Application of ground-based InSAR for rock slope monitoring and site assessment at the Checkerboard Creek Rock Slope
Bibliographic record
Abstract
In recent years ground-based, interferometric, synthetic aperture radar (GB-InSAR) has been successfully implemented for purposes of monitoring displacements of both natural and man-made slopes. GB-InSAR monitoring has also provided detailed, spatially continuous, and high temporal frequency datasets that can be analyzed to provide further insights into key aspects of slope movements including its deformation mechanism(s), spatial extents of landslide activity, and other aspects of landslide kinematics. However, despite these capabilities, this technology has seen limited use within North America and Canada outside of the mining industry due to a variety of factors ranging from associated equipment costs, perceived technical limitations, and unfamiliarity of geoscience and engineering professionals with resulting data, analysis and interpretation. Therefore, to test the applicability of this technology on natural slopes with conditions that are typical to many landslide sites in North America and Canada which include features such as dense vegetation cover, mountainous terrain, deep seasonal snowpack, and inclement weather, it has been applied at a known 2 to 3 million m3 bedrock landslide site with a very slow-average displacement rate (~10 mm/y) known as The Checkerboard Creek Rock Slope located near Revelstoke, BC, Canada. To assess GB-InSAR’s ability to monitor this site and to quantify its potential advantages over traditional geotechnical monitoring techniques and other remote sensing technologies (such as satellite-based InSAR, LiDAR, GNSS, and UAV photogrammetry) resulting temporally discontinuous datasets have been analysed and validated, compared, and contrasted against historical in-place instrumentation data. Additionally, identification and mitigation of the logistical challenges and technical limitations associated with the initial installation of the GB-InSAR equipment at the Checkerboard Creek Rock Slope and site conditions were completed as part of this research which included the expansion of the solar power system, installation of telecommunications equipment for remote access to operating software and collected data, and improvement of the coverage and quality of the GB-InSAR data by means of installation of corner point reflectors, new radar antennas, and shelter window. An analysis of the key limitation of GB-InSAR and other similar technologies due to vegetation and snow ground cover was completed as part of this research and concluded that compensating for apparent movements from snow accumulation and melt can be successfully implemented by making resulting discontinuously processed InSAR displacements relative to a known stable area. However, GB-InSAR results in areas of dense vegetation remain unreliable, therefore, analysis of future data collected with the system improvements made at site such as corner point reflectors is recommended to further evaluate this limitation of the application of this technology at natural slope landslide site. GB-InSAR monitoring equipment at this site was also used to develop new insights into multiple aspects of the Checkerboard Creek Rock Slope. These insights included further confirmation of the currently understood deformation mechanism of complex rotational toppling, in addition to an updated understanding of slope deformation characteristics such as refinement of the northern extent of the active zone of movement, indication that the seasonal pattern in displacement rates recorded by near-surface in-place instruments may be at least partially due to thermal effects on the instruments themselves rather than due to real ground movements, and possible identification of new previously unidentified areas of potential slope movement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".