Using SAR Data to Detect Wheat Irrigation Supply in an Irrigated Semi-arid Area
Bibliographic record
Abstract
The objective of this study was to use SAR (sensitivity of Synthetic Aperture Radar) data to detect the supply of irrigation water during the anthesis and grain-filling phenological stages of wheat in the irrigated Tadla perimeter of Morocco. Backscattering coefficients were derived from four ERS-1 (European Remote-Sensing Satellite-1) images acquired between 31 March and 12 April 2011 and were compared with the irrigation water invoices database. The analysis showed that there were significant changes in backscattering values caused by irrigation, with average values ranging between 0.11 and 3.11 dB. A reference level of 0.52 dB was established for differentiating between (recently; up to 4 days) irrigated and non-irrigated plots. We also set an interval of 5 days for the acquisition of SAR images in order to ensure continuous monitoring of the irrigated wheat plots over time. The study showed that radar data contain important information for the assessment of irrigation supplies during the cropping season, which could help regional decision-support systems to monitor and control irrigation supplies over large areas.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".