SAR Polarimetric Phase Differences in Wetlands: Information and Mis-Information
Bibliographic record
Abstract
We have previously reported anomalous polarimetric decomposition results from SAR observations of wetlands. This is caused by the abrupt change in the phase difference between the HH and VV backscatter that occurs around the Brewster angle of the emergent vegetation. We have now developed and implemented a model for backscattering from wetlands that features a cylinder emergent from a water plane. The model was used in conjunction with an extensive set of RADARSAT-2 polarimetric observations of wetlands to provide further insights into the backscattering process. We are able to show how the abrupt Brewster transition in HH-VV phase difference varies with cylinder diameter and gravimetric moisture. We find that coherent cross-pol backscatter can result from cylindrical stems being tilted. In swamps with extensive tree mortality but primarily vertical trunks, the CPD can be used to monitor the drying of the trees and thus their fire hazard. These insights may be used to identify drying trees, indicating thawing permafrost, a potentially important climate change application in the near future. We recommend that applications researchers and users choose radar wavelengths that are considerably shorter, or longer, than the diameters of the cylinders producing the dominant double-bounce backscatter to avoid resonance effects.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".