一种基于多源遥感的滑坡防灾技术框架及其工程应用

李振洪; 张成龙; 陈博; 占洁伟; 丁明涛; 吕艳; 李鑫泷; 彭建兵

doi:10.3799/dqkx.2022.205

Volume 47 Issue 6

Jun. 2022

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Li Zhenhong, Zhang Chenglong, Chen Bo, Zhan Jiewei, Ding Mingtao, Lü Yan, Li Xinlong, Peng Jianbing, 2022. A Technical Framework of Landslide Prevention Based on Multi-Source Remote Sensing and Its Engineering Application. Earth Science, 47(6): 1901-1916. doi: 10.3799/dqkx.2022.205

Citation:

Li Zhenhong, Zhang Chenglong, Chen Bo, Zhan Jiewei, Ding Mingtao, Lü Yan, Li Xinlong, Peng Jianbing, 2022. A Technical Framework of Landslide Prevention Based on Multi-Source Remote Sensing and Its Engineering Application. Earth Science, 47(6): 1901-1916. doi: 10.3799/dqkx.2022.205

Citation:

Li Zhenhong, Zhang Chenglong, Chen Bo, Zhan Jiewei, Ding Mingtao, Lü Yan, Li Xinlong, Peng Jianbing, 2022. A Technical Framework of Landslide Prevention Based on Multi-Source Remote Sensing and Its Engineering Application. Earth Science, 47(6): 1901-1916. doi: 10.3799/dqkx.2022.205

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A Technical Framework of Landslide Prevention Based on Multi-Source Remote Sensing and Its Engineering Application

doi: 10.3799/dqkx.2022.205

Li Zhenhong^{1, 2, 3
,
,},
Zhang Chenglong^{1, 2},
Chen Bo^{1, 2},
Zhan Jiewei^{1, 3},
Ding Mingtao^{1, 2, 3
,
,
,},
Lü Yan^{1, 3},
Li Xinlong^{1, 2},
Peng Jianbing^{1, 3}

1.
College of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China
2.
Big Data Center for Geosciences and Satellites, Chang'an University, Xi'an 710054, China
3.
Key Laboratory of Western China's Mineral Resource and Geological Engineering, Ministry of Education, Xi'an 710054, China

Received Date: 2022-06-08
Publish Date: 2022-06-25

Abstract

Abstract

China is one of the countries worst affected by landslides in the world, and great efforts have been made to detect potential landslides over wide regions. However, a recent government work report shows that 80% of the newly formed landslides occurred outside the areas labelled as potential landslides, and 80% of them occurred in remote rural areas with limited capability of disaster prevention and mitigation. To address this dilemma, there are urgent needs to (1) identify feasible detection techniques for each landslide type so as to minimize (if not avoid) the missing detection problem, and (2) engage local communities for landslide prevention to help landslide detection and risk assessment. To take full advantage of multi-source remote sensing data and technology, the potential landslides are divided into four types in this paper: actively deforming slopes, reactivated historically deformed slopes, stabilized historically deformed slopes, and undeformed but potentially unstable slopes. Furthermore, a multi-source remote sensing integrated technical framework is presented for landslide prevention, namely "wide-area potential landslide detection-risk assessment for individual potential landslides-community-based disaster prevention". In this study, a key section of the Qinghai-Tibet Plateau Transportation Project (QTPTP) with an area of about 10 000 km² was taken as the research area; collaborating with the local communities including some design and construction units of the QTPTP, it successfully identified 263 potential landslides, among which 249 were actively deforming slopes, 5 reactivated historically deformed slopes and 9 stabilized historically deformed slope. In addition, quantitative risk assessment and community-based disaster prevention were carried out for three typical potential landslides. It is believed that the multi-source remote sensing technical framework will not only help local communities improve their capability in landslide prevention, but also directly benefit to the construction and operation of the QTPTP.
- potential landslide,
- landslide type,
- landslide detection,
- risk assessment,
- community-based disaster prevention

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References(87)

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