Evidence map›Paper›PMID 38407649›Full record

ArticleEnvironmental monitoring and assessment2024

Image-based vegetation analysis of desertified area by using a combination of ImageJ and Photoshop software.

Jin Tong, Longying Wu, Bin Li, Nan Jiang, Jin Huang, Di Wu, Lihong Zhou, Qingwen Yang, Yuan Jiao, Ji Chen and 2 more

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Article in Environmental monitoring and assessment, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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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

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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.

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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

12 authors.

Jin Tong *College of Ecology and Environment, Chengdu University of Technology, Chengdu, 610059, Sichuan, China.
Longying Wu *College of Ecology and Environment, Chengdu University of Technology, Chengdu, 610059, Sichuan, China.
Bin Li *Chengdu Jinkai Bioengineering Co., Ltd., Chengdu, 611130, Sichuan, China.
Nan Jiang *College of Ecology and Environment, Chengdu University of Technology, Chengdu, 610059, Sichuan, China.
Jin HuangCollege of Ecology and Environment, Chengdu University of Technology, Chengdu, 610059, Sichuan, China. huangjin18@cdut.edu.cn.
Di WuCollege of Ecology and Environment, Chengdu University of Technology, Chengdu, 610059, Sichuan, China.
Lihong ZhouCollege of Ecology and Environment, Chengdu University of Technology, Chengdu, 610059, Sichuan, China.
Qingwen YangCollege of Ecology and Environment, Chengdu University of Technology, Chengdu, 610059, Sichuan, China.
Yuan JiaoCollege of Ecology and Environment, Chengdu University of Technology, Chengdu, 610059, Sichuan, China.
Ji ChenCollege of Agronomy, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
Ke ZhaoCollege of Resources, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
Xiangjun PeiState Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, Sichuan, China. peixj0119@tom.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fractional vegetation cover (FVC) is a crucial indicator to estimate degradation and desertification for grasslands. However, traditional small-scale FVC analysis methods, such as visual estimation and point-sampling, are cumbersome and imprecise. Innovative methods like image-based FVC analysis methods, while accurate, face challenges such as complex analytical procedures and the necessary training for operations. Therefore, in this study, a combined application of ImageJ and Photoshop was employed to achieve a more effective analysis of FVC values in desertification areas. Our results showed that the FVC results obtained by combination of Photoshop and ImageJ were dependable and precise (R

Indexed as

Environmental MonitoringImage Processing, Computer-AssistedSoftwareBackground noiseCombined analysisDistorted imagesFractional vegetation cover

Identifiers

PMID38407649

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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.