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Record W2763119356 · doi:10.1002/2017jb014309

TanDEM‐X Time Series Analysis Reveals Lava Flow Volume and Effusion Rates of the 2012–2013 Tolbachik, Kamchatka Fissure Eruption

2017· article· en· W2763119356 on OpenAlexaff
Julia Kubanek, Malte Westerhaus, Bernhard Heck

Bibliographic record

VenueJournal of Geophysical Research Solid Earth · 2017
Typearticle
Languageen
FieldEngineering
TopicSynthetic Aperture Radar (SAR) Applications and Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsLavaGeologyEffusive eruptionDigital elevation modelLava domeVolcanologyVolcanoLateral eruptionVolume (thermodynamics)GeomorphologyRemote sensingSeismologyMagmaExplosive eruption

Abstract

fetched live from OpenAlex

Abstract Assessing eruption volumes is one of the major challenges in volcano research but provides valuable insights into the dynamics of an eruption and the associated hazard. One way to estimate this important parameter is the generation and differencing of digital elevation models (DEMs) acquired before, during, and after an eruption. The satellite mission TanDEM‐X enables generation of time series of DEMs using synthetic aperture radar satellite imagery. We use these data to study the 2012–2013 eruption of Tolbachik in Kamchatka. We developed a processing scheme for generation of 18 DEMs from TanDEM‐X imagery that relies on the generation of a preeruption DEM which is used to process the syneruption and posteruption data pairs. Differencing each DEM with the preeruption DEM enables mapping the lava flows and measuring lava flow volume over time and to estimate lava extrusion rates. We find a final lava flow volume of 0.53 km 3 covering an area of 36 km 2 by the end of the eruption. An uncertainty analysis is performed while analyzing the DEM differences in areas where no topographic change is expected, leading to an error of ±0.01 km 3 for the final lava flow volume. The lava effusion was with 247.92 m 3 /s very high in the first days of the eruption and rapidly decayed toward its end. While many basaltic eruptions follow an exponentially decaying flow model, the extrusion rates at Tolbachik are more compatible with a 1/ t model. This special characteristic might be useful to gain further insight into the eruption process at Tolbachik.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.017
GPT teacher head0.313
Teacher spread0.296 · 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 teacher head, 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

Citations47
Published2017
Admission routes1
Has abstractyes

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