泸石高速公路沿线历史地震诱发滑坡遥感调查及发育分布规律

魏旭; 彭志忠; 刘兴臣; 肖励之

doi:10.19509/j.cnki.dzkq.tb20220653

泸石高速公路沿线历史地震诱发滑坡遥感调查及发育分布规律

doi: 10.19509/j.cnki.dzkq.tb20220653

1.
成都理工大学地质灾害防治与地质环境保护国家重点实验室, 成都 610059
2.
四川泸石高速公路有限责任公司, 成都 610000

基金项目:

国家自然科学基金项目 41941019

详细信息

作者简介:
魏旭, E-mail: 1207288906@qq.com

通讯作者:
彭志忠, E-mail: 99975724@qq.com

中图分类号: P642.22
计量
- 文章访问数: 36
- PDF下载量: 3
- 被引次数: 0
出版历程
- 收稿日期: 2022-11-22
- 录用日期: 2023-01-09
- 修回日期: 2022-12-22

Remote sensing investigation and development distribution of historical earthquake-induced landslides along Lushi Expressway

1.
State Key Laboratory of Geological Disaster Prevention and Environmental Protection, Chengdu University of Technology, Chengdu 610059, China
2.
Sichuan Lushi Expressway Co., Ltd., Chengdu 610000, China

More Information

Author Bio:
WEI Xu, E-mail: 1207288906@qq.com

Corresponding author: PENG Zhizhong, E-mail: 99975724@qq.com

摘要

摘要:
泸(定)石(棉)高速公路沿线断裂构造发育, 地震频发, 造成区域内历史地震诱发的滑坡数量多且规模大, 然而这些地震滑坡体表面生长大量植被, 传统调查难以高效查明地震滑坡分布位置及发育规律。为了减少地震滑坡对公路建设带来的安全隐患, 首先以高精度机载LiDAR数据对地震滑坡进行了识别, 并通过野外复核验证识别的准确性；其次利用高精度机载LiDAR影像对地震滑坡的变形特征进行了分析；最后, 综合考虑地形、地质、地震三大因素(6个因子), 对地震滑坡的空间分布特征进行了分析。结果表明: 利用机载LiDAR技术能够有效地发现植被层下的地震滑坡, 在泸石高速公路沿线共识别出地震滑坡23处, 野外复核验证精度达100%；通过对控制地震滑坡空间分布的6个因子的分析, 得出与断裂构造和地震相关性最高。研究结果为植被茂密山区高速公路的滑坡识别调查提供了一定的参考并为泸石高速公路滑坡灾害防治与风险评价提供了数据支撑。
- 机载LiDAR /
- 地震滑坡 /
- 滑坡识别 /
- 分布规律 /
- 遥感调查 /
- 高速公路
Abstract: Objective
The fault structure along the Lu (ding) Shi (main) highway has developed, and earthquakes are frequent, resulting in a large number and large scale of historical earthquake-induced landslides in the region. However, a large amount of vegetation grows on the surface of these seismic landslides, and it is difficult for traditional surveys to efficiently identify the distribution location and development law of earthquake landslides.
Methods
To reduce the safety hazards caused by earthquake landslides during highway construction, this paper first identifies earthquake landslides with high-precision airborne LiDAR data and verifies the accuracy of identification through field review.Second, high-precision airborne LiDAR images are used to analyse the deformation characteristics of seismic landslides.Finally, the spatial distribution characteristics of the seismic landslides are analysed by comprehensively considering the three major factors (6 factors) of topography, geology and earthquakes.
Results
The results show that airborne LiDAR technology can be used to effectively detect seismic landslides under vegetation layers. A total of 23 seismic landslides are identified along the Lushi Expressway Common Road, and the accuracy of field review and verification is 100%.By analysing the six factors controlling the spatial distribution of seismic landslides, it is concluded that the correlations with fault structure and earthquakes are the highest.
Conclusion
The research results provide a reference for landslide identification and investigations of expressways with dense vegetation and provide data support for landslide disaster prevention and risk assessment of the Lushi Expressway.
- airborne LiDAR /
- earthquake landslide /
- landslide identification /
- distribution law /
- komote sensing investigation /
- expressway
注释:

所有作者声明不存在利益冲突。

HTML全文

图 1 研究区地理位置与地质背景图

Figure 1. Geographic location and geological background map of the study area

下载: 全尺寸图片幻灯片

图 2 地震滑坡分布图

Figure 2. Earthquake landslide distribution map

下载: 全尺寸图片幻灯片

图 3 烂田湾滑坡LiDAR影像及现场复核照片

a.滑坡机载LiDAR影像; b.滑坡现场情况; c.滑坡前缘局部滑塌; d.烂田湾滑坡A—A′纵剖面示意图

Figure 3. LiDAR image and on-site review photos of Lantianwan landslide

下载: 全尺寸图片幻灯片

图 4 泸石高速公路沿线地震滑坡变形特征

a.红军渡地震滑坡拉张裂缝；b.马列村地震滑拉张裂缝；c.摩岗岭地震滑坡的下错陡坎；d.由次级滑动形成的半圆形线条

Figure 4. Deformation characteristics of earthquake landslides along Lushi Expressway

