A multi-sensor remote sensing approach for monitoring large wetland complexes in northern Canada
Bibliographic record
Abstract
The Peace-Athabasca Delta is a 3900 km/sup 2/ freshwater wetland complex, located in north-eastern Alberta, Canada. The intricate channel system, the numerous smaller wetland basins and the large shallow lakes of the delta are important habitats for a large number of migrating waterfowl, mammals and insects. The hydrological regime in this remote area is unique as many of the productive wetland are isolated from the channels and require overland floods to be replenished. Recent studies have shown that the delta has experienced a reduced frequency of these large overland floods. Attribution of these changes is complex, however, remote sensing provides a unique opportunity to characterise the spatio-temporal distribution of these changes and to collect important baseline hydrological information that is too difficult to obtain using traditional methods. This paper focuses on a development of a multi-sensor remote sensing strategy to assess hydrological change in this wetland environment. This includes the use of Radarsat, Landsat, IKONOS and lidar data to derive year to year changes and assist in predicting future outcomes and risks for this ecosystem.
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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".