Analysis of Iceberg Frequency in Labrador Sea Using Aerial Reconnaissance Flight Surveys and Satellite Radar Data
Bibliographic record
Abstract
Recently Nalcor announced the discovery of three newly defined hydrocarbon basins located primarily in deep water in the Labrador Sea, off the east coast of Newfoundland and Labrador, Canada. The basins are Henley, Chidley and Holton Basins and expanded the extent of the Hawke Basin. On behalf of Nalcor Energy, C-CORE recently completed the Offshore Newfoundland and Labrador Metocean Study which summarizes environmental conditions of these regions to support offshore petroleum exploration and development in the Labrador Sea and to outline the resource potential to the global oil and gas industry. Defining iceberg densities was one of the required tasks for the study. Among various environmental conditions, iceberg density is one of the most challenging parameter to define accurately both spatially and temporally. Aerial iceberg reconnaissance flight surveys provided by IIP (International Ice Patrol) and CIS (Canadian Ice Service) were studied, classified and analyzed to compute iceberg density (number of icebergs per square km). Only open water icebergs were considered for analysis because of the difficulty associated with reliably identifying icebergs in pack ice, which may lead to an underestimation of iceberg occurrence. Therefore, aerial reconnaissance data were compared with CIS pack ice charts to eliminate any possibility of iceberg sightings in pack ice being included in the analysis. Satellite radar data acquired using Envisat wide swath mode (WSM) imagery was also used for iceberg detections in order to provide full coverage of the study area. Again, sea ice was outlined in the imagery to ensure no targets in sea ice were counted. The WSM imagery provided a 400 km wide swath with an approximate radar resolution of 150 m, meaning smaller targets were not detected. In order to combine satellite radar data with aerial reconnaissance surveys a non-detection factor was calculated using a comparison of concurrent Envisat and aerial coverage to compensate for missed targets due to the coarser radar resolution. The resulting map of open water iceberg densities will provide a baseline for the region which shall be further refined through an on-going program using high-resolution Sentinel satellite data. Detailed descriptions of the analysis, procedures and results are presented in this paper. Areal density results of the newly defined basins are compared to the other frontier regions, where iceberg risks are higher.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 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".