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Record W4255485260 · doi:10.5194/tcd-9-6395-2015

Growth of a young pingo in the Canadian Arctic observed by RADARSAT-2 interferometric satellite radar

2015· preprint· en· W4255485260 on OpenAlexfundaboutno aff
Sergey Samsonov, Trevor C. Lantz, Steven V. Kokelj, Yu Zhang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPermafrostGeologyElevation (ballistics)Synthetic aperture radarArcticAggradationDigital elevation modelInterferometric synthetic aperture radarSatelliteGeomorphologyRemote sensingPhysical geographyStructural basinOceanographyGeographyFluvial

Abstract

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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 previously unreported 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. Observed changes in elevation were modeled as a 348 m × 290 m uniformly loaded elliptical plate with clamped edge. Model results suggest that this feature is one of the largest diameter pingos in the region that is presently growing. Analysis of historical aerial photographs showed that ground uplift at this location initiated sometime between 1935 and 1951 following lake drainage. 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 permafrost using the Northern Ecosystem Soil Temperature (NEST) was consistent with the maximum height of this feature and the 1972–2014 elevation changes estimated from aerial photographs, suggesting that permafrost aggradation is resulting in the freezing a sub-pingo water lens. Seasonal variation in the uplift rate seen in the DInSAR data also matches the modeled seasonal pattern in the deepening rate of freezing front. This study demonstrates that interferometric satellite radar can successfully contribute to understanding the dynamics of terrain uplift in response to permafrost aggradation and ground ice development in remote polar environments, and highlights possible application of detecting deformation of Martian landscapes. However, our DInSAR data did not show clear growth at other smaller pingos in contrast with field studies performed mainly before the 1990s. Further investigation of this apparent discrepancy may help define limitations of our processing methodology and DInSAR data.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.096
GPT teacher head0.248
Teacher spread0.152 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2015
Admission routes2
Has abstractyes

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