Mapping the topography and land cover of Sable Island
Bibliographic record
Abstract
In September 2014 the Applied Geomatics Research Group (AGRG) completed a third aerial mapping campaign of Sable Island. The AGRG first mapped the island in October 2002 with an aerial photography survey. Then in August 2009 AGRG conducted an aerial photography and Light Detection And Ranging (LiDAR) survey. Five years later these same technologies were deployed again. Each of these surveys led to an orthophoto mosaic of the island and a mapping of the land cover. The 2009 and 2014 surveys also mapped the island’s topography using Digital Surface Models (DSMs) derived from the LiDAR data. Ground-truthing efforts associated with each survey provided data to assist with the interpretation and validation of the results.The repeat surveys resulted in an excellent opportunity to quantify the topographic and land cover changes that have occurred on the island. The mapped results provide a comparison of how and where these changes have occurred over the years. AGRG is working with Parks Canada to better understand how the topography and land cover are changing. This understanding will contribute to Parks Canada Ecological Integrity monitoring program for Sable Island and inform the management planning process for one of Canada’s newest national parks.
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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 | 0.000 | 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".