Craig Parker, Craig Mahlasi, Tamara Govindasamy, Lebohang Radebe, Nicholas Brian Brink, Christopher Jack, Madina Doumbia, Etienne Kouakou, Matthew Chersich, Guéladio Cissé, Sibusisiwe Makhanya
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Environmental indicators (Land Surface Temperature (LST), vegetation indices, and thermal field variance) were combined with socioeconomic and health variables (including indicators on crowded dwellings and healthcare access, self-reporting of chronic diseases) in a comprehensive vulnerability assessment. Principal Component Analysis revealed three primary dimensions explaining 56.6% (95% CI: 52.4-60.8%) of the total variance: urban heat exposure (31.5%), health status (12.8%), and socio-economic conditions (12.3%). Built-up areas showed weak but significant correlations with heat indices (ρ = 0.28, p < 0.01), while higher poverty levels demonstrated moderate positive correlations with LST (ρ = 0.41, p < 0.001). The spatial analysis identified significant clustering of vulnerability (Global Moran's I = 0.42, p < 0.001), with distinct high-vulnerability clusters in historically disadvantaged areas. Alexandra Township showed the highest vulnerability(HVI score: 0.87, LST: 29.8 °C ± 0.4 °C, NDVI: 0.08 ± 0.02), with factors characterising the high vulnerability in that area including limited healthcare access and extreme heat exposure. Northern suburbs formed a significant low-vulnerability cluster (Mean HVI = 0.23 ± 0.07, p < 0.001), benefiting from greater vegetation coverage and better healthcare access. These findings demonstrate how historical planning decisions continue to shape contemporary environmental health risks, with vulnerability concentrated in areas of limited healthcare access and high extreme heat exposure. Results suggest the need for targeted interventions that address both environmental and social dimensions of heat vulnerability, particularly focusing on expanding healthcare access in identified hotspots and implementing community-scale green infrastructure in high-risk areas. 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引用次数: 0
摘要
城市人口越来越容易受到极端高温事件的影响,特别是在快速城市化的全球南方城市,这些城市的环境暴露与社会经济不平等和有限的医疗保健机会交织在一起。本研究通过将高分辨率环境数据与135个城市病房的社会经济和健康指标相结合,量化了南非约翰内斯堡的热脆弱性。我们使用主成分分析和空间统计来研究历史城市发展模式如何影响当代脆弱性分布。在综合脆弱性评估中,将环境指标(地表温度、植被指数和热场方差)与社会经济和健康变量(包括拥挤住房和医疗保健可及性指标、慢性病自我报告)相结合。主成分分析显示,三个主要维度解释了总方差的56.6% (95% CI: 52.4-60.8%):城市热暴露(31.5%)、健康状况(12.8%)和社会经济状况(12.3%)。建成区与热指数呈微弱但显著的相关性(ρ = 0.28, p
Quantifying intra-urban socio-economic and environmental vulnerability to extreme heat events in Johannesburg, South Africa.
Urban populations face increasing vulnerability to extreme heat events, particularly in rapidly urbanising Global South cities where environmental exposure intersects with socioeconomic inequality and limited healthcare access. This study quantifies heat vulnerability across Johannesburg, South Africa, by integrating high-resolution environmental data with socio-economic and health metrics across 135 urban wards. We examine how historical urban development patterns influence contemporary vulnerability distributions using principal component analysis and spatial statistics. Environmental indicators (Land Surface Temperature (LST), vegetation indices, and thermal field variance) were combined with socioeconomic and health variables (including indicators on crowded dwellings and healthcare access, self-reporting of chronic diseases) in a comprehensive vulnerability assessment. Principal Component Analysis revealed three primary dimensions explaining 56.6% (95% CI: 52.4-60.8%) of the total variance: urban heat exposure (31.5%), health status (12.8%), and socio-economic conditions (12.3%). Built-up areas showed weak but significant correlations with heat indices (ρ = 0.28, p < 0.01), while higher poverty levels demonstrated moderate positive correlations with LST (ρ = 0.41, p < 0.001). The spatial analysis identified significant clustering of vulnerability (Global Moran's I = 0.42, p < 0.001), with distinct high-vulnerability clusters in historically disadvantaged areas. Alexandra Township showed the highest vulnerability(HVI score: 0.87, LST: 29.8 °C ± 0.4 °C, NDVI: 0.08 ± 0.02), with factors characterising the high vulnerability in that area including limited healthcare access and extreme heat exposure. Northern suburbs formed a significant low-vulnerability cluster (Mean HVI = 0.23 ± 0.07, p < 0.001), benefiting from greater vegetation coverage and better healthcare access. These findings demonstrate how historical planning decisions continue to shape contemporary environmental health risks, with vulnerability concentrated in areas of limited healthcare access and high extreme heat exposure. Results suggest the need for targeted interventions that address both environmental and social dimensions of heat vulnerability, particularly focusing on expanding healthcare access in identified hotspots and implementing community-scale green infrastructure in high-risk areas. This study provides an evidence-based framework for prioritising heat-resilience initiatives in rapidly urbanising Global South cities while highlighting the importance of addressing historical inequities in urban adaptation planning.
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