How sensitive are sediment dispersal and sea surface temperature to changing wind conditions? \nA mapping approach in the coastal waters of Herschel Island, Yukon Territory, Canada, using Landsat (TM, ETM+ and OLI/TIRS) satellite image data from 1986 to 2016.
Bibliographic record
Abstract
The Arctic is subject to substantial changes due to the greenhouse gas induced climate change. Ground temperatures and river discharge are rising, (permafrost) coasts are eroded and the carbon stored in them is released. The aforementioned factors contribute suspended sediment to the Arctic shelves which represent an uncertainty regarding future ecological and geological reactions. In order to increase the understanding of the development of Arctic shelves due to the changes described, this Master’s thesis presents a mapping approach of sediment dispersal and sea surface temperature (SST) in the coastal and nearshore zone of Herschel Island on the Canadian Beaufort Shelf. \nIn this regard, 30 years of Landsat satellite imagery were analyzed and interpreted under different seasonal wind conditions (E and NW wind). Due to the absence of in-situ measurements to calibrate the spectral data, proxys were chosen for both values to receive a relative overview of the study area: the surface reflectance of the red band (655 nm) for turbidity (which acts as proxy for sediment dispersal) and at-sensor (uncorrected) temperature from thermal infrared channels (10,4–12,5 µm) for SST. For scenes with similar wind conditions, the mean was calculated, resulting in a very good representation over the observation period. \nDuring stable E wind conditions, the mean values of both turbidity and SST were higher than during NW wind conditions. This may result from the influence of the Mackenzie River Plume, distributing suspended sediment and fresh water over the Canadian Beaufort Shelf during stable E wind conditions. The low values during stable NW wind conditions indicate that the sediment and fresh water input from other sources than the Mackenzie River to the Canadian Beaufort Shelf are of minor importance compared to it. Turbidity shows large gradients from the nearshore to the offshore zone, indicating that large parts of the suspended sediment are deposited and transported in the nearshore zone. SST does not have such a strong gradient; however, upwelling causes large differences at ne NE coast of Herschel Island during stable E wind conditions. \nThe resulted values have been compared to other modelling approaches to assess the magnitude of absolute values representing the reflectance values. Modelling turbidity and SPM after Nechad et al. (2009, 2010) results in values of 20 - 30 FTU and 10 – 30 g/m³ along the coast, respectively. These values are in good agreement with SPM modelling from Doxaran et al. (2012). \nLimitations of the presented modelling method are the low temporal resolution of Landsat satellites of 16 days and the atmospheric correction to surface reflection due to the low radiometric resolution of the older Landsat satellite sensors. While newer sensors such as Landsat 8 (OLI) and Sentinel 2 can overcome the last limitation, the temporal resolution is still a limitation for high resolution ocean color remote sensing. With the calibration of the spectral data with in-situ measurements, this model is expected to derive consistent SPM concentration and SST data for the whole Canadian Beaufort Shelf.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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 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".