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Coastal resiliency is the ability of a beach–dune system to recover to a previous state after a storm, and this resiliency is affected by prestorm beach and dune morphology and storm climate (i.e. storm frequency and intensity). Improvements in remote sensing technology such as LIDAR and structure from motion have enabled rapid collection and production of digital elevation models used to assess storm impact and recovery. Although rapid poststorm assessment requires a consistent approach for extracting dune morphology, relatively little attention has focused on defining the different parts of a dune. The goals of this paper are to examine how the definition of a dune feature drives the methodology used to extract dunes and to synthesize a comprehensive definition of dune features. An analysis of existing approaches for extracting beach and dune morphology demonstrates that there is considerable variation in how the beach–dune transition (i.e. dune toe) is defined. Many definitions are recursive or include ambiguous terminology, resulting in a dune toe or crest line position dependent on user interpretation of the definition. Other definitions rely heavily on user interpretation of dune features at varying stages in the feature extraction process. Reliance on visual interpretation can result in substantially different feature locations across different interpreters. Given the impact of varying definitions on dune resiliency assessments and legal implications for dune features location, we propose a series of semantic models for dune features. Semantic modelling of coastal morphology is vital for consistently and accurately assessing coastal recovery and predicting future coastal assessments on the basis of a consistent set of criteria. 

ObjectivePatients have a poor understanding of outcomes related to total knee replacement (TKR) surgery, with most patients underestimating the potential benefits and overestimating the risk of complications. In this study, we sought to compare the impacts of descriptive information alone or in combination with an icon array, experience condition (images), or spinner on participants’ preference forTKR. MethodsA total of 648 members of an online arthritis network were randomized to 1 of 4 outcome presentation formats: numeric only, numeric with an icon array, numeric with a set of 50 images, or numeric with a functional spinner. Preferences forTKRwere measured before and immediately after viewing the outcome information using an 11‐point numeric rating scale. Knowledge was assessed by asking participants to report the frequency of each outcome. ResultsParticipants randomized to the icon array, images, and spinner had stronger preferences forTKR(after controlling for baseline preferences) compared to those viewing the numeric only format (P< 0.05 for all mean differences). Knowledge scores were highest in participants randomized to the icon array; however, knowledge did not mediate the association between format and change in preference forTKR. ConclusionDecision support at the point‐of‐care is being increasingly recognized as a vital component of care. Our findings suggest that adding graphic information to descriptive statistics strengthens preferences forTKR. Although experience formats using images may be too complex to use in clinical practice, icon arrays and spinners may be a viable and easily adaptable decision aid to support communication of probabilistic information.