Effect of radar frequency on waterline mapping from airborne SAR image in the intertidal zone
Bibliographic record
Abstract
Discrepancy of waterline extracted from L- and P-band airborne SAR images was investigated in the intertidal zone through the field measurements and theory of SAR imaging mechanism. In the intertidal zone which has low slope, the Bragg waves resonant with each radar frequency can reside in different depth of surf zone, resulting in the boundary between water and land can be mapped differently in SAR images. I. INTRODUCTION Most large modern cities are located in coastal zones. It is essential to map and monitor changes in waterlines in a timely. Airborne or space-borne synthetic aperture radar (SAR) image provide an efficient aid to monitor and map the waterlines due to high resolution synoptic views of water extent. The west and south coast of the Korean Peninsula is famous for its large tidal range and vast tidal flats. Continuous observation of waterline is highly required in these areas. The extraction of waterlines from SAR images has been studied (1-5). Most of these studies were based on gray level thresholding, segmentation or tracing along the boundary between land and water directly shown in SAR images. However, images of waterlines generated by SAR suffer from a number of speckle effect and meteorological conditions. The return from the wind roughened and wave modulated water can frequently equal or exceed the return from a nearby land area, resulting in inadequate contrast for unambiguous separation. Furthermore, waterline itself estimated from SAR images can vary depending on the sea surface states. Radar frequency or wavelength is important parameter in ocean SAR imaging. Different radar frequency of signal will interact with different length of ocean waves - Bragg scattering (6-8). In the coastal region, the water depth is shallow and rapidly changing, and surface waves can feel the bottom, causing breaking waves. The interaction of these breaking waves with radar signals is extremely complex and very difficult to model. The means by which waves break depends on the nature of the bottom and the characteristics of the wave. For very mildly sloping beaches like tidal flat, typically the waves are spilling breakers - numerous waves occur within the surf zone and these waves begin to lose their energy through friction with the bottom (9). In this paper, we investigate the characteristics of (breaking) surface waves in surf zone in order to explain the discrepancy of waterlines extracted from multiple frequency SAR data in intertidal zone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 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".