ASAR WSS product verification using derived image mosaics
Bibliographic record
Abstract
A program has been written to create image mosaics from ASA_WSS_1P ASAR-WSS level-1 products, providing an overview of the imaged area. The ability to generate WSS mosaics facilitates the study of several WSS product features. This study focuses on their radiometric and geometric characteristics. The incidence angle variation of 16 to 43 degrees across beams SS1 through SS5 creates large differences in the nominal near- and far-range backscatter intensities. Radiometric calibration is applied to the mosaics, taking the range-spreading loss as well as the incidence angle effect into account, normalising for systematic radiometric trends. The five WSS beams acquire data with a substantial overlap (typically several hundred range samples). These overlap regions are of interest because the same ground targets are imaged by two different beams. We calculate the mean radiometric differences between the two beams for each overlap region, and draw conclusions based on the statistics. WSS geolocation accuracy is assessed for the image mosaics as well, using two methods. First, predicted positions of transponders in the Netherlands and Canada are compared to measured positions. Second, terrain geocoding of selected WSS scenes is performed, using DORIS precise state vectors and a digital terrain model (DTM). The geolocation accuracy is estimated using survey points or ground control points (GCPs) derived from topographic maps. The radiometric and geometric investigations confirm a high quality of the level-1 WSS products.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".