LiDAR as a Tool for Lineament Mapping and the Reevaluation of Bedrock and Glacial Geology: Examples from the Mount Moosilauke Region of the White Mountain National Forest, New Hampshire

The increased availability and reliability of meter and sub-meter resolution LiDAR has provided unprecedented opportunities to map geologic features in the last decade. Using ArcGIS and 2010/2012 1-meter resolution LiDAR data provided by the Natural Resources Conservation Service (DeKett et al., 2013), this study explored the use of LiDAR as a tool in bedrock and glacial geology by 1) comparing field-based fracture measurements with LiDAR-based remote lineament measurements, 2) delineating bedrock-controlled and glacially-controlled regions through landscape mapping, 3) reevaluating the distribution and character of previously mapped bedrock units by Billings et al. (1935a), Lyons et al. (1997) and others, and 4) mapping glacial erosional and depositional features, all within the Mount Moosilauke region of the White Mountain National Forest, New Hampshire. The major bedrock units and the statistically significant joint sets, as measured at single, extensive, outcrops during the field-based portion of this study, include: 1) the Littleton Formation with three joint sets trending NNW to SSE, N to S, and NE to SW; 2) the Bethlehem Granodiorite with one joint set trending NE to SW; 3) the Kinsman Granodiorite with two joint sets trending NE to SW and ESE to WNW; 4) the Oliverian Plutonic Suite with two joint sets trending N to S and ENE to WSW; and 5) the Ammonoosuc Volcanics with one joint set trending ENE to WSW. Paleostress reconstructions identified tensile-compressive environments from two distinct events: NW to SE extension and N to S extension believed to be related to earlier and later stages of the Mesozoic rifting of Pangaea. These joint sets were compared to 1,145 coincident lineaments identified through the Mabee et al. (1994) analyses of LiDAR-derived hillshade images within the Mount Moosilauke 7.5’ Quadrangle. Correlations between the field measured joint sets and remotely measured lineament sets were moderate, although these correlations appear to be moderate to strong when considering factors such as sample size and field site location. Through fracture and lineament analyses, bedrock units were determined to have unique bedrock fracture signatures. By further analyzing bedrock-controlled regions as identified during the landscape mapping portion of this study, these bedrock fracture patterns were used in combination with generations of bedrock geologic maps and eventually incorporated into interpretations of LiDAR hillshade images to produce a revised bedrock geologic map with revised geologic contacts and faults as well as newly mapped mega-lineaments. Lastly, LiDAR-based mapping within glacial erosional and depositional feature-controlled regions was conducted in an effort to map glacial deposits and landforms including esker systems, ridges interpreted as De Geer moraines, meltwater channels, ice flow indicators, and stoss and lee topography. LiDAR has proved to be an extremely effective tool to study bedrock and glacial features, contributing to the increased accuracy and efficiency of geologic mapping. Future work will be needed, however, to ground truth remote interpretations with targeted fieldwork