Route Selection of Landslide Prone Area in Wenchuan Section of Chengdu-Wenchuan Expressway Based on SBAS-InSAR
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摘要: 西南山区地质构造复杂导致大量的滑坡分布.为了科学有效的指导西南山区道路选线，提前规避地质灾害高风险，滑坡灾害早期识别必不可少.合成孔径雷达干涉测量(interferometric synthetic aperture radar，InSAR)技术因其全天候、多时相等特点被广泛应用于滑坡灾害的早期识别中.收集了87景Sentinel-1A降轨数据，利用差分干涉测量短基线集时序分析(small baseline subset interferometric synthetic aperture radar，SBAS-InSAR)技术对成汶高速路汶川段进行形变区的识别与分析，结果显示共识别出10处，经野外复核均为处于持续变形中的滑坡，有较好的一致性.根据早期识别结果，对3个比选方案进行综合对比分析，确定方案B为最优选择.SBAS-InSAR技术能有效识别山区公路潜在滑坡隐患区，为山区公路的准确选线提供科学依据.
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关键词:
- 高速公路选线 /
- 滑坡隐患 /
- 差分干涉测量短基线集时序分析 /
- 时序形变分析 /
- 工程地质
Abstract: The complex geological structure in the southwest mountainous area leads to the distribution of many landslides. Early landslide identification is essential to guide road route selection scientifically and effectively and avoid the high risk of geological disaster in advance. Interferometry Synthetic Aperture Radar (InSAR) is widely used in the early identification of landslides due to its all-weather and multi-temporal characteristics. In this paper, 87 sentinel-1A orbital descent data are collected. The small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) is used to identify and analyze the potential landslide hazard in the Wenchuan section of Chengwen expressway. 10 deformation areas were identified through the SBAS-InSAR, which after field validation are landslides under continuous deformation. This conclusion corresponds to the actual case. Based on early identification results, three schemes are compared and analyzed, and scheme B is optimal. SBAS-InSAR can effectively identify potential landslide hazard areas of mountain roads and provide scientific support for accurate route selection of mountain expressways. -
图 2 影像采集时间与空间相对位置
Fig. 2. The relative position of time and space of image acquisition
图 4 研究区时序InSAR形变分布及野外复核照片
Fig. 4. InSAR deformation distribution and field validation in the study area
图 5 月里村滑坡年平均形变速率与野外复核照片
a.SBAS-InSAR形变测量结果；b.控制点野外复核
Fig. 5. The annual average deformation and field validation of potential landslide in the Yueli Village
图 6 月里村滑坡视线向累计形变曲线
Fig. 6. Cumulative LOS displacements of potential landslide in the Yueli Village
图 7 布瓦村滑坡年平均形变速率与野外复核照片
a.SBAS-InSAR形变测量结果；b.控制点野外复核
Fig. 7. The annual average deformation and field validation of potential landslide in the Buwa Village
图 8 布瓦村滑坡视线向累计形变曲线
Fig. 8. Cumulative LOS displacements of potential landslide in the Buwa Village
图 9 滑坡易发区选线设计方案
Fig. 9. Design scheme of route selection for high susceptibility of landslide area
表 1 研究区SAR数据参数
Table 1. SAR data parameters in the study area
轨道方向 成像模式 波段 波长(cm) 地面分
辨率(m)重访周期(d) 视角(°) 极化方式 降轨 IW C 5.6 5×20 12 39 VV 
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表 2 基于InSAR技术识别的滑坡隐患基本特征信息
Table 2. Basic characteristics of potential landslides detected by InSAR
滑坡隐患编号 滑坡名称 经度 纬度 规模类型 滑坡方量(104 m3) 最大累计形变量(mm) H1 通山村滑坡 103°38′55.69″ 31°27′18.55″ 大型土质滑坡 483.44 -125.13 H2 萝卜寨滑坡 103°40′02.64″ 31°30′16.14″ 特大型岩质滑坡 1 304.70 -98.454 H3 索桥村滑坡 103°39′06.88″ 31°29′28.41″ 特大型岩质滑坡 982.68 -115.38 H4 月里村滑坡 103°38′04.41″ 31°28′16.24″ 特大型岩质滑坡 3 641.67 -146.95 H5 月里村北侧滑坡 103°37′56.05″ 31°28′40.74″ 大型岩质滑坡 840.80 -89.64 H6 白水村滑坡 103°37′17.37″ 31°28′13.55″ 大型岩质滑坡 329.12 90.62 H7 秉里村滑坡 103°36′41.48″ 31°28′37.77″ 大型土质滑坡 613.43 -258.54 H8 磨村滑坡 103°35′46.77″ 31°31′00.05″ 特大型岩质滑坡 1 741.58 -178.52 H9 布瓦村滑坡 103°35′29.15″ 31°29′37.59″ 特大型岩质滑坡 4 412.04 -285.24 H10 小克枯滑坡 103°34′30.47″ 31°31′06.42″ 特大型岩质滑坡 1 317.93 -231.87
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