Northeastern Section - 56th Annual Meeting - 2021

Paper No. 12-5
Presentation Time: 9:25 AM

EVALUATING USER INTERPRETATION AND ERROR ASSOCIATED WITH DIGITIZING STONE WALLS USING AIRBORNE LIDAR


LEONARD, Jonathan, Geography, University of Connecticut, 149 Browns Rd, Storrs, CT 06268, OUIMET, William B., Dept. of Geosciences, University of Connecticut, Storrs, CT 06269-4148 and DOW, Samantha, Department of Geosciences, University of Connecticut, 354 Mansfield Rd, Storrs, CT 06269

Light Detection and Ranging (LiDAR) can be used in the northeast United States as a tool to uncover archeological features hidden beneath forest canopy. One prominent feature, stone walls, is the focus of projects in the region that aim to document the legacy of 17th-19th century agricultural practices. Stone walls stand out clearly in derivative LiDAR digital elevation model (DEM) products such as slope and hillshade maps. To date, mapping has been mainly carried out by on-screen digitization, but the error associated with such mapping, particularly as it relates to user interpretation, has not been evaluated. Furthermore, as large regions have yet to be analyzed and manual digitizing being a time consuming task, regional datasets are compiled from multiple users of varying expertise. One important issue associated with digitizing stone walls in LiDAR is that many structures could be misinterpreted as stone walls, such as: fences, roads, streams, vegetation boundaries, trails, and topographic ridges in terrain, whether natural or anthropogenic. This study examines user interpretation and error associated with digitizing stone walls using airborne LiDAR for four distinct landscape types in southern New England: forested with hilly terrain, forested with gently sloping terrain, residential area with cleared fields, and residential/suburban environment. Multiple users are given a LiDAR based slope map, two LiDAR based hillshade maps (with solar azimuths of 45° and 315°) and an aerial photograph. Results are compared regarding stone wall presence/absence and digitized length.