Empirical model for surface soil moisture estimation over wheat fields using C-band polarimetric SAR
Bibliographic record
Abstract
This study proposes a simple empirical model based on polarimetric parameters extracted from RADARSAT-2 imagery to retrieve surface soil moisture (0-5 cm) over agricultural fields. The model is calibrated with ground data acquired from 13 wheat fields, over their whole growth cycle, during the SMAPVEX12 campaign. Sensitivity analysis of the extracted polarimetric variables to soil moisture demonstrated distinct correlations before and after the beginning of the crops flowering stage. Linear backscattering showed significant correlations for all polarizations before crops flowering. The empirical model based on combined linear backscattering coefficients and polarimetric variables allowed to retrieve soil moisture with a 0.076 m3/m3. RMSE if calibrated for the whole growth cycle, 0.067 m3/m3. RMSE if calibrated for data before crop flowering and 0.042 m3/m3. With the data after flowering.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".