使用LiDAR衍生的DEM进行增强的山体滑坡可视化和痕迹识别
Jie Lv1, Chengzhuo Lu2, Minjun Ye2
1Department of Earth Science and Technology, City College, Kunming University of Science and Technology, Kunming 650093, China.
Sensors (Basel, Switzerland)
|July 30, 2025
概括
这项研究引入了一种增强的空中LiDAR方法,用于改进山体滑坡微观地形显示和在复杂的植被地形上的痕迹识别. 这项技术准确地提取了山体滑坡的痕迹,超过了传统的正形照片.
科学领域:
- 地质科学 地质科学
- 遥感 遥感 遥感 遥感
- 地质形态学 地质形态学
背景情况:
- 传统的遥感在复杂的植被地形中与微观地形作斗争.
- 准确的山体滑坡绘图对于灾害管理和风险评估至关重要.
研究的目的:
- 开发一种使用空中LiDAR进行滑坡地形显示和痕迹识别的增强方法.
- 为了提高山体滑坡微观地形图的准确性,在具有挑战性的环境中进行特征提取.
主要方法:
- 从点云数据构建一个高精度LiDAR-DEM.
- 生成可视化图像 (山,坡度,开放度,天空视图因子).
- 像素级图像融合,碎形建模和平均转移算法用于痕迹提取.
主要成果:
- 像素级图像融合有效地增强了滑坡微观地形图表显示.
- 组合的分形模型和平均转移算法准确地提取了山体滑坡的痕迹.
- 拟议的方法显示出优越的性能,相比于基于orthophoto的提取.
结论:
- 空载激光雷达与先进的可视化和图像处理相结合,提供了卓越的滑坡地形分析.
- 这种方法为滑坡灾害紧急调查提供了有效的技术支持.
- 这些发现对于植被丰富,复杂的山区的山体滑坡研究有价值.
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