基于机载LiDAR的隐患滑坡增强显示与识别研究
Enhanced Display and Identification of Hidden Landslides Based on Airborne LiDAR
贾越 1夏永华 2吕杰 3赵昌福4
作者信息
- 1. 昆明理工大学国土资源工程学院,云南 昆明 650093;云南大学高原山区空间信息测绘技术应用工程研究中心,云南 昆明 650093
- 2. 昆明理工大学城市学院,云南 昆明 650051;云南大学高原山区空间信息测绘技术应用工程研究中心,云南 昆明 650093
- 3. 昆明理工大学城市学院,云南 昆明 650051
- 4. 昆明理工大学国土资源工程学院,云南 昆明 650093
- 折叠
摘要
针对传统滑坡监测方法在复杂地形和植被覆盖区域的局限性,提出了一种基于机载激光雷达技术的滑坡隐患增强显示与识别方法.研究结合山体阴影、斜率分析、红色立体图、天空视域因子等多种地形可视化技术构建了高精度数字高程模型.使用支持向量机(SVM)模型对融合后的影像进行分类,以识别滑坡易发区域.实验结果表明,该方法能够有效识别和增强显示滑坡隐患区域,而基于SVM的滑坡易发区域识别精度达到了83.86%.所提方法不仅增强了滑坡隐患区域的可视化效果,还提高了滑坡易发区域识别的精确度,对滑坡灾害的预防和应急响应提供了有效的技术支持.
Abstract
To address the limitations of conventional methods for monitoring landslide in complex terrains and vegetation-covered areas,this paper proposes an enhanced display and recognition method for landslide hazard based on airborne LiDAR technology.In particular,the construction of a high-precision digital elevation model is adopted in conjunction with various terrain-visualization techniques,such as mountain shadows,slope analysis,red stereo maps,and sky field of view factors.The support vector machine(SVM)model is used to classify fused images and identify landslide-susceptible areas.Experimental results show that this method effectively identifies and enhances the display of landslide hazard areas,and that its accuracy in identifying landslide-susceptible areas based on the SVM is 83.86%.The proposed method not only enhances the visualization of landslide hazard areas but also improves the accuracy in identifying landslide-susceptible areas,thus providing effective technical support for landslide disaster prevention and emergency response.
关键词
机载激光雷达/地形可视化/影像融合/支持向量机/滑坡识别Key words
airborne LiDAR/terrain visualization/image fusion/support vector machine/landslide identification引用本文复制引用
出版年
2024
NETL
NSTL
万方数据