Investigation of Polarimetric Palsar2 and Palsar3 for Discontinuous Permafrost Mapping and Monitoring in Northern Alberta
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».