ANALYSIS OF ASAR IMAGERY FOR HYDROLOGICAL APPLICATIONS IN SARDINIA, ITALY
Bibliographic record
Abstract
We present results from analysis of a first set of Envisat ASAR images acquired in 2003-2004 over the Campidano region of Sardinia, Italy. The dataset includes 7 vertically polarized images (ASA_IMP_1P products) for the period Mar-Jun 2003 and 12 alternating polarization (HH and VV) images (ASA_APP_1P products) for Feb-Jul 2004, at two swaths (IS1, with incidence angle range 15.0-22.9 o , and IS2, with range 19.2-26.7 o ). In this report we analyze 3 IS1 APP images from the 2004 dataset. Ground data used to correct the images and to corroborate the analyses at field and regional scales include rainfall, digital terrain, irrigation, and land use maps. Our interest in this preliminary assessment is to determine whether the ASAR images can detect changes in surface soil moisture content over the spring-summer period, an application that would be very useful in water management for this agriculturally important region of Sardinia (e.g., irrigation planning and monitoring).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".