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Record W3091890590 · doi:10.3389/feart.2020.561322

Effective Monitoring of Permafrost Coast Erosion: Wide-scale Storm Impacts on Outer Islands in the Mackenzie Delta Area

2020· article· en· W3091890590 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFrontiers in Earth Science · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsDalhousie UniversityGovernment of NunavutNatural Resources CanadaGeological Survey of Canada
FundersNatural Environment Research CouncilNatural Resources CanadaIndigenous and Northern Affairs CanadaParks CanadaNorthumbria University
KeywordsStormPermafrostGeologyCliffDeltaScale (ratio)ErosionEnvironmental scienceWinter stormRiver deltaPhysical geographyClimatologyRemote sensingOceanographyGeomorphologyCartographyGeography

Abstract

fetched live from OpenAlex

Permafrost coasts are extensive in scale and complex in nature, resulting in particular challenges for understanding how they respond to both long-term shifts in climate and short-term extreme weather events. Taking examples from the Canadian Beaufort Sea coastline characterised by extensive areas of massive ground ice within slump and block failure complexes, we conduct a quantitative analysis of the practical performance of helicopter-based photogrammetry. The results demonstrate that large scale (>1 km2) surface models can be achieved at comparable accuracy to standard UAV surveys, but 36 times faster. Large scale models have greater potential for progressive alignment and contrast issues and so breaking down image sequences into coherent chunks has been found the most effective technique for accurate landscape reconstructions. The approach has subsequently been applied in a responsive acquisition immediately before and after a large storm event and during conditions (wind gusts >50 km hr-1) that would have prohibited UAV data acquisition. Trading lower resolution surface models for large scale coverage and more effective responsive monitoring, the helicopter-based data have been applied to assess storm driven-change across the exposed outer islands of the Mackenzie Delta area for the first time. These data show that the main storm impacts were concentrated on exposed North orientated permafrost cliff sections (particularly low cliffs, >20 m in height) where cliff recession was 43% of annual rates and in places up to 29% of the annual site-wide erosion volume was recorded in this single event. In contrast, the thaw-slump complexes remained relatively unaffected, debris flow fans were generally more resistant to storm erosion than the ice-rich cliffs, perhaps due to the relatively low amounts of precipitation that occurred. Therefore, the variability of permafrost coast erosion rates is controlled by interactions between both the forcing conditions and local response mechanisms. Helicopter-based photogrammetric surveys have the potential to effectively analyse these controls with greater spatial and temporal consistency across more representative scales and resolutions than has previously been achieved, improving the capacity to adequately constrain and ultimately project future Arctic coast sensitivity.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.011
Threshold uncertainty score0.705

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.241
Teacher spread0.214 · 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