Satellite Reveals the Accelerated Coastline Erosion of Sydney’s Sandy Beaches Since the 21st Century
Bibliographic record
Abstract
Coastline change serves as a crucial indicator of environmental changes in coastal areas. By utilizing Landsat imagery time series from 2000 to 2022, we integrated the Modified Normalized Water Index, Support Vector Machine supervised classifier, and the Digital Coastline Analysis System to track coastline changes in Sydney’s sandy beaches over 2000-2022, and analyzed the potential factors. Since the beginning of the 21st century, Sydney’s sandy beaches exhibited an erosion trend of −0.17 m/a, resulting in a net coastline movement of −6.84 m, with over 80% of the coastline experiencing erosion. Before 2010, the sandy beaches, on average, accreted at a rate of 0.40 m/a. Then, from 2010 to 2019, the average beach accretion slowed down (0.07 m/a), with some beaches showing an erosion trend. However, after 2019, sandy coastline erosion in Sydney has greatly accelerated, with an average rate of −4.81 m/a. The primary factors influencing the spatial-temporal patterns of Sydney’s sandy coastline include sea level height, significant wave height, and storm events. This study provides valuable insights into the sustainable management and protection of sandy beaches, disaster response planning, and the sustainable development of coastal areas.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".