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

Heat health assessment and risk simulation prediction in eastern China: a geospatial analysis

Background

High temperatures pose significant health risks and societal challenges in China, with spatial variations in heat health risks. Furthermore, due to the constraint imposed by heat health risk assessment on the construction of the public health security framework, it is necessary to explore the heat health risk pattern of spatial distribution and the trend of future risk development in eastern China.

Methods

Based on the Intergovernmental Panel on Climate Change (IPCC) and Risk Triangle framework which is combined with natural and socio-economic factors, the heat health risk assessment index system of eastern China is established in this paper. This paper enhances the accuracy of risk maps with the aid of high-resolution imagery. It also focuses specifically on the exposure of construction workers in urban areas and agricultural workers in rural areas. This paper also evaluates the heat health risk of eastern China from 2010 to 2019 by using ArcGIS and the CA-Markov model.

Results

The heat health risk in most areas of eastern China is predominantly highest risk, with the proportion of highest and medium risk areas increasing steadily from 2010 to 2019. The spatial distribution pattern reveals that high-risk areas are concentrated in the central urban areas, while low-risk areas are primarily in the mountainous regions, suburbs, rural areas, and water source areas. The conversion of heat health risk areas mainly occurs between adjacent levels, with no mutation process. From 2010 to 2025, the heat health risk of eastern China has been improving, and the overall distribution pattern of risk levels remains consistent.

Conclusion

The research findings provide a basis for us to gain a deeper understanding of the vulnerability of different groups. This study not only presents spatial distribution maps of health risks, but offers a new perspective for us to comprehend the complexity and diversity of these risks. The research findings also establish a foundation for optimizing monitoring and warning systems. Furthermore, this study provides scientific evidence for policymakers to develop comprehensive heatwave mitigation plans. Nevertheless, we must acknowledge the limitations of the research and recognize that there is room for improvement in the future.

Climate-related health impact indicators for public health surveillance in a changing climate: a systematic review and local suitability analysis

Climate change challenges public health. Effective management of climate-related health risks relies on robust public health surveillance (PHS) and population health indicators. Despite existing global and country-specific indicators, their integration into local PHS systems is limited, impacting decision-making. We conducted a systematic review examining population health indicators relevant to climate change impacts and their suitability for national PHS systems. Guided by a registered protocol, we searched multiple databases and included 41 articles. Of these, 35 reported morbidity indicators, and 39 reported mortality indicators. Using Chile as a case study, we identified three sets of indicators for the Chilean PHS. The high-priority set included vector-, food-, and water-borne diseases, as well as temperature-related health outcomes indicators due to their easy integration into existing PHS systems. This review highlights the importance of population health indicators in monitoring climate-related health impacts, emphasising the need for local contextual factors to guide indicator selection.

Funding

This research project was partly funded by ANID Chile and University College London. None of these sources had any involvement in the research conceptualisation, design, or interpretation of the results.

How urban heat island magnifies hot day exposure: Global unevenness derived from differences in built landscape

Urban heat-islands reportedly expose densely populated areas to higher temperatures. However, the magnitude of the impact of extra hot-day exposure (EHDE) and its association with the effects of urbanization on a global scale remain unclear. As local climate zones (LCZs) refine the impact of differences in urban built-type on heat-island effects, this study aimed to quantify the global EHDE caused by the urban heat-island effect based on LCZs and explored the joint impacts of low gross-domestic product and an increasing vulnerable-age population on EHDE. The results showed that EHDE accounted for 48.01 % of overall hot-day exposure. Additionally, despite a significant geographic differentiation among LCZ types with the highest EHDE intensity, they are almost typically building-intensive LCZs. Furthermore, our study revealed regional differences in the structure of the EHDE share in LCZs, which support the adoption of targeted EHDE mitigation strategies.

