With the rise in global temperatures and frequent occurrence of extreme heat events, overheating disasters pose significant threats to the health, safety, and economic activities of urban residents. Existing methods for heat risk assessment often focus on single-dimensional analysis, neglecting the comprehensive consideration of multiple dimensions such as hazard, exposure, vulnerability, and adaptability. These methods also fail to accurately select risk indicators by integrating diverse data sources, making it difficult to capture the spatial heterogeneity of heat risk characteristics. To address these limitations and enhance the scientific rigor and comprehensiveness of risk assessments, this study proposes a multidimensional framework that integrates hazard, exposure, adaptability, and vulnerability to systematically assess urban heat risks during the summer. In terms of data integration, this model combines geographic meteorological data with socioeconomic data to capture the spatial heterogeneity of the heat risk. Regarding the assessment methodology, a combination of the Analytic Hierarchy Process (AHP) and entropy method (EM) was suggested to ensure the scientific accuracy and practical relevance of the risk indicators. For risk visualization, the ArcGIS tool was recommended to clearly display the spatial distribution of risks, allowing for the rapid identification of high-risk areas and providing a foundation for urban management and disaster mitigation planning. By utilizing this multidimensional and multidata source integrated analysis framework, a more comprehensive identification and assessment of heat risks under extreme summer heat conditions can be achieved. This approach offers urban planners and policymakers a practical tool to improve public health management and enhance climate adaptability.