Evidence map›Paper›PMID 31805060›Full record

ArticlePloS one2019

Influence of traffic accessibility on land use based on Landsat imagery and internet map: A case study of the Pearl River Delta urban agglomeration.

Yongwei Liu, Xiaoshu Cao, Jianbin Xu, Tao Li

Abstract read
In one paragraph

Article in PloS one, 2019. 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.

Yongwei LiuSchool of Business, Ludong University, Yantai, Shandong, China.ORCID 0000-0002-6804-1875
Xiaoshu CaoSchool of Geography Science and Planning, Sun Yat-sen University, Guangzhou, Guangdong, China.
Jianbin XuSchool of Geography Science and Planning, Sun Yat-sen University, Guangzhou, Guangdong, China.
Tao LiInstitute of Transport Geography and Spatial Planning, Shaanxi Normal University, Xi'an, Shaanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Taking the Pearl River Delta urban agglomeration, with its rapid economic and social development and dramatic changes in land use, as an example with which to conduct this research, this paper analyzes the influence of traffic accessibility on land use and socioeconomic development by using Internet maps, points of interest (POI), and data about land use and socioeconomic development. The results of this study are as follows: (1) the calculation results of traffic accessibility can reflect the real situation because spatial distribution has an obvious feature of circle-like structure, and the development level of each township has high consistency; (2) major change characteristics in land use are that cultivated and forest lands are decreasing, and construction land is increasing, and it is obvious that the increase of construction land is featured by spatial autocorrelation and clusters of construction areas along the city borders; (3) traffic accessibility has a significant impact on land use status and changes and socioeconomic development, while the number of facilities has weak impact on land use, which is a reflection of advanced infrastructure in the urban agglomeration; and (4) the construction of transport infrastructure promotes the transformation of land use from water to construction land, therefore, more emphasis should be placed on protecting the river system in future infrastructure construction so as to improve the ecological benefits in the river basin.

Indexed as

Conservation of Natural ResourcesMaps as TopicRiversTransportationChinaEconomic DevelopmentHumansInternetSatellite ImageryTravelUrbanization

Identifiers

PMID31805060
PMCPMC6894779

What OpenQuestion holds

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LicenceCC BY
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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.