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Record W2075379112 · doi:10.5539/jsd.v3n4p277

An Assessment of Recent Changes in the Niger Delta Coastline Using Satellite Imagery

2010· article· en· W2075379112 on OpenAlexvenueno aff
Jimmy Adegoke, Mofoluso Fageja, Godstime K. James, Ganiyu Agbaje, Temi Emmanuel Ologunorisa

Bibliographic record

VenueJournal of Sustainable Development · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsNiger deltaDeltaAccretion (finance)Satellite imagerySedimentRemote sensingCoastal erosionPhysical geographySatelliteErosionGeologyDeposition (geology)OceanographyEnvironmental scienceGeographyGeomorphology

Abstract

fetched live from OpenAlex

In Nigeria, there is dearth of studies on recent changes on accelerated marine processes along the national coastlines despite their importance as ports for navigation and marine commerce as well as a bridge for aquatic and terrestrial life.This study, which deals with a time series analysis of recent changes in the Niger Delta Coastline using Satellite Imagery is an attempt at filling this gap. Landsat TM images of 1986 and Landsat ETM+ of 2003 both covering the Niger Delta area of Nigeria were used for this study and the images were processed using Erdas Imagine Version 8.7 and Arc Info 9.1 for the GIS operations. The results of the analyses show among other things that coastline erosion was dominant over accretion of sediment deposition. Also that the total area of observed changes along the coastlines was 46.535sq.km. Of this, 27.65sq.km (59.43%) constitutes eroded area, and 40.57% representing 18.88sq.km of the area showed coastal sediment accretion.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.274
Teacher spread0.257 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations54
Published2010
Admission routes1
Has abstractyes

Explore more

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