ULGS II: A High-Performance Field and Laboratory Spectrogoniometer for Measuring Hyperspectral Bidirectional Reflectance Characteristics
Bibliographic record
Abstract
The derivation of the bidirectional reflectance distribution function (BRDF) from Earth surface features provides vital data for improved remote estimation of Earth surface features and properties. The angular component of a reflectance signature represents a valuable source of information that has largely been ignored due to the lack of empirical data. BRDF data products are now readily available from a variety of remote sensing platforms, and these require extensive field validation to ensure data quality and validity. This paper presents a high-performance, low-cost, and computer-controlled goniometer system capable of sampling surface BRDF and demonstrates several example applications. The system introduces a number of technological advances, including real-time reflectance calibration, programmable sampling schemes, zero target interference structure, and ease of portability. Using this instrument, BRDF estimates were gathered from a variety of agricultural crops in field and laboratory settings, with performance gains of four times the speed of current designs. This system can provide very fast acquisition of a BRDF estimate, depending on the desired angular resolution. Initial experiments demonstrate that this new style of hyperspectral goniometer is a significant advance over previous designs, with respect to scan capabilities, angular resolution, calibration, and portability.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".