基于无人机技术地质露头三维表征识别&#x02014;&#x02014;以北京雁栖湖中侏罗统龙门组剖面为例&#x0002A;

刘浩宇; 马元博; 王浩任; 吴金旭; 谭锋奇; 张玉修

doi:10.7523/j.ucas.2025.016

中国科学院大学学报 >

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DOI: https://doi.org/10.7523/j.ucas.2025.016

基于无人机技术地质露头三维表征识别——以北京雁栖湖中侏罗统龙门组剖面为例^*

刘浩宇 ,
马元博 ,
王浩任 ,
吴金旭 ,
谭锋奇 ,
张玉修

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中国科学院大学地球与行星科学学院,北京 100049

收稿日期: 2025-01-20

修回日期: 2025-03-31

网络出版日期: 2025-04-16

基金资助

^*北京市自然科学基金面上项目(8232048) 、国家自然科学基金（41472209, 40802048）、中国科学院大学在线教学资源建设项目(Y95401BXX2)和中央高校基本科研业务费专项资金(E2E40409X2)资助

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Three-Dimensional Characterization and Identification of Geological Outcrops Using UAV Technology: A Case Study of the Middle Jurassic Longmen Formation Section around Yanqi Lake region, Beijing

LIU Haoyu ,
MA Yuanbo ,
WANG Haoren ,
WU Jinxu ,
TAN Fengqi ,
ZHANG Yuxiu

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College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2025-01-20

Revised date: 2025-03-31

Online published: 2025-04-16

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摘要

在传统地质工作中,野外数据采集主要依靠人工实地测量等方式,工作量大且不方便于数据统计,而且对于高陡处无法进行实地测量,存在诸多局限性。为此本文使用无人机倾斜摄影及机载激光雷达扫描两种拍摄方法,重建地质三维模型,在计算机中完成数据测量工作。选择北京市雁栖湖地区龙门组河流相地层为研究对象,在模型中将剖面地层分为9个岩相并对每层进行厚度及产状测量,同时识别断层、构造变形等地质现象。对模型进行空间坐标检验、精度验证,测量结果显示长度误差小于0.01 m,产状误差小于2°。综合剖面测量和无人机三维模型表征识别,认为该剖面在垂向上呈现多个辫状河沉积序列,沉积序列由下部的河道滞留沉积、中部的河道沙坝沉积和上部的洪水加积沉积构成。因此相较于传统地质数据采集工作,基于无人机地质三维模型数据采集能够满足质量与精度要求,同时提高工作效率并减少野外作业风险。

关键词： 无人机; 倾斜摄影测量; 机载激光雷达; 地质露头

本文引用格式

刘浩宇 , 马元博 , 王浩任 , 吴金旭 , 谭锋奇 , 张玉修 . 基于无人机技术地质露头三维表征识别——以北京雁栖湖中侏罗统龙门组剖面为例^*[J]. 中国科学院大学学报, 0 : 4 . DOI: 10.7523/j.ucas.2025.016

Abstract

In traditional geological fieldwork, data collection primarily relies on manual on-site measurements, which are labor-intensive and inconvenient for data analysis. Moreover, such methods are not feasible for steep and inaccessible areas, presenting numerous limitations. To address these challenges, this study employs two advanced techniques: UAV (Unmanned Arial Vehicle) oblique photogrammetry and airborne LiDAR scanning, to reconstruct three-dimensional geological models and conduct data measurements via computer analysis. The study focuses on the Longmen Group fluvial facies strata in the Yanqi Lake area of Beijing. Within the model, the stratigraphic profile is divided into nine lithofacies, with each layer subjected to measurements of thickness and orientation. Additionally, geological phenomena such as faults and structural deformations are identified. The model undergoes spatial coordinate verification and accuracy validation, revealing measurement errors of less than 0.01 meters in length and less than 2 degrees in orientation. Through comprehensive profile measurements and the characterization and identification afforded by the 3D model, it is concluded that the profile exhibits multiple braided river depositional sequences in the vertical dimension. These sequences consist of lower channel lag deposits, middle channel bar deposits, and upper floodplain aggradation deposits. Consequently, compared to traditional geological data collection methods, the use of UAV-based 3D geological models not only meets quality and precision standards but also enhances operational efficiency and reduces the risks associated with fieldwork.

Key words： UAV; oblique photogrammetry; airborne LiDAR; geological outcrop

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