A conjunct near-surface spectroscopy system for fix-angle and multi-angle continuous measurements of canopy reflectance and sun-induced chlorophyll fluorescence
Bibliographic record
Abstract
An automated spectroscopy system, which is divided into fix-angle and multi-angle subsystems, for collecting simultaneous, continuous and long-term measurements of canopy hyper-spectra in a crop ecosystem is developed. The fix-angle subsystem equips two spectrometers: one is HR2000+ (OceanOptics) covering the spectral range 200–1100 nm with 1.0 nm spectral resolution, and another one is QE65PRO (OceanOptics) providing 0.1 nm spectral resolution within the 730-780 nm spectral range. Both spectrometers connect a cosine-corrected fiber-optic fixed up-looking to collect the down-welling irradiance and a bare fiber-optic to measure the up-welling radiance from the vegetation. An inline fiber-optic shutter FOS-2x2-TTL (OceanOptics) is used to switch between input fibers to collect the signal from either the canopy or sky at one time. QE65PRO is used to permit estimation of vegetation Sun-Induced Fluorescence (SIF) in the O2-A band. The data collection scheme includes optimization of spectrometer integration time to maximize the signal to noise ratio and measurement of instrument dark currency. The multi-angle subsystem, which can help understanding bidirectional reflectance effects, alternatively use HR4000 (OceanOptics) providing 0.1 nm spectral resolution within the 680-800 nm spectral range to measure multi-angle SIF. This subsystem additionally includes a spectrometer Unispec-DC (PPSystems) featuring both up-welling and down-welling channels with 3 nm spectral resolution covering the 300-1100 nm spectral range. Two down-looking fiber-optics are mounted on a rotating device PTU-D46 (FLIR Systems), which can rotate horizontally and vertically at 10° angular step widths. Observations can be used to calculate canopy reflectance, vegetation indices and SIF for monitoring plant physiological processes.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".