Systemic inequalities in heat risk for greater London

The temperature rise and increases in extreme heat events related to global climate change is a growing public health threat. Populations in temperate climates, including the UK, must urgently adapt to increased hot weather as current infrastructure primarily focusses on resilience to cold. As we adapt, care should be taken to ensure existing health inequalities are reduced. Lessons can be learned from regions that experience warmer climates and applied to adaptation in the UK. We identified known indicators of heat-health risk and explored their distribution across area level income for London. Understanding these indicators and their distributions across populations can support the development of interventions that have the dual aim of improving health and reducing inequalities. An exploratory analysis was conducted for each indicator at neighbourhood level to assess existence of disparities in their distributions across London. A systems-thinking approach was employed to deduce if these amount to systemic inequalities in heat risk, whereby those most exposed to heat are more susceptible and less able to adapt. Using this information, we proposed interventions and made recommendations for their implementation. We find inequalities across indicators relating to exposure, vulnerability, and adaptive capacity. Including inequalities in urban greening and access to greenspace, physical and mental health and access to communication and support. Through a system diagram we demonstrate how these indicators interact and suggest that systemic inequalities in risk exist and will become more evident as exposure increases with rising temperatures, depending on how we adapt. We use this information to identify barriers to the effective implementation of adaptation strategies and make recommendations on the implementation of interventions. This includes effective and wide-reaching communication considering the various channels and accessibility requirements of the population and consideration of all dwelling tenures when implementing policies relating to home improvements in the context of heat.

Shared insights for heat health risk adaptation in metropolitan areas of developing countries

Global warming has led to a surge in heat health risks (HHRs), the impacts of which are particularly pronounced in metropolitan areas of developing countries. In the current study, six metropolitan areas - Beijing, China; Cairo, Egypt; Jakarta, Indonesia; Mumbai, India; Rio de Janeiro, Brazil; and Tehran, Iran - were selected as the study area to further differentiate the built-up landscapes by utilizing the concept of local climate zones. Moreover, we assessed the similarities and differences in HHR associated with the landscape. Results revealed a 30.67% higher HHR in compact built-up landscapes than in the open built-up type. Urban green spaces played an effective but differentiated role in mitigating HHR. That is, low vegetation in urbanized areas and trees in suburban areas significantly mitigated HHR. Collectively, our findings emphasize the role of effective planning and management in addressing HHR and provide empirical support for implementing HHR mitigation and adaptation strategies.

Gender disparities in summer outdoor heat risk across China: Findings from a national county-level assessment during 1991-2020

Increasing anthropogenic global warming has emerged as a significant challenge to human health in China, as extreme heat hazards increasingly threaten outdoor-exposed populations. Differences in thermal comfort, outdoor activity duration, and social vulnerability between females and males may exacerbate gender inequalities in heat-related health risks, which have been overlooked by previous studies. Here, we combine three heat hazards and outdoor activity duration to identify the spatiotemporal variation in gender-specific heat risk in China during 1991-2020. We found that females' heat risk tends to be higher than that of males. Gender disparities in heat risk decrease in southern regions, while those in northern regions remain severe. Males are prone to overheating in highly urbanized areas, while females in low urbanized areas. Males' overheating risk is mainly attributed to population clustering associated with prolonged outdoor activity time and skewed social resource allocation. In contrast, females' overheating risk is primarily affected by social inequalities. Our findings suggest that China needs to further diminish gender disparities and accelerate climate adaptation planning.

Mapping social vulnerability indicators to understand the health impacts of climate change: a scoping review

