A YEAR IN THE LIFE OF A COASTAL BLUFF: SEASONAL INFLUENCES ON BLUFF EROSION OBSERVED WHILE TESTING THE APPLICATION OF STRUCTURE FROM MOTION PHOTOGRAMMETRY IN CASCO BAY, ME

Shoreline erosion in response to rising seas is difficult to resist. Recognizing the need for observational data on coastal bluff recession in Casco Bay, Maine, we employed Structure from Motion photogrammetry techniques in a complex intertidal environment to evaluate the application as an effective means to measure and monitor dynamic geomorphological changes occurring at select sites. Observations were evaluated with respect to: the coastal bluff erosion cycle conceptual model; anticipation of local sea level rise; local landslide hazards; and preservation of a shoreline status record. While a sequence of landslide events is often viewed as a single, uniform rate of retreat over time; large-scale events are far more dangerous in that they are sudden and, as yet, unpredictable. A lack of systematic observations of coastal bluff erosion challenges understanding and stunts of the growth of situational awareness. The great scale of Maine’s coastline compounds the problem by keeping a comprehensive survey out of figurative reach and places the onus of coastal zone management on individual property owners under the jurisdiction of local municipal offices. The purpose of this work is to demonstrate an efficient method of measuring bluff erosion at an appropriate scale to inform the development of a regional coastal management tool. In practice, the dependence of Structure from Motion on photographs as source information has led to a wealth of repeat field observations that now show erosion behavior shifting with the seasons. The resulting 3D surface products preserve the shoreline status in great detail at the time of capture and are useful for both mapping and numerical modeling of nearshore dynamics. Structure from Motion is heralded as an emergent photogrammetric technique and found to be easily deployable survey method, favored for its ease of use; budget-friendly equipment; and relatively low start-up costs. Conclusions are drawn concerning potential errors associated with the method as well as an offering of suggestions for best practices moving forward.