Assessment of PALSAR-2 Compact Non-Circularity Using Amazonian Rainforests
Bibliographic record
Abstract
Compact-hybrid SAR (CP) is a dual-polarization (dual-pol) SAR mode that transmits a circular polarization (CirP) and measures the received signal at the horizontal and vertical antenna polarization. It is now admitted that the actual SAR technology does not permit the generation of a perfectly CirP and this may significantly affect CP radiometric and phase information. Since all the existing CP calibration models assume a perfectly transmitted CirP, there is an immediate need for the development of a new model that permits efficient assessment and calibration of CP non-circularity. In this article, a new general polarimetric hybrid SAR model (PolHyb) is introduced for both dual- (CP) and quad-polarization hybrid SAR modes. PolHyb explicitly includes the transmitted polarization non-circularity, in addition to conventional radar transmit and receive distortion matrices, channel imbalances and Faraday rotation contamination. The non-circularity of transmitted polarization is expressed in terms of the axial ratio (AR), which used to be popular in the 1960s for characterization of circularly polarized (transmit and receive) dual- and quad-polarization radar. The new CP model derived from PolHyb is adapted to PALSAR2-CP and used as the basis of an efficient method for an assessment of CP non-circularity using Amazonian rainforests. PALSAR2-CP data collected at four different beams (H2-6 to H2-9), with incidence angle varying between 30° and 45°, allows for the first ever demonstration of non-circularity of PALSAR2 CP transmitted polarization. Although it is lower than 0.5 dB for H2-6 and H2-7, the AR of PALSAR2-CP transmitted polarization increases significantly with incidence angle to reach up to 1 dB at Beam H2-8, and 2.3 dB at the highest incidence angles of Beam H2-9.
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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) | 0.001 | 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) | 0.000 | 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".