下载: 全尺寸图片幻灯片

图 5 不同因子下地震滑坡分布图

Figure 5. Distribution map of earthquake landslides under different factors

下载: 全尺寸图片幻灯片

表 1 研究区地震滑坡解译标志图谱

Table 1. Map of earthquake landslide interpretation indicators in the study area

地震滑坡类型	拉裂-滑移型	拉裂-抛射型
解译特征	①滑坡后缘岩体较为破碎，通常可见拉张裂隙和下错陡坎 ②滑坡的剖面形态近“L”型 ③滑坡堆积体位于斜坡中下部，且整体完整性较好	①滑坡后缘岩体十分破碎，滑坡后壁坡度较陡 ②滑源区一般位于斜坡的中上部，且存在明显的凹腔 ③滑源区与堆积区距离较远，且滑坡堆积体较破碎
光学影像
机载LiDAR影像
三维示意图谱

下载: 导出CSV

表 2 地震滑坡信息

Table 2. Earthquake landslide information table

编号	滑坡名称	面积/m²	体积/m³	规模	经度	纬度	岩性
0	四湾里滑坡	1.3×10⁶	5.0×10⁷	特大型	102°13′49.812″E	29°56′18.401″N	片麻岩
1	小海子滑坡	3.7×10⁵	3.7×10⁶	大型	102°12′28.718″E	29°54′13.943″N	片麻岩
2	竹林坪滑坡	1.1×10⁶	1.5×10⁷	特大型	102°10′38.920″E	29°54′15.876″N	闪长岩
3	甘草村滑坡	7.2×10⁶	7.2×10⁸	巨型	102°11′39.650″E	29°54′1.210″N	闪长岩
4	甘谷地滑坡	6.4×10⁵	6.4×10⁶	大型	102°13′35.174″E	29°50′9.026″N	花岗岩
5	上松林滑坡	5.7×10⁶	3.4×10⁸	巨型	102°11′57.907″E	29°49′18.698″N	角闪岩
6	下松林滑坡	3.5×10⁶	8.9×10⁷	特大型	102°12′47.852″E	29°46′46.107″N	花岗岩
7	鸟支索滑坡	5.4×10⁶	2.0×10⁸	巨型	102°13′11.861″E	29°49′28.429″N	角闪岩
8	海子村滑坡	1.3×10⁶	2.6×10⁷	特大型	102°11′30.545″E	29°43′13.100″N	角闪岩
9	瓦斯沟滑坡	3.9×10⁶	1.9×10⁷	特大型	102°12′49.410″E	29°43′0.062″N	花岗岩
10	高河坝滑坡	2.6×10⁶	4.6×10⁷	特大型	102°12′44.599″E	29°41′45.495″N	花岗岩
11	寨子坪滑坡	6.5×10⁵	2.3×10⁶	大型	102°11′39.283″E	29°41′35.822″N	花岗岩
12	加郡滑坡	7.7×10⁶	1.3×10⁸	巨型	102°12′34.711″E	29°40′20.625″N	花岗岩
13	上奎武滑坡	2.5×10⁶	5.5×10⁷	特大型	102°11′25.072″E	29°39′45.096″N	花岗岩
14	马列村滑坡	1.1×10⁶	3.1×10⁷	特大型	102°11′7.757″E	29°36′51.953″N	角闪岩
15	摩岗岭滑坡	9.4×10⁵	4.5×10⁷	特大型	102°9′27.219″E	29°37′20.338″N	闪长岩
16	小马场滑坡	7.1×10⁵	3.4×10⁶	大型	102°11′7.689″E	29°36′15.737″N	超基性岩
17	烂田湾滑坡	1.7×10⁶	3.0×10⁷	特大型	102°11′20.646″E	29°35′33.054″N	花岗岩
18	得妥滑坡	3.7×10⁵	4.3×10⁶	大型	102°11′3.553″E	29°34′10.887″N	花岗岩
19	新华滑坡	2.8×10⁵	2.7×10⁶	大型	102°10′39.879″E	29°31′14.973″N	花岗岩
20	干谷地滑坡	1.3×10⁶	3.9×10⁷	特大型	102°14′58.679″E	29°22′47.424″N	花岗岩
21	干池沟滑坡	1.1×10⁶	3.2×10⁷	特大型	102°16′0.304″E	29°21′6.399″N	花岗岩
22	红军渡滑坡	1.6×10⁵	4.7×10⁶	大型	102°19′1.994″E	29°14′37.330″N	花岗岩

下载: 导出CSV

表 3 地震滑坡控制因子分级

Table 3. Classification of earthquake landslide control factors

因子类型	因子名称	因子分级
地形	高程/m	＜1 200；[1 200, 1 400)；[1 400, 1 600)；[1 600, 1 800)；[1 800, 2 000]；＞2 000
	坡度/(°)	＜10；[10, 20)；[20, 30)；[30, 40]；＞40
	坡向	平；北；北东；东；东南；南；西南；西；北西
地质	地层岩性	花岗岩；角闪岩；片麻岩；闪长岩；志留系、超基性岩；其他
地震	距断层距离/km	[0, 1)；[1, 2)；[2, 3)；[3, 4];＞4
地震	PGA/g	< 0.1；[0.1, 0.2)；[0.2, 0.3]；＞0.3

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