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Int J Environ Res Public Health. 2018 Nov 9;15(11). pii: E2516. doi: 10.3390/ijerph15112516.

A Raster-Based Subdividing Indicator to Map Urban Heat Vulnerability: A Case Study in Sydney, Australia.

Author information

1
School of Geographical Sciences, Southwest University, Chongqing 400715, China. zwei1997@swu.edu.cn.
2
Research Center of Urban and Regional Planning in Southwest China, Chongqing 400715, China. zwei1997@swu.edu.cn.
3
School of Geosciences, The University of Sydney, Camperdown, NSW 2006, Australia. phil.mcmanus@sydney.edu.au.
4
School of Geosciences, The University of Sydney, Camperdown, NSW 2006, Australia. elizabeth.duncan@sydney.edu.au.

Abstract

Assessing and mapping urban heat vulnerability has developed significantly over the past decade. Many studies have mapped urban heat vulnerability with a census unit-based general indicator (CGI). However, this kind of indicator has many problems, such as inaccurate assessment results and lacking comparability among different studies. This paper seeks to address this research gap and proposes a raster-based subdividing indicator to map urban heat vulnerability. We created a raster-based subdividing indicator (RSI) to map urban heat vulnerability from 3 aspects: exposure, sensitivity and adaptive capacity. We applied and compared it with a raster-based general indicator (RGI) and a census unit-based general indicator (CGI) in Sydney, Australia. Spatial statistics and analysis were used to investigate the performance among those three indicators. The results indicate that: (1) compared with the RSI framework, 67.54% of very high heat vulnerability pixels were ignored in the RGI framework; and up to 83.63% of very high heat vulnerability pixels were ignored in the CGI framework; (2) Compared with the previous CGI framework, a RSI framework has many advantages. These include more accurate results, more flexible model structure, and higher comparability among different studies. This study recommends using a RSI framework to map urban heat vulnerability in the future.

KEYWORDS:

Sydney; demography; heat vulnerability; indicators; mapping; public health

PMID:
30423999
PMCID:
PMC6266879
DOI:
10.3390/ijerph15112516
[Indexed for MEDLINE]
Free PMC Article

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