Towards Automated/Semiautomated Extraction of Faults from Lidar Data

Abstract

The Pajarito fault system is a complex zone of deformation and a seismically active region nestled within the Rio Grande rift in north-central New Mexico. Numerous laterally discontinuous faults and associated folds and fractures interact in a manner that has important implications for seismic hazards and risk mitigation. Previous efforts have established a foundation for the location of lineaments and structures in the Pajarito fault system; however, ensuring the completeness of the current lineament mapping is required for identifying areas for field validation, evaluating the potential for future seismic activity, and better understanding fault interaction. Assistance with this fault-mapping task via automated or semiautomated techniques as applied to lidar data over a large area of interest is highly desirable. A proof-of-concept processing flow which transforms lidar point-cloud data into a raster of surficial fault candidates is described and illustrated herein. These initial results hold great promise toward achieving our ultimate goal.