Abstract
Heatwaves, as one of the most significant consequences of climate change, have exhibited increasing trends in intensity, frequency, and spatial extent across the globe over recent decades. This hazard can have extensive impact on human activities. The aim of this study is to present a framework integrating geospatial models and multi-criteria decision-making systems to assess the risk of heatwaves on human activities. For this purpose, various geospatial datasets including environmental, climatic, infrastructural, and human activity-related factors were used for Iran, a region highly vulnerable to heatwaves. In the first stage, key vulnerability criteria including the hazard indicators, exposure indicators, and adaptive capacity, were identified, and their corresponding maps were generated. The criteria were standardized using the min–max normalization method. The Best–Worst Method (BWM) was then applied to determine the weights of the influencing criteria. Subsequently, hazard indicators, exposure indicators, and adaptive capacity were produced using the Weighted Linear Combination (WLC) model. By integrating these components, the final heatwave vulnerability map was generated. Finally, the Global Human Modification (GHM) map was combined with the vulnerability map to extract the final heatwave risk map for human activities. The results revealed that approximately 20%, 5%, and 9% of Iran’s area were classified as very high in terms of hazard indicators, exposure indicators, and adaptive capacity, respectively. The spatial distribution of heatwave vulnerability in Iran is heterogeneous, increasing from north to south and from west to east. Approximately 29% of the country falls within the high vulnerability class, and 20% within the very high class, with these areas geographically concentrated in the southern and eastern regions. Based on the analysis, 40–50% of human activity areas are located within moderate- to high-risk zones. Human activities in the central, southern, and southeastern regions of Iran face the highest levels of heatwave risk. To further characterize this spatial pattern, a zonal statistical analysis across Köppen climate zones showed that the Hot Desert climate (Bwh) exhibited the highest risk, with a peak mean risk score of 15.74 ± 4.85, followed closely by the Hot Semi-Arid zone (Bsh) at 13.80 ± 5.65. The robustness of these results was further confirmed through a One-At-a-Time (OAT) sensitivity analysis, which yielded a 96.2% mean pixel class retention rate across 52 perturbation scenarios, with the Exposure (32.5%) and Hazard (24.2%) dimensions exerting the strongest influence on vulnerability classification. The findings indicate that the combination of a hot and arid climate, low adaptive capacity, and high human activity density are the main drivers of increased heatwave risk in Iran. The results of this study can serve as a foundation for national-scale adaptation planning and heat hazard management. Furthermore, the proposed approach can be applied to assess heatwave risk to human activities in regions with similar climatic conditions worldwide.