A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Locating and characterizing potential rainfall-induced landslides on a regional scale based on SBAS-InSAR technique
https://orcid.org/0000-0002-4609-9945
Abstract Locating potential landslides accurately is vital for developing mitigation strategies in advance to avoid catastrophic damages. This task typically requires intensive human efforts in detecting or monitoring the deformation or pore water pressure at various points of a slope, which is difficult to cover slopes over a wide area on a regional scale. This study investigates the potential of integrating small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique into rainfall-induced slope movement characterization, with the goal of locating potential landslides accurately on a regional scale. The surface deformation of the slopes is first obtained using SBAS-InSAR technique, through which the soils with large downwards deformation that is prone to separate with the stable slope soils can be identified. Then, an index of separating trend is proposed to quantify the degree of separation, which is further used to characterize the potential landslides. The locations of potential landslides are then identified through the trend of separation. The proposed method is verified on 14 slopes in Shenzhen, China. The analysis on a mountain area of 4 km × 2 km in Shenzhen identified 2 potential landslides in May 2018 which collapsed after a heavy rainfall in August 2018. A separating trend keeping lower than 0.5 for at least 3 months is a reliable criterion to identify potential rainfall-induced landslides. A limitation of this study is that the proposed method cannot be used to identify the landslides caused by earthquakes and human activities. This study provides a quantified method to locate the potential landslides over a wide slope area rigorously, paving the way for a more cost-effective landslide mitigation strategy.
Locating and characterizing potential rainfall-induced landslides on a regional scale based on SBAS-InSAR technique
https://orcid.org/0000-0002-4609-9945
Abstract Locating potential landslides accurately is vital for developing mitigation strategies in advance to avoid catastrophic damages. This task typically requires intensive human efforts in detecting or monitoring the deformation or pore water pressure at various points of a slope, which is difficult to cover slopes over a wide area on a regional scale. This study investigates the potential of integrating small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique into rainfall-induced slope movement characterization, with the goal of locating potential landslides accurately on a regional scale. The surface deformation of the slopes is first obtained using SBAS-InSAR technique, through which the soils with large downwards deformation that is prone to separate with the stable slope soils can be identified. Then, an index of separating trend is proposed to quantify the degree of separation, which is further used to characterize the potential landslides. The locations of potential landslides are then identified through the trend of separation. The proposed method is verified on 14 slopes in Shenzhen, China. The analysis on a mountain area of 4 km × 2 km in Shenzhen identified 2 potential landslides in May 2018 which collapsed after a heavy rainfall in August 2018. A separating trend keeping lower than 0.5 for at least 3 months is a reliable criterion to identify potential rainfall-induced landslides. A limitation of this study is that the proposed method cannot be used to identify the landslides caused by earthquakes and human activities. This study provides a quantified method to locate the potential landslides over a wide slope area rigorously, paving the way for a more cost-effective landslide mitigation strategy.
Locating and characterizing potential rainfall-induced landslides on a regional scale based on SBAS-InSAR technique
https://orcid.org/0000-0002-4609-9945
Abstract Locating potential landslides accurately is vital for developing mitigation strategies in advance to avoid catastrophic damages. This task typically requires intensive human efforts in detecting or monitoring the deformation or pore water pressure at various points of a slope, which is difficult to cover slopes over a wide area on a regional scale. This study investigates the potential of integrating small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique into rainfall-induced slope movement characterization, with the goal of locating potential landslides accurately on a regional scale. The surface deformation of the slopes is first obtained using SBAS-InSAR technique, through which the soils with large downwards deformation that is prone to separate with the stable slope soils can be identified. Then, an index of separating trend is proposed to quantify the degree of separation, which is further used to characterize the potential landslides. The locations of potential landslides are then identified through the trend of separation. The proposed method is verified on 14 slopes in Shenzhen, China. The analysis on a mountain area of 4 km × 2 km in Shenzhen identified 2 potential landslides in May 2018 which collapsed after a heavy rainfall in August 2018. A separating trend keeping lower than 0.5 for at least 3 months is a reliable criterion to identify potential rainfall-induced landslides. A limitation of this study is that the proposed method cannot be used to identify the landslides caused by earthquakes and human activities. This study provides a quantified method to locate the potential landslides over a wide slope area rigorously, paving the way for a more cost-effective landslide mitigation strategy.
Locating and characterizing potential rainfall-induced landslides on a regional scale based on SBAS-InSAR technique
Li, Jinhui (author) / Xing, Xinfu (author) / Ou, Jinping (author)
2023
Article (Journal)
Electronic Resource
English
BKL:
56.00$jBauwesen: Allgemeines
/
38.58
Geomechanik
/
38.58$jGeomechanik
/
56.20
Ingenieurgeologie, Bodenmechanik
/
56.00
Bauwesen: Allgemeines
/
56.20$jIngenieurgeologie$jBodenmechanik
RVK:
ELIB18
Detection and Monitoring of Potential Geological Disaster Using SBAS-InSAR Technology
| Springer Verlag | 2023
Modelling rainfall-induced landslides at a regional scale, a machine learning based approach
| Springer Verlag | 2023
Deformation monitoring of long-span railway bridges based on SBAS-InSAR technology
| DOAJ | 2024
Rainfall Induced Landslides—A Review
| Springer Verlag | 2022