Evidence map›Paper›PMID 29801488›Full record

ArticleInternational journal of health geographics2018

Spatially explicit assessment of heat health risk by using multi-sensor remote sensing images and socioeconomic data in Yangtze River Delta, China.

Qian Chen, Mingjun Ding, Xuchao Yang, Kejia Hu, Jiaguo Qi

Abstract read
In one paragraph

Article in International journal of health geographics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Variations of Urban Thermal Risk with Local Climate Zones.International journal of environmental research and public health · 2023
    Article
  7. Article
  8. Article
  9. A Raster-Based Subdividing Indicator to Map Urban Heat Vulnerability: A Case Study in Sydney, Australia.International journal of environmental research and public health · 2018
    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

5 authors.

Qian ChenInstitute of Island and Coastal Ecosystems, Ocean College, Zhejiang University, Zhoushan, 316021, China.
Mingjun DingKey Lab of Poyang Lake Wetland and Watershed Research of Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang, 330022, China.
Xuchao YangInstitute of Island and Coastal Ecosystems, Ocean College, Zhejiang University, Zhoushan, 316021, China. yangxuchao@zju.edu.cn.ORCID 0000-0002-8130-7447
Kejia HuInstitute of Island and Coastal Ecosystems, Ocean College, Zhejiang University, Zhoushan, 316021, China.
Jiaguo QiInstitute of Island and Coastal Ecosystems, Ocean College, Zhejiang University, Zhoushan, 316021, China.

Funding

National Natural Science Foundation of China 41371068National Natural Science Foundation of China 41671035
6 · The paper itself

Abstract

backgroundThe increase in the frequency and intensity of extreme heat events, which are potentially associated with climate change in the near future, highlights the importance of heat health risk assessment, a significant reference for heat-related death reduction and intervention. However, a spatiotemporal mismatch exists between gridded heat hazard and human exposure in risk assessment, which hinders the identification of high-risk areas at finer scales.

methodsA human settlement index integrated by nighttime light images, enhanced vegetation index, and digital elevation model data was utilized to assess the human exposure at high spatial resolution. Heat hazard and vulnerability index were generated by land surface temperature and demographic and socioeconomic census data, respectively. Spatially explicit assessment of heat health risk and its driving factors was conducted in the Yangtze River Delta (YRD), east China at 250 m pixel level.

resultsHigh-risk areas were mainly distributed in the urbanized areas of YRD, which were mostly driven by high human exposure and heat hazard index. In some less-urbanized cities and suburban and rural areas of mega-cities, the heat health risks are in second priority. The risks in some less-developed areas were high despite the low human exposure index because of high heat hazard and vulnerability index.

conclusionsThis study illustrated a methodology for identifying high-risk areas by combining freely available multi-source data. Highly urbanized areas were considered hotspots of high heat health risks, which were largely driven by the increasing urban heat island effects and population density in urban areas. Repercussions of overheating were weakened due to the low social vulnerability in some central areas benefitting from the low proportion of sensitive population or the high level of socioeconomic development. By contrast, high social vulnerability intensifies heat health risks in some less-urbanized cities and suburban areas of mega-cities.

Indexed as

RiversAgedChinaCitiesClimate ChangeData AnalysisEnvironmental ExposureEnvironmental MonitoringExtreme HeatFemaleHot TemperatureHumansMaleMiddle AgedRemote Sensing TechnologyRisk AssessmentGISHeat health riskRemote sensingSpatial risk assessmentYangtze River Delta

Identifiers

PMID29801488
PMCPMC5970500

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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.