Evidence map›Paper›PMID 35564574›Full record

ArticleInternational journal of environmental research and public health2022

A Method for Identifying the Spatial Range of Mining Disturbance Based on Contribution Quantification and Significance Test.

Chengye Zhang, Huiyu Zheng, Jun Li, Tingting Qin, Junting Guo, Menghao Du

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of environmental research and public health, 2022. 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
–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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Chengye ZhangCollege of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China.ORCID 0000-0002-4902-8704
Huiyu ZhengCollege of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China.
Jun LiCollege of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China.
Tingting QinCollege of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China.
Junting GuoState Key Laboratory of Water Resource Protection and Utilization in Coal Mining, Beijing 102209, China.
Menghao DuCollege of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying the spatial range of mining disturbance on vegetation is of significant importance for the plan of environmental rehabilitation in mining areas. This paper proposes a method to identify the spatial range of mining disturbance (SRMD). First, a non-linear and quantitative relationship between driving factors and fractional vegetation cover (FVC) was constructed by geographically weighted artificial neural network (GWANN). The driving factors include precipitation, temperature, topography, urban activities, and mining activities. Second, the contribution of mining activities (

Indexed as

Environmental MonitoringMiningChinaTemperaturedisturbance rangeenvironmentfractional vegetation coverGWANNmining area

Identifiers

PMID35564574
PMCPMC9103946

What OpenQuestion holds

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Read underepoch 390

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.