Calculation and Evaluation of BRF Correction Factors for Railroad Valley Playa
Bibliographic record
Abstract
Applications ranging from military reconnaissance to climate studies depend on the data collected by spaceborne remote sensors. Vicarious calibration is one method by which these sensors are validated. At the Radiometric Calibration Test Site (RadCaTS) in Railroad Valley Playa, Nevada, several autonomous ground viewing radiometers (GVRs) measure the surface reflectance at a nadir view. These data can then be used to calibrate sensors that view the playa from space. The process works well for sensors that view the playa at nadir, but uncertainty increases when the sensors view the playa at large zenith angles due to the non-Lambertian nature of the playa surface. However, if the bidirectional reflectance factor (BRF) of the surface is determined through models or measurement, it is possible to calculate a correction factor that converts a nadir reflectance value to the expected reflectance at an arbitrary view angle. Using preliminary surface measurements taken by the University of Lethbridge Goniometer System II (ULGS-II), correction factors were calculated which improved the agreement between the bottom of atmosphere (BOA) reflectances determined by RadCaTS and those measured by the Sentinel-2A and -2B Multispectral Instrument (MSI) for a view zenith angle (VZA) of 11°.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".