Seasonal surface displacement and highway embankment grade derived from InSAR and LiDAR, Highway 3 west of Yellowknife, Northwest Territories
Bibliographic record
Abstract
Monitoring highway conditions is critical to effectively maintain northern infrastructure within discontinuous permafrost environments. This Open File presents seasonal surface displacement and embankment grade calculated for a 48 km section of Highway 3 (km marker 282 to 330), located to the west of Yellowknife. Satellite interferometric synthetic aperture radar (InSAR) was used to calculate relative surface displacement from May to September of 2010 along the highway corridor. Airborne light detection and ranging (LiDAR) data acquired on August 22 and 24, 2010 were also used to measure road elevations, calculate embankment grade and map raised ice-rich clay terrain. The highway embankment was determined to be seasonally stable over 67% (31.2 linear km) of the 48 linear kilometres analyzed, which corresponds to sections where bedrock is exposed or covered by a thin veneer of sediment. Low downward displacement (-1 to -3 cm) was calculated over 20% (9.3 linear km) and moderate downward displacement (-3 to -6 cm) over 2% (1.0 linear km) of the highway. Downward displacement is attributed to subsidence that occurs across forested clay and peatland terrain. Over an additional 11% (4.9 linear km) of the highway, displacement was not measured due to incoherence between repeat satellite observations. Incoherence over the highway is primarily attributed to the smooth surface of the roadway that produces very low radar return (i.e. low signal strength). At one location where the highway crosses the former location of an ice-rich clay ridge, the embankment has subsided by 95 cm over a 4-5 year period following construction. Embankment side slopes were determined to be steeper than recommended grade along some sections where highway instability exists. LiDAR intensity is also shown to be successful for mapping wet terrain that may thermally impact permafrost. The derived data products accompanying this Open File are presented in the form of graphical representations and digital geotiff and shapefiles compatible with ArcGIS. The datasets demonstrate the ability to remotely monitor several aspects of highway infrastructure located within the discontinuous permafrost zone and to identify sections of the highway that may require future remediation and adaption measures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".