Growth of a young pingo in the Canadian Arctic observed by RADARSAT-2 interferometric satellite radar
Bibliographic record
Abstract
Abstract. Advancements in radar technology are increasing our ability to detect Earth surface deformation in permafrost environments. In this paper we use satellite Differential Interferometric Synthetic Aperture Radar (DInSAR) to describe the growth of a large, relatively young pingo in the Tuktoyaktuk Coastlands. High-resolution RADARSAT-2 imagery (2011–2014) analyzed with the Multidimensional Small Baseline Subset (MSBAS) DInSAR revealed a maximum 2.7 cm yr−1 of domed uplift located in a drained lake basin. Satellite measurements suggest that this feature is one of the largest diameter pingos in the region that is presently growing. Observed changes in elevation were modeled as a 348 × 290 m uniformly loaded elliptical plate with clamped edge. Analysis of historical aerial photographs suggested that ground uplift at this location initiated sometime between 1935 and 1951 following drainage of the residual pond. Uplift is largely due to the growth of intrusive ice, because the 9 % expansion of pore water associated with permafrost aggradation into saturated sands is not sufficient to explain the observed short- and long-term deformation rates. The modeled thickness of ice-rich permafrost using the Northern Ecosystem Soil Temperature (NEST) was consistent with the maximum height of this feature. Modeled permafrost aggradation from 1972 to 2014 approximated elevation changes estimated from aerial photographs for that time period. Taken together, these lines of evidence indicate that uplift is at least in part a result of freezing of the sub-pingo water lens. Seasonal variations in the uplift rate seen in the DInSAR data closely match the modeled seasonal pattern in the deepening rate of freezing front. This study demonstrates that interferometric satellite radar can detect and contribute to understanding the dynamics of terrain uplift in response to permafrost aggradation and ground ice development in remote polar environments. The present-day growth rate is smaller than predicted by the modeling and no clear growth is observed at other smaller pingos in contrast with field studies performed mainly before the 1990s. Investigation of this apparent discrepancy provides an opportunity to further develop observation methods and models.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".