Title of article :
Detection of subtle tectonic–geomorphic features in densely forested mountains by very high-resolution airborne LiDAR survey
Author/Authors :
Lin، نويسنده , , Zhou and Kaneda، نويسنده , , Heitaro and Mukoyama، نويسنده , , Sakae and Asada، نويسنده , , Norichika and Chiba، نويسنده , , Tatsuro، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Pages :
12
From page :
104
To page :
115
Abstract :
Despite successes elsewhere in the world, 2 m resolution DEMs from a standard airborne LiDAR survey failed to detect small tectonic–geomorphic features in densely-forested high-relief mountains of central Japan. Our new 0.5-m DEMs from an unprecedentedly high-resolution LiDAR survey along the Neodani Fault now reveal a number of previously unknown fault scarps as well as other hidden geomorphic features. The survey achieves a ground-return density of 6.2 m− 2 out of a total shot density of as much as ~ 12.7 m− 2. The main factor to gain sufficient ground returns in unfavorable conditions is a large side lap of ~ 70% between flight swaths, which means that any specific area in the target zone is scanned three or more times from different angles. Evaluation of DEMs with resolution from 0.25 to 10 m assures that a 0.5m resolution LiDAR DEM is necessary for the detection of subtle tectonic breaks. Another key factor for complete detection of small tectonic–geomorphic features is the application of a recently developed DEM visualization “Red Relief Image Map (RRIM)”, which allows mapping of all the small features with various sizes, orientations and morphology, overcoming major drawbacks of classic DEM visualizations. A very high-resolution LiDAR survey aided with RRIM visualization as used in this study provides a more reliable approach for the detailed mapping of slight active fault traces hidden under dense vegetation.
Keywords :
tectonic geomorphology , Airborne LiDAR , RRIM , DEM
Journal title :
Geomorphology
Serial Year :
2013
Journal title :
Geomorphology
Record number :
2362189
Link To Document :
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