Geomorphological monitoring of a highly dynamic estuary using oblique aerial photographs
Bibliographic record
Abstract
Bad weather in many countries limits the use of optical satellite imageries in spatial and temporal monitoring of the environment. In this paper, a series of low-altitude oblique aerial photos taken on daily, weekly and monthly intervals were used to monitor the geomorphological changes in the upper part of the Mersey Estuary, northwestern England. This low-altitude aerial photo methodology reveals itself to be a satisfying compromise between cost, accuracy and difficulty of implementation. It offered a large amount of information on a spatial and temporal scale aiding in the understanding of channel mobility. This was an important consideration in the sitting and installation of new bridge pier foundations. This series of oblique aerial photos was used in a dynamic model to determine the migration of the ebb channel and was effective in identifying the main route of flow. Few uncertainties were encountered and the level of accuracy achieved in resolving these uncertainties in the images was in the range from 40 cm to a maximum of 1.7 m. This was compared with historical navigation charts and showed good correlation. Further applications are required to improve the quality of the data output from these images and the development of the technique.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".