Evidence map›Paper›PMID 42590538›Full record

ArticleSensors (Basel, Switzerland)2026

Mapping Drought Vulnerability in the Chi River Basin, Thailand: A Machine Learning Framework Using H3 Hexagonal Grids and Topographic Variables.

Narueset Prasertsri, Patiwat Littidej, Benjamabhorn Pumhirunroj, Donald Slack

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 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.

Narueset PrasertsriDepartment of Geoinformatics, Research Unit of Geoinformatics for Spatial Management, Faculty of Informatics, Mahasarakham University, Maha Sarakham 44150, Thailand.
Patiwat LittidejDepartment of Geoinformatics, Research Unit of Geoinformatics for Spatial Management, Faculty of Informatics, Mahasarakham University, Maha Sarakham 44150, Thailand.ORCID 0000-0002-1024-547X
Benjamabhorn PumhirunrojProgram in Animal Science, Faculty of Agricultural Technology, Sakon Nakhon Rajabhat University, Sakon Nakhon 47000, Thailand.ORCID 0009-0009-6607-5594
Donald SlackDepartment of Civil & Architectural Engineering & Mechanics, University of Arizona, 1209 E. Second St., Tucson, AZ 85721, USA.ORCID 0000-0003-0324-2163

Funding

Mahasarakham University 2-2569
6 · The paper itself

Abstract

Drought is a recurrent hazard in the Chi River Basin, northeastern Thailand, causing agricultural losses despite its low-lying floodplain setting. This study developed a machine learning framework integrating Sentinel-2 indices (SMI, NDVI, MNDWI, VCI, NDMI) and static spatial variables (DEM, TWI, prox2river, slope) aggregated to H3 hexagonal grids (≈5.96 km

Indexed as

AI and GIS integrationChi River Basindrought risk mappingH3 hexagonal gridLightGBMmachine learningMaha SarakhamSHAP analysistopographic controlsvulnerability assessment

Identifiers

PMID42590538
PMCPMC13469154

What OpenQuestion holds

Textmetadata
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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.