Evidence map›Paper›PMID 37587193›Full record

ArticleScientific reports2023

Assessing demographic and economic vulnerabilities to sea level rise in Bangladesh via a nighttime light-based cellular automata model.

Bijoy Mitra, Syed Masiur Rahman, Mohammed Sakib Uddin, Khaled Mahmud, Md Kamrul Islam, Md Arifuzzaman, M M Hafizur Rahman, Muhammad Muhitur Rahman

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In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

8 authors.

Bijoy MitraDepartment of Geography and Environmental Studies, University of Chittagong, Chittagong, 4331, Bangladesh.
Syed Masiur RahmanApplied Research Center for Environment and Marine Studies, Research Institute, King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia.
Mohammed Sakib UddinDepartment of Geography and Environmental Studies, University of Chittagong, Chittagong, 4331, Bangladesh.
Khaled MahmudDepartment of Geography and Environmental Studies, University of Chittagong, Chittagong, 4331, Bangladesh.
Md Kamrul IslamDepartment of Civil and Environmental Engineering, College of Engineering, King Faisal University, 31982, Al-Ahsa, Saudi Arabia.
Md ArifuzzamanDepartment of Civil and Environmental Engineering, College of Engineering, King Faisal University, 31982, Al-Ahsa, Saudi Arabia.
M M Hafizur RahmanDepartment of Communication and Networking, College of Computer and Information Sciences, King Faisal University, 31982, Al-Ahsa, Saudi Arabia.
Muhammad Muhitur RahmanDepartment of Civil and Environmental Engineering, College of Engineering, King Faisal University, 31982, Al-Ahsa, Saudi Arabia. mrahman@kfu.edu.sa.

Funding

Deanship of Scientific Research, King Faisal University GRANT 3568
6 · The paper itself

Abstract

The Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6) forecasts a sea level rise (SLR) of up to 2 m by 2100, which poses significant risks to regional geomorphology. As a country with a rapidly developing economy and substantial population, Bangladesh confronts unique challenges due to its extensive floodplains and 720 km-long Bay of Bengal coastline. This study uses nighttime light data to investigate the demographic repercussions and potential disruptions to economic clusters arising from land inundation attributable to SLR in the Bay of Bengal. By using geographical information system (GIS)-based bathtub modeling, this research scrutinizes potential risk zones under three selected shared socioeconomic pathway (SSP) scenarios. The analysis anticipates that between 0.8 and 2.8 thousand km

Identifiers

PMID37587193
PMCPMC10432505

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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.