Investigation of Polarimetric Palsar2 and Palsar3 for Discontinuous Permafrost Mapping and Monitoring in Northern Alberta
Bibliographic record
Abstract
Northern Alberta contains a significant component of discontinuous permafrost, which is distributed within wooded palsa bogs and peat plateaus that form part of heterogeneous mosaic of non-permafrost wooded bogs, fens, swamps and other upland forest types. In this study, the potential of Polarimetric ALOS2-PALSAR2 for discontinuous permafrost mapping and monitoring is investigated. Polarimetric ALOS2, LIDAR and field data were collected in the middle of August 2014, at the maximum permafrost thaw conditions, over discontinuous permafrost distributed within wooded palsa bogs and peat plateaus near the Na mur Lake (Northern Alberta). The scattering type phase generated by the Touzi decomposition [1], which was shown to be sensitive to peatland subsurface water flow, is investigated for discontinuous permafrost mapping. It is shown that the dominant and medium scattering type phases are the only polarimetric parameters which can detect subsurface discontinuous permafrost [2]. The medium scattering type phase,$\phi_{s 2}$, performs better than the dominant scattering type phase,$\phi_{s 1}$, and permits a better detection of subsurface discontinuous permafrost in peatland regions.$\phi_{s 2}$also allows better discrimination of areas underlain by permafrost from the non-permafrost areas. The Touzi discriminators [3], which exploits the extrema of the degree of polarization (DoP), permit solving for the scattering type phase ambiguities that might occur in areas with deep permafrost (more than 55 cm depth). Since 2020, Polarimetric ALOS2 have been collected at FP6-3 (22° incidence angle) over the study site in the fall, summer, and late August (at the maximum permafrost thaw conditions). The comparison of the results obtained in 2023 and 2020 with the 2014 investigation revealed a significant transformation of discontinuous permafrost distribution and Active Layer Thickness (ALT). This is not surprising since, from 2014-2023, the rate of human-induced warming was 0.26° C per decade, which is unprecedented. The potential role of permafrost changes in response to wildfires in the region should also be mentioned. There have been a number of very large fires in this general region since 2014 which may have had a very significant impact overall as well. This significant transformation of discontinuous permafrost distribution and ALT could have implications for linear infrastructures, surface water hydrology, and ecosystem function in the region. Field data will be collected in the future for the validation of these results. The excellent performances of polarimetric PALSAR2 in term of NESZ$(-37 ~\text{dB})$permit the demonstration of the very promising L-band long penetration SAR capabilities for enhanced detection and mapping of relatively deep (up to 55$\text{cm})$discontinuous permafrost in peatlands regions [2]. The Namur lake study sites will be used to assess and validate ALOS4-PALSAR3 calibration and NESZ performances for peatland and discontinuous permafrost mapping. ALOS4 acquisitions have been ordered at the polarimetric FPQ4 (22° incidence angle) from the spring (permafrost melting season) to the fall (freezing season). Equipped with digital antenna beaming, ALOS4-PALSAR3 is initiating the new ere of operational polarimetry with high-resolution (3m) large swath$(100 ~\text{km})$cover.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".