Paper No. 2
Presentation Time: 8:15 AM


WERNETTE, Phillipe A., Department of Geography, Texas A&M, College Station, TX 77845, SHORTRIDGE, Ashton, Department of Geography, Michigan State University, East Lansing, MI 488824, LUSCH, David, Department of Geography, Michigan State University, 673 Auditorium Road, East Lansing, MI 488824 and ARBOGAST, Alan, Geography, Michigan State University, 121 Geography Building, East Lansing, MI 48824,

Systematic shifts in shoreline position are important indicators of environmental change. Historical aerial imagery is used to measure past shoreline positions to conduct change analysis. Most published studies do not formally consider the potential impact of positional uncertainty or interpretation error on estimates of shoreline change. This research introduces and evaluates a novel, uncertainty-aware approach that explicitly integrates positional uncertainty into shoreline change detection. The approach extends the epsilon band model to account for multiple sources of positional uncertainty in two shorelines, and assesses their degree of overlap to distinguish significant change from noise. The method is contrasted with a standard change detection technique that uses regularly-spaced transects perpendicular to the shoreline to measure the direction and magnitude of change. A case study using shoreline data at four sites along the Michigan (USA) coast was used to evaluate these methods. Shoreline positions were manually delineated from aerial photography for multiple years between 1938 and 2010. An epsilon band was constructed for each feature to represent the positional uncertainty. These bands were used to visualize and test for significant change. The case study demonstrates that the overlapping epsilon band method is viable for analyzing change in linear features when the accuracy of these features has been quantified. In the case study, positional uncertainty introduced by the georeferencing process was greater than the amount introduced by interpretation error.