Drone-based ground-penetrating radar for glaciological applications
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
The cryosphere, which includes glaciers, ice sheets, ice shelves, sea ice, and permafrost, plays a crucial role in regulating the Earth’s climate, with significant impacts on ecosystems and human societies. Changes in the cryosphere, such as glacier retreat and ice shelf collapse, are key indicators of climate change, contributing to sea-level rise and accelerating global warming through feedback mechanisms. Consequently, understanding and modeling these changes is essential for predicting future climate impacts and developing effective adaptation and mitigation strategies. To model them consistently, in-situ data are necessary. Geophysics, particularly ground-penetrating radar (GPR), has been instrumental in studying the cryosphere’s internal structure. GPR can help to map ice thickness, estimate ice volume, detect water bodies, trace subglacial water flow, and more. Groundbased GPR surveys (i.e., by skis, snowmobile, or walking) offer high-resolution data but their coverage is usually spatially limited as they are labor-intensive and time-consuming, especially in difficult terrains. Airborne GPR surveys (i.e., on helicopter or airplane), though efficient, come at the cost of limited data density and resolution, and are expensive and polluting. This gap suggests the need for more adaptable methods of GPR data acquisition over glaciers. This thesis introduces a drone-based GPR system developed for acquiring highresolution and high-density 3D GPR data over alpine glaciers. The specification of each of its components as well as the survey methodology have been optimized to allow for efficient and safe data acquisitions. An 80-MHz antenna and a recording time of 2800 ns mean that depths of over 100 m can be reached in temperate ice. Also, differential GPS positioning assures accurate flight paths. The system was used to acquire a 3D dataset over the Otemma glacier in Switzerland, where 462 profiles were surveyed at a 1-m line spacing, totaling over 112 line-km of data covering an area of approximately 350 m x 500 m, in only four days. This proves the efficiency of our drone-based GPR system in acquiring such high-density 3D GPR data over glaciers. The accurate positioning capabilities of the drone-based GPR system makes precise repetitions of 3D acquisitions possible, further leading to high-resolution and high-density 4D GPR data. This was done over a near-terminus collapse feature at the Rhône glacier in Switzerland. The survey covers an area of approximately 100 m x 150 m, consists of over 100 parallel GPR lines with a 1-m lateral spacing, and was repeated four times between July and October 2022. Such acquisitions would not have been possible with conventional GPR methods. The data provide insights into the formation of the collapse feature and reveal the rapid temporal evolution of both a large subglacial air cavity and the associated subglacial water channels. To further test the capabilities of the drone-based GPR system in challenging environments, the system was brought to the Canadian High-Arctic, onWard Hunt Island located at 83°N. After optimizing the system’s performance for this polar setting and testing its capabilities in comparison with a snowmobile-towed GPR system, 3D GPR datasets were acquired over the Ward Hunt ice rise and ice shelf. Key findings include the detailed detection of internal ice layers within the ice rise following the seabed topography, the identification of a seabed step below the northern ice shelf that may have strengthened its stability during previous collapse events, and the confirmation of a mirror-symmetry between surface and basal undulations on the western ice shelf that supports theories of plastic deformation driven by pressure forces. By enabling the acquisition of large-scale, high-density, and high-resolution 3D and 4D GPR data, while also facilitating surveys in previously inaccessible areas that conventional surface-based GPR methods could not reach, the developed drone-based GPR system offers significant new opportunities for future cryospheric research.
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.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 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 découle