What is real? Identifying patterns of erosion and deposition in context of spatially-variable uncertainty

Authors: Phillipe Wernette*, University of Windsor, Jacob Lehner, University of Windsor, Chris Houser, University of Windsor
Topics: Marine and Coastal Resources, Geomorphology, Geographic Information Science and Systems
Keywords: coastal geomorphology, environmental change, erosion monitoring, GIS, remote sensing, error analysis
Session Type: Poster
Day: 4/5/2019
Start / End Time: 1:10 PM / 2:50 PM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: No File Uploaded

Measuring coastal erosion and deposition can be accomplished using a wide variety of field and remote sensing techniques. A common approach is to calculate the difference between two spatially equivalent digital elevation models (DEMs) acquired at different times. However, measurement and interpolation uncertainty can significantly skew the magnitude of erosion or deposition. Current approaches to evaluate coastal change require subjective user-defined thresholds or make assumptions about adjacency, which may not be true in all cases. This paper presents a probabilistic approach to measuring DEM change that accounts for spatially-variable uncertainty and is not dependent on user-defined thresholds. The probability that the observed erosion or deposition for any given location is ‘real’ is determined by computing the area of overlap between two uncertainty distributions around the DEM surface. This overlapping area provides information about the likelihood that the observed erosion/deposition is influenced by uncertainty in both surfaces. Case studies from Follets Island, TX, Padre Island National Seashore, TX, and Pensacola, FL highlight the importance of accounting for uncertainty when monitoring for ‘real’ coastal erosion and deposition. The described approach also has potential application for monitoring changes across a range of landscapes.

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