Analysis of temporal radar backscatter of rice: A comparison of SAR observations with modeling results
Bibliographic record
Abstract
AbstractIn this study an established microwave backscatter model is used to predict the radar backscatter behavior of rice and to understand the interaction between backscatter and the rice canopy during its growth cycle. The emphasis of this study is to understand the effect of physical plant parameters on the backscatter signatures as a function of polarization and how these signatures vary during a complete growth cycle of rice. Inputs to the backscatter model included the physical parameters of rice as obtained through field measurements. These measurements were acquired within a few days of multiple RADARSAT acquisitions of the Zhaoqing test site in southern China. RADARSAT observations and the modeling results were then compared and analyzed. The results show that the interaction mechanisms change during the rice growth cycle and polarimetric and (or) multi-polarization measurements at C band will contribute to rice monitoring programs.Nous utilisons dans cette étude un modèle reconnu de rétrodiffusion micro-onde pour prédire le comportement de la rétrodiffusion radar du riz et pour comprendre l'interaction entre la rétrodiffusion et le couvert du riz durant la période de croissance. L'intérêt principal de cette étude est de comprendre l'effet des paramètres physiques des plantes sur les signatures de rétrodiffusion en tant que fonction de la polarisation et comment ces signatures varient tout au long d'un cycle complet de croissance du riz. Les intrants au modèle de rétrodiffusion incluent les paramètres physiques du riz tels qu'obtenus par des mesures sur le terrain. Ces mesures ont été acquises à l'intérieur d'une période de quelques jours au cours d'une campagne d'acquisition d'images multiples RADARSAT sur le site d'expérimentation de Zhaoqing dans le sud de la Chine. Les observations RADARSAT et les résultats de la modélisation ont alors été comparés et analysés. Les résultats montrent que les mécanismes d'interaction changent durant le cycle de croissance du riz et que les mesures polarimétriques et (ou) en multipolarisation en bande C apportent une contribution aux programmes de suivi du riz.[Traduit par la Rédaction]
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".