Wetland Hydroperiod Analysis in Alberta Using InSAR Coherence Data
Bibliographic record
Abstract
Wetlands are dynamic environments, the water and vegetation of which can change considerably over time. Thus, it is important to investigate the hydroperiod status of wetlands using advanced techniques such as remote sensing technology. Wetland hydroperiod analysis has already been investigated using optical satellite and synthetic aperture radar (SAR) backscattering data. However, interferometric SAR (InSAR) coherence products have rarely been used for wetland hydroperiod mapping. Thus, this study utilized Sentinel-1 coherence maps produced between 2017 and 2020 (48 products) to map the wetland hydroperiod over the entire province of Alberta, Canada. It was observed that a coherence value of 0.45 was an optimum threshold value to discriminate flooded from non-flooded wetlands. Moreover, the results showed that most wetlands were inundated less than 50% of the time over these four years. Furthermore, most wetlands (~40%) were seasonally inundated, and there was a small percentage of wetlands (~5%) that were never flooded. Overall, the results of this study demonstrated the high capability of InSAR coherence products for wetland hydroperiod analysis. Several suggestions are provided to improve the results in future works.
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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 | 0.000 | 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 | 0.002 |
| 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 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".