The need to assess and measure how social vulnerability influences the health impacts of climate change has resulted in a rapidly growing body of research literature. To date, there has been no overarching, systematic examination of where this evidence is concentrated and what inferences can be made. This scoping review provides an overview of studies published between 2012 and 2022 on social vulnerability to the negative health effects of climate change. Of the 2115 studies identified from four bibliographic databases (Scopus, Web of Science, PubMed, and CAB Direct), 230 that considered indicators of social vulnerability to climate change impacts on health outcomes were selected for review. Frequency and thematic analyses were conducted to establish the scope of the social vulnerability indicators, climate change impacts, and health conditions studied, and the substantive themes and findings of this research. 113 indicators of social vulnerability covering 15 themes were identified, with a small set of indicators receiving most of the research attention, including age, sex, ethnicity, education, income, poverty, unemployment, access to green and blue spaces, access to health services, social isolation, and population density. The results reveal an undertheorisation and few indicators that conceptualise and operationalise social vulnerability beyond individual sociodemographic characteristics by identifying structural and institutional dimensions of vulnerability, and a preponderance of social vulnerability research in high-income countries. This Review highlights the need for future research, data infrastructure, and policy attention to address structural, institutional, and sociopolitical conditions, which will better support climate resilience and adaptation planning.

Variations of Urban Thermal Risk with Local Climate Zones

Due to the differences in land cover and natural surroundings within cities, residents in various regions face different thermal risks. Therefore, this study combined multi-source data to analyze the relationship between urban heat risk and local climate zones (LCZ). We found that in downtown Shenyang, the building-type LCZ was mainly found in urban centers, while the natural- type LCZ was mainly found in suburbs. Heat risk was highest in urban centers, gradually decreasing along the suburban direction. The thermal risk indices of the building-type LCZs were significantly higher than those of the natural types. Among the building types of LCZs, LCZ 8 (open middle high-rise) had the highest average thermal risk index (0.48), followed by LCZ 3 (0.46). Among the natural types of LCZs, LCZ E (bare rock and paved) and LCZ F (bare soil and sand) had the highest thermal risk indices, reaching 0.31 and 0.29, respectively. This study evaluated the thermal risk of the Shenyang central urban area from the perspective of LCZs and combined it with high-resolution remote sensing data to provide a reference for thermal risk mitigation in future urban planning.

Spatiotemporal Variation Analysis of the Fine-Scale Heat Wave Risk along the Jakarta-Bandung High-Speed Railway in Indonesia

As a highly important meteorological hazard, heat waves notably impact human health and socioeconomics, and accurate heat wave risk identification and assessment are effective ways to address this issue. The current spatial scale of heat wave risk assessment is relatively coarse, hardly meeting fine-scale heat wave risk assessment requirements. Therefore, based on multi-source fine-scale remote sensing data and socioeconomic data, this paper evaluates the heat wave risk along the Jakarta-Bandung high-speed railway, obtains the spatial distribution of heat wave risk in 2005, 2014 and 2019, and analyzes spatiotemporal risk variations over the past 15 years. The results show that most high-risk areas were affected by high-temperature hazards. Over time, the hazard, exposure, vulnerability and risk levels increased by 25.82%, 3.31%, 14.82% and 6.97%, respectively, from 2005–2019. Spatially, the higher risk in the northwest is mainly distributed in Jakarta. Additionally, a comparative analysis was conducted on the risk results, and the results showed that the 100-m scale showed more spatial differences than the kilometer scale. The research results in this paper can provide scientific advice on heat wave risk prevention considering the Jakarta-Bandung high-speed railway construction and regional economic and social development.

Modulations of surface thermal environment and agricultural activity on intraseasonal variations of summer diurnal temperature range in the Yangtze River Delta of China

