摘要
地表裂缝作为斜坡变形的前兆特征之一,能够对地质灾害早期识别、运动失稳特征确定提供预报信息。受地形条件影响,人工排查效率低,使用单一遥感数据识别也难以解决复杂背景下裂缝的尺寸效应及噪点滤波问题。为了高效采集变形斜坡地表裂缝分布位置及几何信息,采用以无人机仿地飞行获取的点云及数字正射影像图作为数据源。首先,利用分别以点云粗糙度、坡度、离散度、数字图像像素梯度、灰度值和RGB(red green blue)值作为特征的6种算法模型实现斜坡裂缝的初步识别,进行不同模型的受试者工作特征曲线检验并确定分割阈值;其次,通过形态修复、基于密度聚类算法索引的裂缝方向、长度、频数3种滤波算法对初始提取结果进行背景噪点处理,在最小程度造成裂缝失真情况下能够最高去除82.7%的噪点;然后,采用二分类模型评价指标分析6种滤波后裂缝提取结果的优劣性,并针对裂缝尺寸效应获得数据融合后的最优检测模型(F1=0.8350);最后,基于裂缝骨架及轮廓自动计算了数量、长度、宽度、方向、离散度、裂纹密度6个定量化特征指标。结果表明,采用多维数据融合能够解决地表裂缝识别的空间尺度效应,以裂缝单元索引的滤波处理方式能够适用于大范围复杂地表场景下的噪点去除。
Objectives:As one of the precursor features of slope deformation,surface cracks can provide forecast information for the early identification of geological hazards and the determination of motion insta⁃bility characteristics.Affected by terrain conditions,the efficiency of manual investigation is low,and it is difficult to solve the problem of size effect and noise filtering of cracks in complex backgrounds using a sin⁃gle remote sensing data identification.In order to efficiently collect the location and geometry information of surface fractures on deformed slopes,the main purpose is to develop a method system for automatic crack identification and information statistics based on remote sensing data,which is suitable for large-scale slope surfaces.Methods:Using the high-resolution three⁃dimensional point cloud and orthophoto image generated by autonomous terrain-following flight technology as the data source,the automatic extraction of cracks and the statistical research on the deformed slope of the reservoir bank of Baihetan Hydropower Station are carried out.The initial automatic identification of slope cracks is completed by using six algorithm models with point cloud's roughness,slope,dispersion and digital images pixel gradient,gray value and RGB(red green blue)value as identification features respectively.Completed receiver operating characteristic curve(ROC)tests of different models and determined segmentation thresholds.The initial extraction results are processed by morphological repair and three filtering algorithms of crack direction,length and frequency based on density-based spatial clustering of applications with noise(DBSCAN)algorithm index to deal with background noise.The two-category evaluation index is used to analyze the pros and cons of the 6 filtered crack extraction results,and for the effect of crack size,the optimal detection model after data fusion is ob⁃tained.Based on the crack skeleton and outline,6 quantitative characteristic indicators of quantity,length,width,direction
作者
邓博
许强
董秀军
巨袁臻
胡武婷
DENG Bo;XU Qiang;DONG Xiujun;JU Yuanzhen;HU Wuting(State Key Laboratory of Geohazard Prevention and Geo-environmental Protection,Chengdu University of Technology,Chengdu 610059,China)
出处
《武汉大学学报（信息科学版）》
EI
CAS
CSCD
北大核心
2023年第8期1296-1311,共16页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金(41941019,42072306)。
关键词
无人机
地质灾害
斜坡变形裂缝
自动提取
信息统计
unmanned aerial vehicle(UAV)
geological disasters
slope deformation cracks
automatic ex⁃traction
information statistics
