FOREST HEIGHT AND BIOMASS ESTIMATION USING SPACE-BORNE POLARIMETRIC SAR DATA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To demonstrate the potential of ALOS PALSAR data for polarimetric SAR interferometry (PolInSAR), a pair of PALSAR polarimetric scenes has been selected over Glen Affric, Scotland where various ground truth is available including digital terrain models (DTMs) and tree measurements. The overall coherence level is quite low due to the temporal decorrelation, relatively lower signal-to-noise ratio (SNR), and possible residual mis-registration between the two scenes. The results show that the low observed coherence level in forest in all lexicographic polarizations is a major problem challenging PolInSAR using PALSAR data. Additional data sets of forested areas in Kenai, Alaska and Edson, Alberta were similarly addressed with the same problematic results.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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