An inversion method based on multi-angular approaches for estimating bare soil surface parameters from RADARSAT-1
Bibliographic record
Abstract
Abstract. The radar signal recorded by earth observation (EO) satellites is sensitive to soil moisture and surface roughness, which both influence the onset of runoff. This paper focuses on inversion of these parameters using a multi-angular approach based on RADARSAT-1 data with incidence angles of 35° and 47° (in mode S3 and S7). This inversion was performed with three backscatter models: Geometrical Optics Model (GOM), Oh Model (OM), and Modified Dubois Model (MDM), which were compared to obtain the best configuration. Mean absolute errors of 1.23, 1.12, and 2.08 cm for roughness expressed in rms height and for dielectric constant, mean absolute errors of 2.46 – equal to 3.88 (m3 m−3) in volumetric soil moisture, – 4.95 – equal to 8.72 (m3 m−3) in volumetric soil moisture – and 3.31 – equal to 6.03 (m3 m−3) in volumetric soil moisture – were obtained for the MDM, GOM, and OM simulation, respectively. These results indicate that the MDM provided the most accurate data with minimum errors. Therefore, the latter inversion algorithm was applied to images, and the final results are presented in two different maps showing pixel and homogeneous zones for surface roughness and soil moisture.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".