Evidence map›Paper›PMID 37833285›Full record

ArticleScientific reports2023

Spatiotemporal-based automated inundation mapping of Ramsar wetlands using Google Earth Engine.

Manish Kumar Goyal, Shivukumar Rakkasagi, Soumya Shaga, Tian C Zhang, Rao Y Surampalli, Saket Dubey

Open access · goldAbstract read
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
5.9field-weighted citation impact, top 3% of its field
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, 37 citations in OpenAlex.

  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

6 authors at 3 institutions in 2 countries.

Manish Kumar GoyalDepartment of Civil Engineering, Indian Institute of Technology, Indore, India. mkgoyal@iiti.ac.in.
Shivukumar RakkasagiDepartment of Civil Engineering, Indian Institute of Technology, Indore, India.
Soumya ShagaDepartment of Civil Engineering, Indian Institute of Technology, Indore, India.
Tian C ZhangDepartment of Civil and Environmental Engineering, University of Nebraska, Lincoln, NE, USA.
Rao Y SurampalliGlobal Institute for Energy, Environment, and Sustainability, Lenexa, KS, USA.
Saket DubeyDepartment of Civil Engineering, Indian Institute of Technology, Indore, India.
Indian Institute of Technology Indore · INInstitute for Global Environmental Strategies · USUniversity of Nebraska–Lincoln · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wetlands are one of the most critical components of an ecosystem, supporting many ecological niches and a rich diversity of flora and fauna. The ecological significance of these sites makes it imperative to study the changes in their inundation extent and propose necessary measures for their conservation. This study analyzes all 64 Ramsar sites in China based on their inundation patterns using Landsat imagery from 1991 to 2020. Annual composites were generated using the short-wave infrared thresholding technique from June to September to create inundation maps. The analysis was carried out on each Ramsar site individually to account for its typical behavior due to regional geographical and climatic conditions. The results of the inundation analysis for each site were subjected to the Mann-Kendall test to determine their trends. The analysis showed that 8 sites exhibited a significantly decreasing trend, while 14 sites displayed a significantly increasing trend. The accuracy of the analysis ranged from a minimum of 72.0% for Hubei Wang Lake to a maximum of 98.0% for Zhangye Heihe Wetland National Nature Reserve. The average overall accuracy of the sites was found to be 90.0%. The findings emphasize the necessity for conservation strategies and policies for Ramsar sites.

Identifiers

PMID37833285
PMCPMC10575872
OpenAlexW4387616620

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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.