Compared with interdecadal, interannual, or seasonal scales, the variations of diurnal temperature range (DTR) at the intraseasonal scale and their driving forces are less understood. Using surface meteorological observations and multi-source satellite retrievals during 2013-2017, together with Random Forest modeling, this study examines the intraseasonal variation of summer DTR in the Yangtze River Delta (YRD) region, China, and determines its potential driving factors [i.e., daily maximum/minimum surface air temperature (SAT_max/SAT_min), sunshine duration (SSD), rainfall, altitude, land vegetation cover, and land surface thermal environment including daytime/nighttime land surface temperature (LST_D/LST_N) and anthropogenic heat flux (AHF)]. It is found that the intraseasonal variation of DTR at both 8-day and monthly scales in the YRD exhibits regional differences and is modulated by different primary factors across the region. The evident intraseasonal variation of DTR, with a peak in June, in the northern YRD, is largely attributable to nighttime temperatures (SAT_min and LST_N), which in turn are mainly attributable to different LST_N responses to the underlying surface cover changes associated with crop rotation. In contrast, as the YRD metropolitan area (MYRD) is covered by a large proportion of built-up surfaces, and the weather stations there are surrounded by a higher surface thermal environment and AHF, the MYRD has stably higher LST and SAT_min in the whole summer season. Thus, the summer DTR in the MYRD exhibits marginal intraseasonal variations. In the southern YRD, there is also a distinct DTR characteristic, with a maximum in July and minimum in June, since this region is largely covered by forests with constantly high-density vegetation cover, and its DTR variation is mainly forced by SSD, which directly affects SAT_max. The findings reported here have important implications for understanding the influences of human activities on regional climate and environmental change for other regions of the world that experience various external forcings.

Mapping Heat-Related Risks in Northern Jiangxi Province of China Based on Two Spatial Assessment Frameworks Approaches

Heat-health risk is a growing concern in many regions of China due to the more frequent occurrence of extremely hot weather. Spatial indexes based on various heat assessment frameworks can be used for the assessment of heat risks. In this study, we adopted two approaches—Crichton’s risk triangle and heat vulnerability index (HVI) to identify heat-health risks in the Northern Jiangxi Province of China, by using remote sensing and socio-economic data. The Geographical Information System (GIS) overlay and principal component analysis (PCA) were separately used in two frameworks to integrate parameters. The results show that the most densely populated community in the suburbs, instead of city centers, are exposed to the highest heat risk. A comparison of two heat assessment mapping indicates that the distribution of HVI highlights the vulnerability differences between census tracts. In contrast, the heat risk index of Crichton’s risk triangle has a prominent representation for regions with high risks. The stepwise multiple linear regression zero-order correlation coefficient between HVI and outdoor workers is 0.715, highlighting the vulnerability of this particular group. Spearman’s rho nonparametric correlation and the mean test reveals that heat risk index is strongly correlated with HVI in most of the main urban regions in the study area, with a significantly lower value than the latter. The analysis of variance shows that the distribution of HVI exhibits greater variety across urban regions than that of heat risk index. Our research provides new insight into heat risk assessment for further study of heat health risk in developing countries.

Fine-scale mapping of an evidence-based heat health risk index for high-density cities: Hong Kong as a case study

The most recent extreme heat recorded in Europe re-alerts the world to the threat of heat stress. Future extreme heat events are reported to be more frequent, long-lasting, and intense. The intense exposure to hot temperatures can cause an excess of heat-related deaths, leading to an increasing risk of heat-related health. In reducing Heat Health Risk (HHR), the use of fine-scale evidence-based mapping of heat-related health risk index (HHRI) and its underlying contributors is essential for policy-making and site-specific action plans. However, its use is still considered to be at an early stage, especially in high-density cities like Hong Kong. This study conducted a spatially explicit assessment of HHR in Hong Kong and constructed a HHRI based on indicators categorized through Principle Component Analysis (PCA) into four meaningful components representing social/language, social isolation, socioeconomic, and urbanization/environmental risks. The applicability of the index was validated against heat-related mortality data at the community level. The community-level maps of HHRI and its subcomponents revealed that portions of Kowloon Peninsula had always suffered exceptionally high HHR ten years ago and after, but the hot spots and problematic communities experienced displacement and the dominant underlying factors of their HHR also varied. Results also showed that HHRI correlated fairly well with the heat-related deaths ratio (R² = 0.60) at the community level for most of Hong Kong (62.33% of all communities that contain 81.69% of total population). Our analysis results helped generate an evidence-based index to assess HHR in high-density cities like Hong Kong and provided fine-scale maps of the index and its subcomponents, with the aim of benefiting site-specific policy making and optimizing the existing action plans.

