3:45 PM - 4:00 PM
[HDS10-07] Monitoring of land surface changes caused by slope failure with SAR satellite data
Keywords:PS-InSAR, SBAS-InSAR, slope faliure, land surface changes, ALOS-2/PALSAR-2
In recent years, landslide disasters have frequently occurred worldwide due to climate change and other factors. Sediment disasters always affect social and economic development and restrict the sustainable development of society. Therefore, it is crucial to study the methods of disaster prevention and management in areas with high sediment hazard occurrence. However, obtaining large-scale information through field surveys is extremely difficult regarding workforce, time, and risk. Therefore, making full use of excellent satellite remote sensing technology, such as wide area, periodicity, and all-weather, in landslide disasters is of great interest. The limitations of optical satellites are that they cannot imagine the Earth's surface through clouds and cannot be observed without sunlight. Unlike optical satellite images, SAR satellites can observe the surface regardless of weather, day or night, and can observe a wide area at a time. Time series data can be acquired at regular intervals.
Slope failure is a process of geomorphological changes caused by geophysical and meteorological factors, including heavy or prolonged rainfall, earthquakes, and other hazards. Slope failure frequently occur in mountainous areas and are dangerous mass movements. It can also have immediate and long-term physical impacts on critical infrastructure such as roads, bridges, and human settlements. It can seriously affect local infrastructure development and land use management. For disaster preparedness and to reduce losses in the event of a disaster, it is vital to understand the changes in the large-scale ground surface.
Due to its mountainous location and subtropical monsoon climate, Japan receives much heavy rain in summer, and in recent years, landslides have also often occurred due to heavy rainfall disasters. From July 5 to 6, 2017, the Kitakyushu region of Japan was hit by an exceptionally heavy rainfall disaster, with 829 mm of rainfall in 24 hours in Asakura, Fukuoka Prefecture, which is located at the center of the disaster. During this disaster, a large amount of sediment and driftwood was swept away by the floodwater due to the destabilization of the slopes. Many houses were damaged as the sediment and driftwood flooded into rivers. Thus, slope failure became one of the major disasters caused by this heavy rain.
Understanding the spatial and temporal variability of slope failure is important for hazard assessment and risk management of hazards, as well as for the definition and implementation of effective disaster prevention. Time series and long-term ground displacement measurements associated with slope failure allow us to investigate the history of slope deformation and identify effective prevention and mitigation measures. Therefore, we will use SAR satellite data to perform a time series analysis of areas where slope failure has occurred, monitor ground movements, and examine the pre-disaster conditions of subtle ground movements. In this way, the slopes where slope failure may occur are identified.
InSAR (Interferometric SAR) is a method to estimate the amount of fluctuation based on the phase difference between two satellite data. Based on the InSAR interferometric analysis, PS-InSAR (Persistent Scatterer InSAR) and SBAS-InSAR (Small Baseline Subset InSAR) analysis methods are proposed, which are time series analysis methods for monitoring small ground deformations. PS and SBAS effectively improve the accuracy of InSAR analysis.
The study area for this study was a 10 km2 area within Fukuoka Prefecture, which suffered from the Kitakyushu rainstorm disaster. We collected ALOS-2 data in the study area from March 2017 to March 2020 and analyzed PS-InSAR and SBAS-InSAR. A typical feature of slope failure is that its displacement occurs vertically and horizontally, while InSAR interferometry can only measure one-dimensional (1-D) displacements along the line of sight (LOS) direction. In addition, due to the characteristics of the satellite observation method, there are unobservable regions in the satellite data. However, the analyzable area may be increased considering satellite data with different orbits, observation directions, and observation angles. Therefore, after analyzing the results of ALOS-2, in this study, we will analyze the satellite data of sentinel-1 to monitor the surface changes caused by slope failure.
Slope failure is a process of geomorphological changes caused by geophysical and meteorological factors, including heavy or prolonged rainfall, earthquakes, and other hazards. Slope failure frequently occur in mountainous areas and are dangerous mass movements. It can also have immediate and long-term physical impacts on critical infrastructure such as roads, bridges, and human settlements. It can seriously affect local infrastructure development and land use management. For disaster preparedness and to reduce losses in the event of a disaster, it is vital to understand the changes in the large-scale ground surface.
Due to its mountainous location and subtropical monsoon climate, Japan receives much heavy rain in summer, and in recent years, landslides have also often occurred due to heavy rainfall disasters. From July 5 to 6, 2017, the Kitakyushu region of Japan was hit by an exceptionally heavy rainfall disaster, with 829 mm of rainfall in 24 hours in Asakura, Fukuoka Prefecture, which is located at the center of the disaster. During this disaster, a large amount of sediment and driftwood was swept away by the floodwater due to the destabilization of the slopes. Many houses were damaged as the sediment and driftwood flooded into rivers. Thus, slope failure became one of the major disasters caused by this heavy rain.
Understanding the spatial and temporal variability of slope failure is important for hazard assessment and risk management of hazards, as well as for the definition and implementation of effective disaster prevention. Time series and long-term ground displacement measurements associated with slope failure allow us to investigate the history of slope deformation and identify effective prevention and mitigation measures. Therefore, we will use SAR satellite data to perform a time series analysis of areas where slope failure has occurred, monitor ground movements, and examine the pre-disaster conditions of subtle ground movements. In this way, the slopes where slope failure may occur are identified.
InSAR (Interferometric SAR) is a method to estimate the amount of fluctuation based on the phase difference between two satellite data. Based on the InSAR interferometric analysis, PS-InSAR (Persistent Scatterer InSAR) and SBAS-InSAR (Small Baseline Subset InSAR) analysis methods are proposed, which are time series analysis methods for monitoring small ground deformations. PS and SBAS effectively improve the accuracy of InSAR analysis.
The study area for this study was a 10 km2 area within Fukuoka Prefecture, which suffered from the Kitakyushu rainstorm disaster. We collected ALOS-2 data in the study area from March 2017 to March 2020 and analyzed PS-InSAR and SBAS-InSAR. A typical feature of slope failure is that its displacement occurs vertically and horizontally, while InSAR interferometry can only measure one-dimensional (1-D) displacements along the line of sight (LOS) direction. In addition, due to the characteristics of the satellite observation method, there are unobservable regions in the satellite data. However, the analyzable area may be increased considering satellite data with different orbits, observation directions, and observation angles. Therefore, after analyzing the results of ALOS-2, in this study, we will analyze the satellite data of sentinel-1 to monitor the surface changes caused by slope failure.