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National Accessible DataBase

Amy Lobben, W. Andrew Marcus, Nick Perdue, Shiloh Dietz, Antoine Nzeyimana.  While municipalities’ geospatial databases likely include ADA mandated features, there are many other environmental features (i.e. slope, surface material, sidewalk obstructions…) that represent barriers or facilitators to accessible navigation for people with disabilities.  These features are largely not included in municipalities’ geospatial databases.  In order to provide a national-level accessible routing tool, we first need the national-level database.  The sheer volume of data needed precludes on-the-ground mapping.  As a result, we are adopting a machine learning approach in which we are exploring two methods (traditional computational modeling as well as scraping street-view images) for imputing the categorical/nominal missing data.  We are grateful for support for this research from the National Science Foundation – BCS – Geography and Spatial Science as well as the College of Arts and Sciences at University of Oregon.