Assessing Urban Risk to Extreme Heat in China

Many cities are experiencing persistent risk in China due to frequent extreme weather events. Some extreme weather events, such as extreme heat hazard, have seriously threatened human health and socio-economic development in cities. There is an urgent need to measure the degree of extreme heat risk and identify cites with the highest levels of extreme heat risk. In this study, we presented a risk assessment framework of extreme heat and considered risk as a combination of hazard, exposure, and vulnerability. Based on these three dimensions, we selected relevant variables from historical meteorological data (1960–2016) and socioeconomic statistics in 2016, establishing an indicator system of extreme heat risk evaluation. Finally, we developed an extreme heat risk index to quantify the levels of extreme heat risk of 296 prefecture-level cities in China and revealed the spatial pattern of extreme heat risk in China in 2016 and their dominant factors. The results show that (1) cities with high levels of extreme heat hazard are mainly located in the south of China, especially in the southeast of China; (2) the spatial distribution of the extreme heat risk index shows obvious agglomeration characteristics; (3) the spatial distribution of the extreme heat risk is still mostly controlled by natural geographical conditions such as climate and topography; (4) among the four types of hazard-dominated, exposure-dominated, vulnerability-dominated, and low risk cities, the number of vulnerability-dominated cities is the largest. The results of this study can provide support for the risk management of extreme heat disasters and the formation of targeted countermeasures in China.

Heat health risk assessment in Philippine cities using remotely sensed data and social-ecological indicators

More than half of the world’s population currently live in urban areas and are particularly at risk from the combined effects of the urban heat island phenomenon and heat increases due to climate change. Here, by using remotely sensed surface temperature data and social-ecological indicators, focusing on the hot dry season, and applying the risk framework of the Intergovernmental Panel on Climate Change, we assessed the current heat health risk in 139 Philippine cities, which account for about 40% of the country’s total population. The cities at high or very high risk are found in Metro Manila, where levels of heat hazard and exposure are high. The most vulnerable cities are, however, found mainly outside the national capital region, where sensitivity is higher and capacity to cope and adapt is lower. Cities with high levels of heat vulnerability and exposure must be prioritized for adaptation. Our results will contribute to risk profiling in the Philippines and to the understanding of city-level heat health risks in developing regions of the Asia-Pacific.

Evaluating the heat risk among city dwellers is important. Here, the authors assessed the heat risk in Philippine cities using remote sensing data and social-ecological indicators and found that the cities at high or very high risk are found in Metro Manila, where levels of heat hazard and exposure are high.

Meteorological and Ancillary Data Resources for Climate Research in Urban Areas

An increasing plethora of both meteorological and ancillary data are presently available for climate research and applications in urban areas. The data are often held by local or national institutions (i.e., meteorological services, universities or environmental agencies). This paper outlines a total number of 33 datasets, organized into three main categories of meteorological data resources (14 datasets) and four categories of ancillary data resources (19 datasets), selected for their potential to support urban climate studies, but also for their free accessibility. Such a collection cannot be exhaustive, but we aim to draw the attention of the scientific community to relevant datasets, freely available at temporal and spatial resolutions appropriate for urban climatology. Each dataset contains information about its availability, limitations, and examples of research in urban areas.

