Evidence map›Paper›PMID 32403250›Full record

ArticleSensors (Basel, Switzerland)2020

Street-Scale Analysis of Population Exposure to Light Pollution Based on Remote Sensing and Mobile Big Data-Shenzhen City as a Case.

Bo Sun, Yang Zhang, Qiming Zhou, Duo Gao

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. 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. Urban Food Takeaway Vitality: A New Technique to Assess Urban Vitality.International journal of environmental research and public health · 2021
    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.

Bo SunShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Yang ZhangShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Qiming ZhouShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.ORCID 0000-0003-0934-0602
Duo GaoTalkingData Co., Ltd., Beijing 100027, China.

Funding

Hong Kong Baptist University Faculty Research Grant FRG2/17-18/030National Natural Science Foundation of China 41971386
6 · The paper itself

Abstract

Most studies on light pollution are based on light intensity retrieved from nighttime light (NTL) remote sensing with less consideration of the population factors. Furthermore, the coarse spatial resolution of traditional NTL remote sensing data limits the refined applications in current smart city studies. In order to analyze the influence of light pollution on populated areas, this study proposes an index named population exposure to light pollution (PELP) and conducts a street-scale analysis to illustrate spatial variation of PELP among residential areas in cites. By taking Shenzhen city as a case, multi-source data were combined including high resolution NTL remote sensing data from the Luojia 1-01 satellite sensor, high-precision mobile big data for visualizing human activities and population distribution as well as point of interest (POI) data. Results show that the main influenced areas of light pollution are concentrated in the downtown and core areas of newly expanded areas with obvious deviation corrected like traditional serious light polluted regions (e.g., ports). In comparison, commercial-residential mixed areas and village-in-city show a high level of PELP. The proposed method better presents the extent of population exposure to light pollution at a fine-grid scale and the regional difference between different types of residential areas in a city.

Indexed as

Environmental MonitoringLightRemote Sensing TechnologyBig DataCitiesEnvironmental ExposureEnvironmental PollutionHumanslight pollutionLuojia 1-01NTL remote sensingpopulation exposure to light pollutionresidential area

Identifiers

PMID32403250
PMCPMC7248970

What OpenQuestion holds

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LicenceCC BY
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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.