Evidence map›Paper›PMID 40676004›Full record

ArticleScientific data2025

A Global Multi-Sensor Dataset of Surface Water Indices from Landsat-8 and Sentinel-2 Satellite Measurements.

Yohei Miura, Mohammad Shamsudduha, Anawat Suppasri, Daisuke Sano

Abstract read
In one paragraph

Article in Scientific data, 2025. 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

4 authors.

Yohei MiuraDepartment of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Aoba 6-6-06, Aramaki, Aoba-ku, Sendai, Miyagi, 980-8579, Japan.ORCID http://orcid.org/0000-0003-2355-8296
Mohammad ShamsudduhaDepartment of Risk and Disaster Reduction, University College London, Gower Street, London, WC1E 6BT, UK. m.shamsudduha@ucl.ac.uk.
Anawat SuppasriInternational Research Institute of Disaster Science, Tohoku University, Aoba 468-1, Sendai, Miyagi, 980-8572, Japan.
Daisuke SanoDepartment of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Aoba 6-6-06, Aramaki, Aoba-ku, Sendai, Miyagi, 980-8579, Japan. daisuke.sano.e1@tohoku.ac.jp.

Funding

MEXT | Japan Society for the Promotion of Science (JSPS) 23KJ0182
6 · The paper itself

Abstract

Spatiotemporal mapping of surface water extent constitutes a valuable dataset for the management of water resources, the monitoring of flood- and drought-affected areas, and the conservation of wetlands and freshwater ecosystems. Surface water indices, derived from optical satellite data, serve as effective indicators for estimating surface water coverage. However, global-scale datasets featuring high-resolution surface water mapping using multiple water indices remain scarce and constrained in temporal and spatial scope. Here, we present monthly surface-water maps derived from three water indices, Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), and Water Index 2015 (WI2015), utilizing high-resolution earth observation satellite data from Landsat-8 and Sentinel-2 for the period January 2019 to December 2021. These maps will be regularly updated as new satellite data become available. These water index mappings provide a baseline for projecting the distribution of surface-water resources and deliver critical information for the sustainable management of surface water resources under the challenges posed by the global climate change.

Identifiers

PMID40676004
PMCPMC12271537

What OpenQuestion holds

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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.