Dynamic Monitoring and Change Analysis of the Coastline with Remote Sensing in Zhongshan City
Bibliographic record
Abstract
Dynamic monitoring and change analysis of coastlines is of great research significance, which can provide a scientific basis and policymaking support for the sustainable development of the coastline economy and society. In this paper, ENVI and ArcGIS software were used to semi-automatically extracts the based on the normalized water body index of Zhongshan City from 1981 to 2019 in 8 phases, from Landsat series satellites and GF-1 satellite images. Then, we focus on analyzing the temporal and spatial evolution of coastlines of Zhongshan City quantitatively and qualitatively over the past 40 years. The study found that the coastline of Zhongshan City was significantly affected by human engineering activities, such as reclamation and aquaculture, engineering construction, and land-linked island projects. The total length of the coastline showed an increasing trend and the proportion of artificial coastlines increased year by year.
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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) | 0.000 | 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".