Permafrost Dynamics Observatory (PDO): 2. Joint Retrieval of Permafrost Active Layer Thickness and Soil Moisture From L‐Band InSAR and P‐Band PolSAR
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
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.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it