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中巴经济走廊洪扎段潜在滑坡SBAS-InSAR早期识别及发育特征分析

Potential landslides identification and development characteristics analysis in Hunza valley, along China-Pakistan Economic Corridor based on SBAS-InSAR

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【作者】 苏晓军张毅孟兴民Rehman Mohib UrKhalid Zainab赵富萌岳东霞郭富赟周自强

【Author】 SU Xiaojun;ZHANG Yi;MENG Xingmin;REHMAN Mohib Ur;KHALID Zainab;ZHAO Fumeng;YUE Dongxia;GUO Fuyun;ZHOU Ziqiang;College of Earth and Environmental Sciences, Lanzhou University;Technology & Innovation Centre for Environmental Geology and Geohazards Prevention;Key Laboratory of Western China’s Environmental Systems (Ministry of Education);School of Earth Sciences, Lanzhou University;Geological Environment Monitoring Institute of Gansu Province;Institute of Geological Hazards Prevention, Gansu Academy of Sciences;

【通讯作者】 张毅;

【机构】 兰州大学资源环境学院甘肃省环境地质与灾害防治技术创新中心兰州大学西部环境教育部重点实验室兰州大学地质科学与矿产资源学院甘肃省地质环境监测院甘肃省科学院地质自然灾害防治研究所

【摘要】 中巴经济走廊巴基斯坦境内洪扎河谷(Hunza Valley)段地形高差巨大、地质环境复杂,滑坡灾害多发,对河谷内村镇威胁极大,也严重制约中巴经济走廊安全建设与运行。为了加深对Hunza河谷滑坡灾害的认识,亟待进行滑坡识别编目和发育特征研究。本研究基于升、降轨获取的87景哨兵一号(Sentinel-1)数据,利用SBAS-InSAR技术获取了洪扎河谷地表形变,计算了地表斜坡向形变速率。并综合利用光学遥感影像解译和野外实地调查验证,成功识别了洪扎河谷53处潜在滑坡,并讨论了滑坡识别效果,对Ghulmet和Humarri两个典型大型滑坡监测形变、影像解译和验证特征进行了分析。在此基础上,选取11个地形地质环境因素作为影响滑坡发育的因子,分析了滑坡分布发育特征。结果表明,升轨和降轨数据监测到研究区内斜坡向最大形变速率分别为-311 mm/a和-490 mm/a,洪扎河谷区不稳定形变阈值为-20 mm/a。大型滑坡受河流侵蚀作用,形变剧烈,次级滑坡发育。识别的潜在滑坡主要集中在河流两岸、公路上下边坡;潜在滑坡主要分布在风化堆积层以及千枚岩、板岩等变质岩区;高差200—1000 m、坡度30°—40°和坡向南、南西向为滑坡发育的优势地形条件;斜坡地表裸露、植被稀疏地段(NDVI<0.2)物源充足,滑坡较为发育。研究结果可用于巴基斯坦洪扎河谷防灾减灾工作,保障中巴经济走廊畅通运营,为具有毁路与堵江风险的滑坡重点监测和评价研究提供科学参考和数据支持。

【Abstract】 The Hunza Valley in the China–Pakistan Economic Corridor(CPEC) in the northern part of Pakistan has a high relief and harsh geo-environment. Villages and towns in this area are prone to geohazard development, and high-risk incidents have been observed from the construction to operation stages of the CPEC. Landslide hazards in the Hunza Valley must be investigated and analyzed via landslide inventories and landslide development tools. This study applied 45 images and 42 images from the ascending and descending Sentinel-1A datasets, respectively, to monitor surface deformation via SBAS-InSAR. The deformation information along the slope direction was subsequently estimated. On the basis of the displacement rates derived from the SAR data, the optical remote sensing images were visually interpreted, and in situ surveys and validations were conducted. A total of 53 potential landslides were detected and delineated. On the basis of the effects of landslide identification and the detected deformation, image interpretation and validation features of typical large landslides Ghulmet and Humarri, 11 factors related to geomorphology, geology, hydrology, and vegetation were analyzed for landslide development.Maximum displacement velocities of-311 and-490 mm/a along the slope were detected on the basis of the ascending and descending datasets, respectively. Consequently, an annual deformation velocity of 20 mm/a was set as the threshold for the detection and mapping of potential landslides in the Hunza River Valley. The deformation of large landslides is severe under the influence of Hunza River erosion, and secondary landslides are developed. The validated potential landslides are distributed on the slopes on both sides of the Hunza River and are sometimes on the upper and lower slopes of the road. These active landslides primarily are developed in metamorphic rocks such as phyllite and slate. In the CPEC, landslides preferentially form and deform in areas where the elevation relief is between 200 and 1000 m, the slope is between 30° and 40°, and the aspect is within the southern and southwestern regions. Given the bare area of slope surfaces and sparse vegetation(NDVI<0.2), weathered and fragmented slopes provide enough provenance and materials for landslide development. The outcomes and results may facilitate hazard management and risk reduction in the Hunza Valley, allowing the operation of the CPEC to be uninterrupted. The findings of this work can also provide scientific references and data support for the monitoring and assessments of major landslide disasters that destroy roads and block rivers and their resulting secondary disaster events.

【基金】 国家重点研发计划(编号:2017YFC1501005);甘肃省科技计划(编号:18YF1WA114);甘肃省科技重大专项(编号:19ZD2FA002);兰州大学中央高校基本科研业务费专项资金(编号:lzujbky-2021-ey05)~~
  • 【文献出处】 遥感学报 ,National Remote Sensing Bulletin , 编辑部邮箱 ,2024年04期
  • 【分类号】P237;P642.22
  • 【下载频次】182
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