Permafrost Dynamics Observatory (PDO): 2. Joint Retrieval of Permafrost Active Layer Thickness and Soil Moisture From L‐Band InSAR and P‐Band PolSAR
Bibliographic record
Abstract
Abstract Seasonal subsidence induced by ground ice melt can be measured by interferometric synthetic aperture radar (InSAR) techniques to infer active layer thickness (ALT) in permafrost regions. The magnitude of subsidence depends on both how deep the soil thawed and how much ice/water content existed in the active layer soil. To provide the later, P‐band polarimetric synthetic aperture radar (PolSAR) backscatter is used due to its sensitivity to subsurface soil moisture and freeze/thaw conditions. In this study, which is the second in a two‐part series of Permafrost Dynamics Observatory (PDO), we exploit L‐band InSAR subsidence and P‐band PolSAR backscatter in a joint retrieval scheme to simultaneously estimate ALT and soil moisture profile of permafrost active layer. Both subsidence and backscatter are explicitly characterized by physics‐based models and share a common set of soil parameters including porosity and water saturation profiles. The PDO joint retrieval has been applied to the L‐ and P‐band SAR data acquired by National Aeronautics and Space Administration/Jet Propulsion Laboratory's Uninhabited Aerial Vehicle Synthetic Aperture Radar over Alaska and western Canada during the 2017 Arctic‐Boreal Vulnerability Experiment (ABoVE) airborne campaign. This high‐resolution (30 m) regional estimates of ALT and soil moisture profile spanning over the ABoVE study domain can help link the ground‐based field surveys with satellite observations to further understand the permafrost and active layer soil process dynamics to disturbances and climate change occurring across the northern circumpolar region.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".