Sensitivity of C-band Synthetic Aperture RADAR to field-scale soil surface parameters
Bibliographic record
Abstract
This thesis investigates the sensitivity of polarimetric variables from C-band Synthetic Aperture RADAR to near-surface soil moisture (6 cm), micro-topographical surface roughness, and biomass cover, during pre/seed and post-harvest over agricultural fields. Variables examined include: the like-polarized and cross-polarized linear intensity channels; polarization ratios; the Total Power signal; the co-polarized phase difference and co-polarized complex correlation coefficient; Pedestal Height; extrema of the completely polarized and unpolarized components; extrema of the received power and scattered intensity; and the polarization coefficient of variation. Classification of scattering mechanisms with the Cloude-Pottier and Freeman-Durden decompositions are also examined. The empirical relationships between RADAR variables and surface parameters are first analyzed using data collected during field-validation campaigns. Secondly, RADAR imagery is integrated over the watershed scale to assess the operational discrimination of tillage practices with these polarimetric variables and decompositions. Overall results provide an enhanced theoretical understanding of these variables and decompositions for agricultural target retrievals and demonstrate promise for use in an agricultural monitoring scheme.
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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 | 0.002 |
| 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 | 0.000 |
| 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 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".