Combining Satellite Remote Sensing Data with the FAO-56 Dual Approach for Water Use Mapping In Irrigated Wheat Fields of a Semi-Arid Region
Bibliographic record
Abstract
The aim of this study was to combine the FAO-56 dual approach and remotely-sensed data for mapping water use (ETc) in irrigated wheat crops of a semi-arid region. The method is based on the relationships established between Normalized Difference Vegetation Index (NDVI) and crop biophysical variables such as basal crop coefficient, cover fraction and soil evaporation. A time series of high spatial resolution SPOT and Landsat images acquired during the 2002/2003 agricultural season has been used to generate the profiles of NDVI in each pixel that have been related to crop biophysical parameters which were used in conjunction with FAO-56 dual source approach. The obtained results showed that the spatial distribution of seasonal ETc varied between 200 and 450 mm depending to sowing date and the development of the vegetation. The validation of spatial results showed that the ETc estimated by FAO-56 corresponded well with actual ET measured by eddy covariance system over test sites of wheat, especially when soil evaporation and plant water stress are not encountered.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".