Selection of emergency logistics facility locations considering major natural disasters in mountainous cities based on GIS-MCDM.

Yusen Lin, Yong Xiang, Hao Yin, Zeyou Chen

Abstract read

In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Yusen LinSchool of Architecture and Civil Engineering, Xihua University, Chengdu, 610039, China.

Yong XiangSchool of Architecture and Civil Engineering, Xihua University, Chengdu, 610039, China.

Hao YinSchool of Architecture and Civil Engineering, Xihua University, Chengdu, 610039, China.

Zeyou ChenSchool of Architecture and Civil Engineering, Xihua University, Chengdu, 610039, China. 0119940033@xhu.edu.cn.

Funding

Research Centre for Social Development and Social Risk Control, Key Research Bases of Philosophy and Social Sciences of Sichuan Province SR23A05

6 · The paper itself

Abstract

The rising frequency of extreme natural disasters under global climate change presents significant uncertainty and safety challenges for emergency logistics facility planning, particularly in mountainous regions. Addressing the limitations of traditional location studies that often overlook terrain complexity and disaster risks, this study proposes an integrated framework for mountainous emergency logistics site selection, combining Geographic Information Systems (GIS) spatial analysis with Multi-Criteria Decision-Making (MCDM) methods. Using 88 counties and districts in Guizhou Province as a case study, the framework incorporates four criterion-level dimensions and eight indicator-level factors, and employs GIS spatial analysis alongside a hybrid BWM-EWM weighting scheme and an improved TOPSIS evaluation to generate a suitability map. Sensitivity analysis confirms the robustness of the model. The results reveal an east-strong-west-weak spatial pattern of suitability, with population density and transportation accessibility as dominant factors, terrain imposing fundamental constraints, and natural disaster risk providing critical differentiation for decision-making.

Indexed as

Emergency logisticsFacility sitingMulti-criteria decision-making (MCDM)Natural disasters in mountainous areasSite selection

Identifiers

PMID41803241

DOI10.1038/s41598-026-43065-y

PMCPMC13056903

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

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Registered trials

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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.