A Continuation of Uncovering the Past Landscape of Central New Hampshire: Accuracy Assessment for Identifying Stonewalls Using LiDAR-derived Products

Authors: Hannah Kingston*,
Topics: Remote Sensing, Natural Resources, Cultural and Political Ecology
Keywords: remote sensing, archaeology, forestry, LiDAR, DEM
Session Type: Poster
Day: 4/13/2018
Start / End Time: 1:20 PM / 3:00 PM
Room: Napoleon Foyer/Common St. Corridor, Sheraton, 3rd Floor
Presentation File: No File Uploaded

Remote sensing is used to assist in understanding historical land use by identifying unique physical land characteristics that are representative of historical features. Digital elevation models (DEM), representing Earth’s bare surface, can be created from light detection and ranging (LiDAR) data. In New England, historical features, including stonewalls, can be digitized using LiDAR-derived DEM products. Common DEM-derived products, such as hillshade, slope, and aspect, can be used to manually digitize the areal extent and location of archaeological features. These historical features are considered significant sites that require documentation for various land management purposes. This is especially true for the preservation of such historical features within the White Mountain National Forest (WMNF), NH. Therefore, in 2016 we completed a field assessment within the WMNF using line-transect sampling to assess the accuracy of both the presence and absence of digitized stonewalls. Although we found that common derived-DEM products led to successful identification of stonewalls, methods of digitizing stonewalls that parallel roads were not always accurate and consistent among digitizers. The objective of this project was to investigate alternative DEM-derived visual renderings by evaluating surface topography to further delineate stonewalls. We found methods of calculating topographic ruggedness more clearly distinguished stonewalls from roads, especially dirt roads, than initial visual products. These results are essential for informing and standardizing digitizing practices for future statewide and regional efforts.

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