Wind Speed Retrieval From Hybrid-Pol Compact Polarization Synthetic Aperture Radar Images
Bibliographic record
Abstract
This paper presents an attempt to retrieve wind speed from hybrid-pol compact polarization (CP) synthetic aperture radar (SAR) data. Cross-polarization (cross-pol, denoted by HV or VH) facilitates wind speed retrieval and improves the accuracy of the results, especially with respect to high wind speeds. Although the cross-pol data cannot be obtained from CP SAR data directly, these data can be reconstructed from CP SAR data. However, the existing reconstruction algorithms cannot satisfy the quantitative wind-speed retrieval requirements for specifying the critical parameter, denoted “N” in reconstruction algorithms, either as a constant, or as a variable with limited range. Here, N is defined in terms of the ratio between cross- and co-polarization channels and the coherence coefficient between co-polarization (denoted by HH and VV) channels. Thus, we have improved the empirical reconstruction algorithm for the modified N based on a data set of more than 2000 RADASAT-2 (RS-2) quad-polarization images and collocated buoy observations. The algorithm improves the accuracy for the reconstruction of cross-pol data and, ultimately, gives improved wind speed retrievals from the hybrid-pol CP SAR data. With the new algorithm, results show that the wind speed retrievals from reconstructed cross-pol data can approximate the accuracy of VH observations collected by RS-2.
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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 | 0.000 | 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 | 0.001 |
| 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 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".