel resolution respectively). However, the coarser resolution of these satellite images mean that multiple tree canopies determine the spectral reflectance of each pixel. In addition, the red-edge band in WV imagery was shown in this study to be an important predictor of yield and this band is not available from Landsat, and only available at 20 m resolution from Sentinel 2. Other alternatives for imagery capture are unmanned aerial vehicles (UAVs) or manned aircraft. These alternatives are generally more expensive on a cost to area ratio, unless the vehicle and image processing is completed by the orchard grower themselves (something that is beyond the scope of many growers).  
For this reason, the purchase of high-resolution satellite imagery such as Worldview is a viable cost-effective solution for orchard variability mapping and yield prediction, particularly if costs are shared between adjacent orchards. It is also possible that new additions such as Planet's Dove satellites, which offer almost daily temporal coverage, will offer a viable cost-affordable option in terms of spatial resolution (3 m pixels). However, these sensors do not currently provide a re-edge sensor. Further research would need to be completed to determine if the increased temporal frequency offered by the Dove satellite constellation is able to be used for accurate avocado yield prediction.  
This study only explored the relationship between yield and satellite imagery in the Bundaberg region of Queensland, Australia. It is likely that different relationships will occur in other regions and different VIs to those identified here may be the best predictors of yield. Further research will investigate how VIs relate to avocado yield in other growing regions of Australia.