Dune monitoring: implementing remote sensing techniques
Bibliographic record
Abstract
There is an increasing interest for different methodological and conceptual approaches applied in geomorphology. Data collection is becoming more and more efficient, and from remote sensing techniques to the use of very precise anemometry instrumentation, the way in which we sample nature improves our ability to subsequently understand it. However, there are a number of issues associated with the different temporal/spatial scales, and the absence of high-quality data of dune dynamics over long periods keeps holistic approaches away from numerical modeling. The work presented here explores the applicability of remote sensing techniques to the study of coastal dunes, and its potential in establishing links between factors acting at different temporal scales. The monitoring station is located at Greenwich Dunes, PEI National Park, PEI (Canada). We have deployed three cannon digital cameras on a 6m mast on top of an 8m foredune crest, each taking hourly exposures during daylight hours. A 2D sonic anemometer mounted at the top of the mast provides continuous record of wind speed and direction. Sediment transport and deposition/erosion processes are measured using a set of Sabatech saltation probes and pins permanently deployed at the backshore area and at the base of the foredune. Through a combination of ArcMap 9.2 and PCI Geomatica tools the pictures are analyzed following a procedure of several steps, such as image rectification or camera calibration for measuring surface moisture content on the beach surface. The result is a large database including time series of wind speed and direction, transport processes, moisture maps, vegetation cover, shoreline position, fetch distances, and other factors involved in the aeolian system at Greenwich. This database is a primary source of information where the aeolian system at Greenwich can be queried in an easy way, and the basis for subsequent modeling. The monitoring of the magnitude, frequency, and timing of events that deliver sediment to the dune will allow us to understand the relative importance of different variables and events. The overall goal is to assess the applicability of remote sensing techniques in measuring beach/dune aeolian processes, and advance our knowledge in the factors affecting foredune evolution to better assist management projects.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".