Vegetation height derived from Sentinel-1 and Sentinel-2 satellite data (2015-2018) for tundra regions
Bibliographic record
Abstract
Vegetation height has been derived from Sentinel-1 satellite data acquired in VV mode. Masking based on Sentinel-2 has been applied.Areas with NDVI < 0.4 are excluded for vegetation height retrieval in order to account for effects related to C-band scattering from rough and bare surfaces. Areas with VV < -15.4 dB (and NDVI > 0.4) are flagged as well as indicator for anomalous high values in vegetation related indices with at the same time low vegetation height. The remaining land area is assigned vegetation heights up to 160 cm. All heights > 160 cm are excluded and labelled as a separate class.Covered areas are: Yamal peninsula (Russia), Usa Basin (Russia), Lena Delta (Russia), Kytalyk (Russia), Mackenzie Delta (Canada), Umiuaq (Canada), Barrow (Alaska), Teshekpuk (Alaska), Toolik (Alaska) and Seward peninsula (Alaska).For more Information see the product documentation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.023 |
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".