SATELLITE MONITORING OF TRANSPORTATION INFRASTRUCTURE
Bibliographic record
Abstract
Harsh weather conditions caused by climate change and increased traffic loads can accelerate the aging process of core public infrastructure. Conventional condition assessment methods primarily rely on visual inspections conducted years apart, making it difficult to detect subtle, ongoing changes in performance resulting from structural deterioration. Consequently, engineers may be unable to initiate early countermeasures to prevent service disruption or structural failure. In response, public infrastructure owners are actively seeking innovative solutions that can help maintain high levels of user safety, reduce service disruption, extend the service life of infrastructure, and lower overall life-cycle costs. To this end, the National Research Council Canada, Transport Canada, and Infrastructure Canada have collaborated for several years to adapt, further develop and validate space-based earth observation technology for monitoring key public infrastructure, including bridges and, more recently, marine ports and airports. Case studies on runways of the Vancouver International Airport and wharves of the Vancouver Fraser Port have been conducted to validate remote satellite observations with in-situ surveying subsidence measurements. Satellite image interferometry allows the mapping of displacement by determining the signal phase change within pairs of co-registered pixels from two radar images of the same target taken at different times. The result is a line-of-sight (LOS) displacement measurement that can be used to remotely assess uplift, subsidence, and horizontal motion taking place over time. Since it is a 1D measurement taken at an angle from the zenith, the vertical and horizontal components are unknown a priory. Thus, attempting to validate satellite LOS measurements with in-situ surveying vertical measurements can be challenging since one has to make valid assumptions about the horizontal movements of the ground targets being measured – in our case, the riding surface of the airport runways or the port wharves. This paper compares satellitemeasured displacements and field survey measurements at selected locations and discusses challenges associated with the interpretation of satellite measurements.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".