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基于 Sentinel-1 多时相 InSAR 的四川大渡河滑坡监测。

Landslide Monitoring along the Dadu River in Sichuan Based on Sentinel-1 Multi-Temporal InSAR.

机构信息

College of Water Resource and Hydropower, Sichuan University, Chengdu 610065, China.

Guoneng Dadu River Hydropower Co., Ltd., Chengdu 610093, China.

出版信息

Sensors (Basel). 2023 Mar 23;23(7):3383. doi: 10.3390/s23073383.

Abstract

The Dadu River travels in the mountainous areas of southwestern China, one of regions with the most hazards that has long suffered from frequent geohazards. The early identification of landslides in this region is urgently needed, especially after the recent Luding earthquake (MS 6.8). While conventional ground-based monitoring techniques are limited by the complex terrain conditions in these alpine valley regions, space interferometric synthetic aperture radar (InSAR) provides an incomparable advantage in obtaining surface deformation with high precision and over a wide area, which is very useful for long-term and slow geohazard monitoring. In this study, more than 500 Sentinel-1 SAR images with four frames acquired during 2017~2022 were collected to detect the hidden landslide regions from the Jinchuan to Ebian Section along the Dadu River, based on joint-scatterer InSAR (JS-InSAR) and small baseline subset (SBAS) techniques. The results showed that our method could be successfully applied for landslide monitoring in complex mountainous regions. Furthermore, 143 potential landslide regions spreading over an 800 km area along the Dadu River were extracted by integrating the deformation measurements and optical images. Our study can provide a reference for large-scale geological hazard surveys in mountainous areas, and the InSAR technique will be encouraged for the local government in future long-term monitoring applications in the Dadu River Basin.

摘要

大渡河穿行于中国西南部的山区,该地区是灾害多发区之一,长期以来一直深受地质灾害的困扰。因此,急需对该地区的滑坡进行早期识别,尤其是在最近的泸定地震(MS6.8)之后。虽然传统的地面监测技术受到这些高山峡谷地区复杂地形条件的限制,但星载干涉合成孔径雷达(InSAR)技术在获取高精度、大面积地表形变方面具有无与伦比的优势,非常适用于长期、缓慢的地质灾害监测。在这项研究中,我们利用 2017 年至 2022 年期间获取的超过 500 景 Sentinel-1 SAR 四轨图像,基于联合散射体 InSAR(JS-InSAR)和小基线集(SBAS)技术,对大渡河金川县至埃比安段进行了隐伏滑坡区的探测。结果表明,该方法可以成功应用于复杂山区的滑坡监测。此外,通过整合变形测量和光学图像,我们在大渡河流域 800 公里范围内提取了 143 个潜在的滑坡区。本研究可为山区大规模地质灾害调查提供参考,InSAR 技术将鼓励大渡河流域地方政府在未来进行长期监测应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ef6/10099090/fafcf454cbbb/sensors-23-03383-g001.jpg

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