Detection of subtle tectonic-geomorphic features in densely forested mountains by very high-resolution airborne LiDAR survey
Detection of subtle tectonic-geomorphic features in densely forested mountains by very high-resolution airborne LiDAR survey
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DOI：
10.1016/j.geomorph.2012.11.001
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发表时间：
2013-01-15
期刊：
影响因子：
3.9
通讯作者：
Chiba, Tatsuro
中科院分区：
文献类型：
--
作者：
Lin, Zhou;Kaneda, Heitaro;Chiba, Tatsuro
尽管在世界其他地方取得了成功，但来自标准机载激光雷达调查的2米分辨率DEM未能在日本中部森林茂密的高海拔山区检测到小的构造地貌特征。我们新的0.5米DEM从一个前所未有的高分辨率激光雷达调查沿着Neodani断层现在揭示了一些以前未知的断层崖以及其他隐藏的地貌特征。在总炮点密度高达12.7 m（-2）的情况下，该测量实现了6.2 m（-2）的地面回波密度。在不利条件下获得足够的地面回波的主要因素是飞行条带之间的大侧重叠（接近70%），这意味着目标区域中的任何特定区域从不同角度扫描三次或更多次。分辨率为0.25至10米的DEM的评估，确保0.5米分辨率的激光雷达DEM是必要的检测微妙的构造断裂。完整检测小的构造地貌特征的另一个关键因素是应用最近开发的DEM可视化“红色地貌图像图"，它允许绘制具有各种大小、方向和形态的所有小特征，克服了经典DEM可视化的主要缺点。一个非常高分辨率的激光雷达测量辅助RRIM可视化在这项研究中使用的提供了一个更可靠的方法，为隐藏在茂密的植被下的轻微活动断层痕迹的详细映射。(C)2012爱思唯尔有限公司版权所有。
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 similar to 12.7 m(-2). The main factor to gain sufficient ground returns in unfavorable conditions is a large side lap of similar to 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. (C) 2012 Elsevier B.V. All rights reserved.