Dielectric characterization of vegetation at L-band using an open-ended coaxial probe
Bibliographic record
Abstract
Abstract. Decoupling the integrated microwave signal originating from soil and vegetation remains a challenge for all microwave remote sensing applications. To improve satellite and airborne microwave data products in forest environments, a precise and reliable estimation of the relative permittivity (𝜺 = 𝜺’ – i 𝜺’’) of the trees is required. We developed an open-ended coaxial probe suitable for in situ permittivity measurements of tree trunks at L-band wavelengths (1–2 GHz). The probe is characterized by uncertainties under 3.3 % for a broad range of permittivities, [2–40] for 𝜺’ and [0.1–20] for 𝜺’’. We quantified the complex number describing the permittivity of seven different tree species in both frozen and thawed states: black spruce, larch, red spruce, balsam fir, red pine, aspen and black cherry. Variability in permittivity is substantial, and can range up to 300 % for some species. Our results show that the permittivity of wood is linked to the freeze/thaw state of the vegetation and that even short winter thaw events lead to an increase in vegetation permittivity. The open-ended coaxial probe proved to be precise enough to capture the diurnal cycle of water storage inside the trunk over the growing season.
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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 | 0.000 |
| 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 | 0.000 |
| 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".