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Record W2909612439

Terrestrial laser scanning for quantifying small-scale vertical movements of the ground surface in Arctic permafrost regions

2017· article· en· W2909612439 on OpenAlex
Sabrina Marx, Katharina Anders, Sofia Antonova, Inga Beck, Julia Boike, Philip Marsh, Moritz Langer, Bernhard Höfle

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHelmholtz-Zentrum für Polar-und Meeresforschung (Alfred-Wegener-Institut) · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostRemote sensingGeologyArcticTundraTerrainScale (ratio)Vegetation (pathology)Sampling (signal processing)SubsidenceEnvironmental scienceGeomorphologyGeographyCartographyFilter (signal processing)Computer science
DOInot available

Abstract

fetched live from OpenAlex

Three-dimensional data acquired by terrestrial laser scanning (TLS) provides an accurate representation of the Earth’s surface, which is commonly used to detect and quantify topographic changes on a small scale. However, in Arctic permafrost regions TLS-based monitoring of thaw subsidence is challenging due to vegetation and the micro-topographic characteristics (e.g. dense moss-lichen layer, hummocks etc.). In this presentation, we focus, firstly, on the evaluation of raster- and point-based TLS methods for quantifying small-scale thaw subsidence within the continuous permafrost zone. Secondly, a new filter strategy is presented that reduces spatial sampling effects caused by various factors such as vegetation, micro-topography and scan-setup. Our study site is located at the Trail Valley Creek research watershed, 50 km north-east of Inuvik, Northwest Territories, Canada. Three field campaigns took place in 2015 and 2016. Besides capturing TLS data, at-point real-time kinematic (RTK) Global Navigation Satellite System (GNSS) measurements and manual subsidence measurements were gathered. To achieve a highly accurate registration (on mm-scale) of the three TLS campaigns, co-registration of the georeferenced point clouds is performed based on the stable fix points in the otherwise highly dynamic permafrost environment. Then, different methods to quantify vertical ground movements are applied and evaluated. The result reveals limitations of standard raster-based DEM differencing, but also of point-based distance calculation for detecting spatial patterns of small-scale thaw subsidence. In the Arctic tundra ecosystem, TLS-based deformation analysis is strongly affected by occlusion and spatial sampling effects, even if data acquisition is repeated from similar scan positions. We show that the mentioned errors can be reduced by capturing the ground surface from more than one TLS scan position. Our filter strategy allows to identify TLS points which are suitable for multi-temporal deformation analyses, and results in an average seasonal subsidence rate (2015/06-2015/08) of about -2.0 cm at our study site. The derived subsidence maps deliver highly accurate ground-truth data, which is needed to improve area-wide subsidence monitoring methods such as SAR interferometry. This leads to a deeper understanding of permafrost-related subsidence processes.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.082
GPT teacher head0.307
Teacher spread0.226 · 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