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Tuesday, November 7 • 10:30am - 11:00am
User Session. Mapping Stone Walls and Relict Land Use Features with LIDAR Data

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AUTHORS: William B. Ouimet*, Department of Geography and Center for Integrative Geosciences, University of Connecticut; Katharine M. Johnson, Department of Geography and Center for Integrative Geosciences, University of Connecticut, and Earth Resources Technology, Inc., NOAA National Centers for Environmental Information, Asheville, NC

ABSTRACT: High-resolution, publicly available airborne LiDAR data for southern New England has transformed the ability to identify and map fine scale topographic features related to past human activity, particularly those which lie abandoned and covered by modern forests.The most well-known and widespread example of these features seen in LIDAR data are stone walls, which indicate areas used for 17th to early 20th century agriculture and pasture. Another widespread but less well-known feature type that can be detected by LiDAR is relict charcoal hearths, which were primarily used in the 19th century for charcoal production associated with iron furnaces. Additional features seen in LIDAR include old roads, trails, dams and drainage ditches. This presentation will outline and discuss the steps and techniques involved with mapping these historic era features with LiDAR data, including: downloading and working with LiDAR data; employing DEM visualization techniques; and, identifying and digitizing features. In addition to creating, analyzing and publishing maps of stone walls (Johnson and Ouimet, 2016), we have recently been applying this approach in undergraduate GIS courses and plan to develop a workshop with similar aims. LiDAR is available for the entire extents of CT, RI, MA and parts of NY, VT, and NH, but to date historic features have only been mapped in isolated portions. Datasets of historic features created through this approach will aid preservation and conservation efforts by enabling scientists, archaeologists, and concerned groups to locate, research, catalogue and demarcate the features, as well as their material sources and impact.

Tuesday November 7, 2017 10:30am - 11:00am EST
  User Sessions, Remote Sensing/Imagery