**Acknowledgements**

The density and variety of vegetation increases at BB moving from the crest landward. As a result, a significant reduction in the 'bare earth' points become problematic in these areas (**Figure 11B**). Vegetation filtering then becomes a less viable option. Although, these locations are less prone to low magnitude topographic changes, quantifying dune metrics (e.g., *Dh* or *Dv*) measured from UAV surveys would likely be inflated. Highly vegetated back dune areas are typically stable as they are protected from the wave, tidal, and wind processes that are actively shaping the seaward zones. These locations are likely to remain a 'zone of uncertainty' in UAV SfM surveys without significant vegetation removal or burial

*Spatial Variability in Environmental Science - Patterns, Processes, and Analyses*

Therefore, current UAV SfM applications for monitoring repeat topographic changes occurring in coastal systems are likely to be constrained to the backshore. The accuracy of UAV SfM data on unvegetated surfaces has been demonstrated and there is significant potential to increase the accuracy of sparsely vegetated foredune slopes by applying filtering algorithms (e.g., [41]). It is evident that challenges still remain in resolving water and vegetation boundaries; however, the benefits of UAVs are also clear as they provide an accessible cost-effective method to produce high resolution and spatially extensive surveys of sandy coastal systems. The number of UAV SfM monitoring studies in coastal systems are likely to increase in the coming years, but in order for these studies to confidently report topographic adjustments between the beach-dune boundary, addressing data uncertainties and improvements in vegetation filtering methods

This chapter has addressed common problems associated with UAV SfM research on sandy coastlines by presenting a methodology for survey and quality control measures, handling of uncertainties, and the interpretation of storm impacts. This introduction to basic geo-spatial techniques and considerations is aimed at coastal researchers who are developing UAV monitoring strategies. UAVs are becoming increasingly used to monitor beach-dune dynamics, so a systematic approach to address these issues are needed. This study has shown the ability of UAV SfM to accurately report the topographic adjustments of a sandy coastline that has been impacted by a storm event. However, it is also noted that our ability to confidently report these changes was aided in the removal of vegetation at the beach dune boundary. Post-storm recovery of the beach-dune system will be coincident with periods of vegetation growth and, thereby additional environmental

Future studies can advance upon these current methodological considerations, particularly regarding the application of vegetation filtering algorithms to reduce environmental uncertainties and constraints. A review of current filtering techniques applied to UAV SfM point clouds, and specifically aimed at removing vegetation characteristic of the backshore, could determine to what extent these systems are capable of continuously monitoring topographic changes occurring at the beach-

dune boundary. Using UAV SfM systems to accurately monitor subsequent foredune recovery are dependent on addressing the spatiotemporal uncertainties discussed in this chapter and resolving remaining limitations in handling backshore vegetation. As UAV SfM studies continue to increase in volume, it is critical that uncertainties are addressed in order to confidently monitor topographic adjustments resulting from storm impacts, post-storm recovery, and the longer-term

through blowout development, breaching, or overwash events.

are needed.

**6. Conclusion**

uncertainties will be introduced.

resiliency of beach-dune systems.

**84**

The authors would like to thank Prince Edward Island National Park for permitting our field work at Brackley Beach, logistical assistance, and supplying of equipment. We would also like to thank CBCL Limited for supplying the baseline LiDAR survey used in this chapter. Finally, a special thank you to Phillipe Wernette and Jacob Lehner for their invaluable field assistance.
