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Record W4405388883 · doi:10.62051/3cmhbd41

Spatiotemporal Analysis of the Bohai Sea Coastline Based on GIS and Remote Sensing

2024· article· en· W4405388883 on OpenAlexaff

Bibliographic record

VenueTransactions on Environment Energy and Earth Sciences · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Changes in China
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRemote sensingOceanographyGeologyEnvironmental science

Abstract

fetched live from OpenAlex

In recent years, the Bohai coastline has undergone significant changes. Due to sea reclamation and harbor construction driven by industrialization, the coastline has expanded significantly, bay areas have shrunk, and the types of coastal land use experienced huge changes. These alterations pose threats to the stability of coastal ecosystems. Remote sensing plays a crucial role in monitoring the spatiotemporal changes of coastlines, providing high-resolution images that are indispensable for coastal analysis. Based on remote sensing and GIS methods, this paper will analyze the spatiotemporal changes of the coastline from 1986 to 2016, identifying the drivers behind these changes. The study focuses on three main factors: coastline change, bay area change and land-use type change. It finds an increase of 1102.77 km in coastline length, a decrease of 1824 km² in the bay area, and a gradual replacement of natural shorelines with artificial ones and constructed lands, leading to severe degradation of coastal mudflat wetlands. These changes have resulted in impaired ecosystem services, habitat loss, and reduced biodiversity, threatening the stability of the coastal ecosystem.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.216
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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