Monitoring Slope Creep Motion using Multi Temporal Interferometry Synthetic Aperture Radar in Semarang, Indonesia

Landslide is one type of slope movement, where the slope movement includes creep. Although creep movement does not have an impact on the risk of loss of life, this creep movement takes place constantly and invisible which has an impact on economic losses. In this study, a time-series monitoring was carried out from 2018 to 2020 to see the movement of the slopes in the study area using the Multi-Temporal Interferometry Synthetic Aperture Radar (MTInSAR). A time series method from Sentinel 1A/B data, which includes Trangkil Sejahtera Housing (PTS), Soegijapranata Catholic University (UNIKA), and 17 August 1945 University (UNTAG) in Semarang City, Indonesia. The results of data processing indicate that there are slope movement in the target location, namely Trangkil Sejahtera and Selorejo Housing (southwest of UNIKA). Based on BPBD 2021 data, landslides occurred in the Trangkil Baru Housing Center (to the north of PTS) and the Garang River landslide channel west of Selorejo. This shows that there is a link between crawling in 2018-2020 and landslides in 2021. Although the use of satellite data has some drawbacks, the results can be taken into consideration in building an early warning system and reducing losses due to landslides.

Assessment of landslide behaviour in colluvium deposit at Doi Chang, Thailand

The paper presents the case study of the recurrent slope movement in colluvium deposits at Doi Chang, Thailand. A thorough site investigation confirmed the slope movement rate corresponding to slow creep during dry season, while in the rainy season, its velocity remarkably increased. Despite frequent repair, the movement rate was sufficient to result in the recurrent damage of infrastructures like roads and buildings, causing economic loss and public concerns. Furthermore, surface mapping revealed that the hill's topography led to the concentration of flowing water in a particular area. This resulted in a high level of groundwater table, especially during the rainy season. The inclinometer installed in that area suggested an average movement rate of 20.5 mm/month in the wet season. In contrast, during the dry season, it was limited within 2 mm/month, indicating that the increase in the rate of slope movement in the colluvium deposit was primarily due to the rising groundwater table. Field and laboratory tests were conducted to determine the properties of the colluvium deposit. Landslide susceptibility assessment was performed using infinite slope model and later integrated with GIS to evaluate the factor of safety (FS) over a large area. The FS decreased below 1 when the groundwater level rose to 0.3 cm below the ground surface, and using GIS, based on infinite slope model, the potential risk zone were delineated.

Seismic behavior of pile group in soil slope

Seismic behavior of pile group in slope is interested for many years by researchers .Inthis research Shaking table tests were conducted by means of a rigid-box with 1.8m in length,0.8 in width and 1.2 in height in order to investigate the effects of the location of pile group insand slope on its seismic behavior .A cap supported by a pile group was set in a dry sandslope, and subjected to sinusoidal base motion with constant frequency. Soil used in this studywas firoozkuh sand 161 with 60% relative density. The tests were scaled at 1/10th and the pileswere made from aluminum with 95cm in length and they have fixed head condition.Discussions are focused on the behavior of pile groups in different situations. Main interestsare recognition the effect of slope movement and location of pile group on bending behaviorof piles.

Low-Cost Automatic Slope Monitoring Using Vector Tracking Analyses on Live-Streamed Time-Lapse Imagery

Identifying precursor events that allow the timely forecasting of landslides, thereby enabling risk reduction, is inherently difficult. Here we present a novel, low cost, flow visualization technique using time-lapsed imagery (TLI) that allows real time analysis of slope movement. This approach is applied to the Rest and Be Thankful slope, Argyle, Scotland, where past debris flows have blocked the A83 or forced preemptive closure. TLI of the Rest and Be Thankful are taken from a fixed station, 28 mm lens, time lapse camera every 15 min. Imagery is filtered to counter the effects of misalignment from wind induced vibration of the camera, asymmetric lighting, and fog. Particle image velocimetry (PIV) algorithms are then run to produce slope movement velocity vectors. PIV generated vectors are automatically post-processed to separate vectors generated by slope movement from false positives generated by harsh environmental conditions. Results for images over a 20-day period indicated precursor slope movement initiated by a rainfall event, a period of quiescence for 10 days, followed by a large landslide failure during proceeding rainfall where over 3000 tons of sediment reached the road. Results suggest low cost, live streamed TLI and this novel PIV approach correctly detect and, importantly, report precursor slope movement, allowing early warning, effective management and landslide impact mitigation. Future applications of this technique will allow the development of an effective decision-making tool for asset management of the A83, reducing the risk to life of motorists. The technique can also be applied to other critical infrastructure sites, allowing hazard risk reduction.

Detecting precursors of an imminent landslide along the Jinsha River

Landslides are major hazards that may pose serious threats to mountain communities. Even landslides in remote mountains could have non-negligible impacts on populous regions by blocking large rivers and forming dam-breached mega floods. Usually, there are slope deformations before major landslides occur, and detecting precursors such as slope movement before major landslides is important for preventing possible disasters. In this work, we applied multi-temporal optical remote sensing images (Landsat 7 and Sentinel-2) and an image correlation method to detect subpixel slope deformations of a slope near the town of Mindu in the Tibet Autonomous Region. This slope is located on the right bank of the Jinsha River, ∼80 km downstream from the famous Baige landslide. We used a DEM-derived aspect to restrain background noise in image correlation results. We found the slope remained stable from November 2015 to November 2018 and moved significantly from November 2018. We used more data to analyse slope movement in 2019 and found retrogressive slope movements with increasingly large deformations near the riverbank. We also analysed spatial–temporal patterns of the slope deformation from October 2018 to February 2020 and found seasonal variations in slope deformations. Only the foot of the slope moved in dry seasons, whereas the entire slope was activated in rainy seasons. Until 24 August 2019, the size of the slope with displacements larger than 3 m was similar to that of the Baige landslide. However, the river width at the foot of this slope is much narrower than the river width at the foot of the Baige landslide. We speculate it may continue to slide down and threaten the Jinsha River. Further modelling works should be carried out to check if the imminent landslide could dam the Jinsha River and measures should be taken to mitigate possible dam breach flood disasters. This work illustrates the potential of using optical remote sensing to monitor slope deformations over remote mountain regions.