TanDEM‐X Time Series Analysis Reveals Lava Flow Volume and Effusion Rates of the 2012–2013 Tolbachik, Kamchatka Fissure Eruption
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".