Spatially Explicit Assessment of Social Vulnerability in Coastal China

Social vulnerability assessment has been recognized as a reliable and effective measure for informing coastal hazard management. Although significant advances have been made in the study of social vulnerability for over two decades, China’s social vulnerability profiles are mainly based on administrative unit. Consequently, no detailed distribution is provided, and the capability to diagnose human risks is hindered. In this study, we established a social vulnerability index (SoVI) in 2000 and 2010 at a spatial resolution of 250 m for China’s coastal zone by combining the potential exposure index (PEI) and social resilience index (SRI). The PEI with a 250 m resolution was obtained by fitting the census data and multisource remote sensing data in random forest model. The county-level SRI was evaluated through principal component analysis based on 33 socioeconomic variables. For identifying the spatiotemporal change, we used global and local Moran’s I to map clusters of SoVI and its percent change in the decade. The results suggest the following: (1) Counties in the Yangtze River Delta, Pearl River Delta, and eastern Guangzhou, except several small hot spots, exhibited the most vulnerability, especially in urban areas, whereas those in Hainan and southern Liaoning presented the least vulnerability. (2) Notable increases were emphasized in Tianjin, Yangtze River Delta, and Pearl River Delta. The spatiotemporal variation and heterogeneity in social vulnerability obtained through this analysis will provide a scientific basis to decision-makers to focus risk mitigation effort.

New ECOSTRESS and MODIS Land Surface Temperature Data Reveal Fine-Scale Heat Vulnerability in Cities: A Case Study for Los Angeles County, California

Rapid 21st century urbanization combined with anthropogenic climate warming are significantly increasing heat-related health threats in cities worldwide. In Los Angeles (LA), increasing trends in extreme heat are expected to intensify and exacerbate the urban heat island effect, leading to greater health risks for vulnerable populations. Partnerships between city policymakers and scientists are becoming more important as the need to provide data-driven recommendations for sustainability and mitigation efforts becomes critical. Here we present a model to produce heat vulnerability index (HVI) maps driven by surface temperature data from National Aeronautics and Space Administration’s (NASA) new Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) thermal infrared sensor. ECOSTRESS was launched in June 2018 with the capability to image fine-scale urban temperatures at a 70 m resolution throughout different times of the day and night. The HVI model further includes information on socio-demographic data, green vegetation abundance, and historical heatwave temperatures from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Aqua spacecraft since 2002. During a period of high heat in July 2018, we identified the five most vulnerable communities at a sub-city block scale in the LA region. The persistence of high HVI throughout the day and night in these areas indicates a clear and urgent need for implementing cooling technologies and green infrastructure to curb future warming.

Mapping heat-related health risks of elderly citizens in mountainous area: A case study of Chongqing, China

Heat wave becomes a leading cause of weather-related illness and death across the world under the background of climate change, urban heat island, and population ageing. Heat health risk assessment is an important starting point for heat-related morbidity and mortality reduction within the risk governance framework. Chongqing, a mountainous municipality with a fast rate of population ageing in China, was selected as a case study for mapping the heat health risk of the elderly population at a raster scale. The results indicated that the high heat hazard and human exposure areas were mainly distributed in the metropolitan areas, which largely resulted in high heat health risk in the urban areas. However, the high heat vulnerability pixels were mainly concentrated at the remote mountainous regions which have broken terrains and low socioeconomic statuses. Compared with traditional general heat risk indicator, this new model can provide more targeted spatial information to decision makers, and is helpful to improve the flexibility and comparability of heat risk assessment tool. Furthermore, this new model is particularly valuable for quantifying heat health risk in developing countries with limited open access data.

An Index-Based Assessment of Perceived Climate Risk and Vulnerability for the Urban Cluster in the Yangtze River Delta Region of China

This paper proposes an index-based assessment tool to consolidate diverse opinions of various stakeholders on their assessments of sector-specific risks posed by climate change, and to aggregate these opinions into intuitive and comparable graphs. This tool enables cities to measure and monitor the multiple factors that contribute to their resilience towards climate risk and hazard in the long term. We applied this tool to five key infrastructure sectors in six representative cities in the Yangtze River Delta region. The graphs generated provide for the first time first-hand insights into the aggregative understanding of various stakeholders with regard to the current and future climate risk in their concerned sectors and cities. Our results indicate that a high level of exposure is not automatically associated with a high level of vulnerability across our selected cities. While all cities need to make efforts to reduce their vulnerability towards climate hazards, those characterized by “lower level of exposure but higher level of vulnerability” need to make more urgent and much greater efforts.

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

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.