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Record W2141257886 · doi:10.5589/m10-053

Mapping changing temperature patterns over a glacial moraine using oblique thermal imagery and lidar

2010· article· en· W2141257886 on OpenAlexvenueno aff
Chris Hopkinson, John Barlow, Michael N. Demuth, John W. Pomeroy

Bibliographic record

VenueCanadian Journal of Remote Sensing · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersAustralian Government
KeywordsMoraineLidarDebrisOrthophotoDigital elevation modelRemote sensingGeologySnowSnowmeltElevation (ballistics)Glacial periodGeomorphology

Abstract

fetched live from OpenAlex

AbstractDue to access difficulties in active alpine moraine environments, it can be challenging to accurately map and quantify debris cover and ice-core extent. To aid in identifying the presence and extent of ice-cored moraine, a non-invasive method of mapping spatial and temporal moraine temperature patterns using a light detection and ranging (lidar) digital elevation model (DEM) and sequences of oblique thermal imagery was evaluated. A procedure of lidar DEM-based orthorectification of thermal images collected through time from different locations enabled maps of temperature change to be generated and thermal signatures plotted. Although no exposed ice was visible on the moraine slope studied, the presence of shallow ice core beneath the debris-covered surface was inferred in areas of cooler temperatures during daylight solar heating and rapid thermal decay after sunset. It is presumed that this apparent increased heat loss in some areas of the moraine is being used to drive internal melt processes. It is believed that such temporal thermal imaging at high repetition frequency will aid in remotely mapping the presence of buried ice and, with the combination of energy balance data and further field validation, could enable the estimation of debris cover depth.En raison des difficultés d'accès dans les environnements de moraines alpines actives, il peut être difficile de cartographier et de quantifier de façon précise le couvert de débris et l'étendue du noyau de glace. Afin de faciliter l'identification de la présence et de l'étendue des moraines à noyau de glace, on a évalué une méthode non invasive de cartographie des patrons spatiaux et temporels des températures de moraines à l'aide d'un MNE dérivé des données lidar et des séquences d'images thermiques en oblique. Une procédure d'orthorectification basée sur un MNE dérivé des données lidar d'images thermiques acquises dans le temps à partir de différentes localisations a permis de générer des cartes de changements des températures et de tracer des signatures thermiques. Bien qu'aucune glace exposée n'ait été visible sur le versant de moraine étudié, la présence de noyaux de glace peu profonds sous la surface recouverte de débris a pu être déduite dans les zones de températures plus froides durant la période de réchauffement solaire diurne et de décroissance thermique rapide après le coucher du soleil. On présume que cette perte de chaleur apparente accrue dans certaines zones de la moraine sert à conduire les processus de fonte interne. On croit que de telles images thermiques temporelles à des fréquences de répétition élevées faciliteront la cartographie par télédétection de la présence de glace enfouie et, en combinaison avec les données du bilan d'énergie et de validation additionnelle sur le terrain, pourraient permettre d'estimer l'épaisseur du couvert de débris.[Traduit par la Rédaction]

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.203
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2010
Admission routes1
Has abstractyes

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