Landscape Freeze/Thaw Mapping from Active and Passive Microwave Earth Observations over the Tursujuq National Park, Quebec, Canada
Bibliographic record
Abstract
<p>Nous avons examiné la sensibilité au couvert végétal de la classification gel/dégel (G/D) active (PALSAR) et passive (SMAP). Nous avons aussi utilisé une classification G/D à partir de données à haute résolution (30 m) PALSAR pour suivre l’évolution des états gelé et dégelé des sols provenant d’un algorithme adapté avec des données à faible résolution (36 km) SMAP. Nous avons utilisé des scènes SMAP et PALSAR acquises au-dessus du Parc national Tursujuq (Umiujaq, Quebec, Canada) entre juin 2015 et janvier 2017. Un nouvel algorithme G/D avec des seuils de référence spécifiques à chaque type de végétation (arbustes, herbacées, lichens, milieu humide, et terre nue) est proposé pour classifier les pixels PALSAR. La validation de la classification G/D PALSAR avec les données de température du sol à ~5 cm de la surface a révélé une meilleure précision (> 80%) avec les seuils en polarisation de transmission horizontale et de réception verticale (HV). La classification G/D PALSAR montre qu’un pixel SMAP est classifié comme gelé lorsque plus de 50% de sa surface est gelée. Nous avons confirmé la sensibilité au couvert végétal des classifications G/D passive et active en bande L.</p><h2>Abstract</h2><p> We investigated the sensitivity to vegetation cover type of active (PALSAR) and passive (SMAP) freeze/thaw (F/T) classification. We also used F/T classification from high-resolution PALSAR data (30 m) to follow the evolution of frozen and thawed soil states obtained from an adaptive algorithm with low-resolution SMAP data (36 km). We used PALSAR and SMAP scenes acquired from June 2015 to January 2017 over the Tursujuq National Park (Umiujaq, Quebec, Canada). A new F/T algorithm with a specific reference threshold under each vegetation type (shrub, grass, lichen, wetland, and bare land) is proposed to classify PALSAR pixels. The validation of the PALSAR F/T classification with soil temperature at ~5 cm depth revealed a greater overall accuracy (> 80%), with horizontal transmitted and vertical received (HV) thresholds. The PALSAR F/T classification shows that a SMAP pixel is classified as frozen when more than 50% of its area is frozen at the surface. We confirmed the sensitivity to vegetation cover type of passive and active F/T classification with L-band sensor.</p>
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 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 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".