Remotely Piloted Aircraft Systems (RPAS) for Monitoring Archaeological Sites in Nunavik in the Face of a Changing Climate
Bibliographic record
Abstract
Over the last century, remote sensing has proven effective in recognizing and studying cultural heritage in various geographic and chronological contexts, and the use of Remotely Piloted Aircraft Systems (RPAS) has become an integral part of archaeological research. In this paper, we explore the potential of RPAS equipped with photogrammetry and LiDAR sensors to identify archaeological features covered by vegetation and produce high-resolution models to document sites threatened by climate change (i.e., coastal erosion, forest fires, and shrubification). In 2023, we conducted remote sensing surveys at seven archaeological sites located in two different areas of Nunavik (Northern Québec, Canada), producing orthomosaics, Digital Surface and Terrain Models (DSMs and DTMs), and 3D models. The analysis of such products highlights the effectiveness of photogrammetry in recording sites affected by coastal erosion and features recently cleared by forest fires. In addition, we show that LiDAR sensors can help to locate archaeological features hidden by shrubs; however, in cases where the vegetation is exceptionally dense, even LiDAR struggles to identify anthropogenic features.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".