Radarsat-1 calibration and image quality evolution to the extended mission
Bibliographic record
Abstract
Abstract Since its launch on November 4, 1995 and the start of the routine operation on April 1, 1996, RADARSAT-1, the first Canadian Synthetic Aperture Radar (SAR) remote sensing satellite, has provided calibrated data to worldwide users for their intended applications. From the early qualification stages of the mission, both single beams and ScanSAR operating modes are monitored routinely for radiometric calibration performance using images of the Amazon Rainforest, and for image quality performance using images of RADARSAT-1 Precision Transponders. After the initial Calibration Phase and the Antarctic Mapping Mission in 1997, a systematic calibration monitoring strategy showed changes in the characteristics of several previously calibrated elevation antenna patterns. Compensations for these changes are made in the processor by re-calibrating the beams. In addition, a major upgrade of the ScanSAR processor completed at the Canadian Data Processing Facility (CDPF) in 2002 yielded to significant improvements in image quality and radiometry. Throughout the nominal mission life of 5 years and the 3 years of the current extended mission, which started in early 2001, the Canadian Data Processing Facility continued to provide radiometrically and geometrically calibrated RADARSAT-1 products to users. In late October 2000, concerns began to rise of the possibility of failure of the Horizon Scanner 1, which would result in operating the spacecraft in a mode known as ‘Attitude Determination Method 3’ (ADM3), causing a decrease in attitude control performance of the spacecraft compared to the current operation in primary ADM1. Experiments were conducted to better understand the impact on processing and image quality when in ADM3 mode. No major impact on image quality was noticed with adapted re-processing. In mid 2002, due to aging considerations for the On-Board Recorder, natural sites within Canadian data reception masks have been envisioned for their potential to support radiometric analyses, as an alternative to the Amazon Rainforest where images are recorded. From several sites, a Boreal Forest location near Hearst, Ontario, Canada was chosen for testing radiometric measurements, using specific beams to cover the entire range of incidence angles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".