Evidence map›Paper›PMID 39381212›Full record

ArticleHeliyon2024

A generalized machine learning model for long-term coral reef monitoring in the Red Sea.

Justin J Gapper, Surendra Maharjan, Wenzhao Li, Erik Linstead, Surya P Tiwari, Mohamed A Qurban, Hesham El-Askary

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Justin J GapperEarth Systems Science and Data Solutions Lab, Chapman University, Orange, CA, 92866, USA.
Surendra MaharjanEarth Systems Science and Data Solutions Lab, Chapman University, Orange, CA, 92866, USA.
Wenzhao LiEarth Systems Science and Data Solutions Lab, Chapman University, Orange, CA, 92866, USA.
Erik LinsteadFowler School of Engineering, Chapman University, Orange, CA, 92866, USA.
Surya P TiwariCenter for Environment and Water, The Research Institute, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, 31261, Saudi Arabia.
Mohamed A QurbanNational Center for Wildlife, Saudi Arabia.
Hesham El-AskaryEarth Systems Science and Data Solutions Lab, Chapman University, Orange, CA, 92866, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coral reefs, despite covering less than 0.2 % of the ocean floor, harbor approximately 35 % of all known marine species, making their conservation critical. However, coral bleaching, exacerbated by climate change and phenomena such as El Niño, poses a significant threat to these ecosystems. This study focuses on the Red Sea, proposing a generalized machine learning approach to detect and monitor changes in coral reef cover over an 18-year period (2000-2018). Using Landsat 7 and 8 data, a Support Vector Machine (SVM) classifier was trained on depth-invariant indices (DII) derived from the Gulf of Aqaba and validated against ground truth data from Umluj. The classifier was then applied to Al Wajh, demonstrating its robustness across different sites and times. Results indicated a significant decline in coral cover: 11.4 % in the Gulf of Aqaba, 3.4 % in Umluj, and 13.6 % in Al Wajh. This study highlights the importance of continuous monitoring using generalized classifiers to mitigate the impacts of environmental changes on coral reefs.

Indexed as

ClassificationLandsatMachine learningSpatiotemporal coral change analysisSVM

Identifiers

PMID39381212
PMCPMC11458965

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.