Seasonal Spectral Separation of Western Snowberry and Wolfwillow in Grasslands with Field Spectroradiometer and Simulated Multispectral Bands
Why this work is in the frame
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Bibliographic record
Abstract
Woody plant encroachment (WPE), the expansion of native and non-native trees and shrubs into grasslands, has led to degradation worldwide. In the Canadian prairies, western snowberry and wolfwillow shrubs are common encroachers, whose cover is currently unknown. As the use of remote sensing in grassland monitoring increases, opportunities to detect and map these woody species are enhanced. Therefore, the purpose of this study is to identify the optimal season for detection of the two shrubs, to determine the sensitive wavelengths and bands that allow for their separation, and to investigate differences in separability potential between a hyperspectral and broadband multispectral approach. We do this by using spring, summer, and fall field-based spectra of both shrubs for the calculation of spectral separability metrics and for the simulation of broadband spectra. Our results show that the summer offers higher discrimination between the two species, especially when using the red and blue spectral regions and to a lesser extent the green region. The fall season fails to provide significant spectral separation along the wavelength spectrum. Moreover, there is no significant difference in the results from the hyperspectral or broadband approach. Nevertheless, cross-validation with satellite imagery is needed to confirm the current results.
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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 | 0.000 | 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 it