Coherent stacks of RADARSAT-2 spotlight mode interferometry data for monitoring Arctic DEW Line Clean-Up
Bibliographic record
Abstract
The DEW Line Clean-Up proof-of-concept project was conducted to determine if space-based Synthetic Aperture Radar (SAR) data from the Canadian satellite RADARSAT-2 can be used for landfill monitoring at the DEW Line sites. Interferometric stacks (time series consisting of interleaved 24-day cycles) of RADARSAT-2 Spotlight mode images are being acquired over four of the former DEW Line sites. Results show that amplitude change detection, coherent change detection and surface deformation products are useful for detecting change in and around landfills. Although these techniques cannot fully eliminate site visits and visual inspection, this study has shown that space-borne SAR can detect structural changes not yet evident to the field inspection teams and provide other useful information such as flooding. The RADARSAT Constellation Mission (RCM) with its four-day coherent repeat (scheduled for launch in 2018) will prove a great asset for monitoring the former DEW Line sites.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".