AN IMPACT OF THE ATMOSPHERE ON THE STUDIES OF RUGGED TERRAIN BY RADAR INTERFEROMETRY TECHNIQUES
Bibliographic record
Abstract
An influence of the atmosphere on the interferometric studies of the rugged terrain in the area of Tolbachik volcanic complex, Kamchatka, is discussed. Brief description of the radar interferometry technique and the components of the interferometric phase differences are presented. The two-component model of the troposphere is described, which assumes the decomposition of the refractive index into dry and wet components. An influence of the variations of the troposphere refractive index between radar observations on the phase measurements is simulated. The weather data of Klyuchi meteorological station were interpolated to the moments of the Canadian synthetic aperture radar «Radarsat-2» observations in summer-autumn 2013 and used as input data in the modeling. In the number of cases the calculated differential radar interferograms contain non-zero values of the phase difference that grow with the height of the relief. The non-zero phase differences observed on the interferograms are typically in the good agreement with simulation results. A noticeable discrepancy between interferometric measurements and simulation data occurs in the case of unstable weather with sharp alteration of relative humidity in the survey area, especially in the case the troposphere meteorological parameters vary in different directions during the radar observations. An assumption is made that the reason of the observed modeling errors is that the weather data of distant meteorological station do not match sometimes the actual weather conditions in the study area. The impact of variations of the refractive index between radar observations is less, the less the variations of the relief heights in the survey area.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".