A Data-Driven Approach to Urban Heat Island Mitigation: Prioritizing areas based on Heat Risk Index for Ahmedabad city, India

Urban Heat Island (UHI) effects pose a significant challenge in rapidly urbanizing cities, particularly in hot-dry climates like Ahmedabad, India. This study presents a data-driven approach to UHI mitigation by utilizing a Heat Risk Index (HRI) to prioritize areas based on their vulnerability. The research utilizes ward-level data for the year 2020-21, incorporating population density, yearly averaged land surface temperature, and percentage of area lacking green cover.

The Heat Risk Index (HRI) is computed by summing the normalized scores of the selected parameters. HRI ranges from 3 to 15 and classifies urban heat risk into four categories: low (3-6), medium (6-9), high (9-12), and very high (12-15). The methodology involves normalizing the ward-level data on a scale of 1-5, followed by the computation of HRI through summation of the normalized values. The final output is a ward-level HRI map of the city, identifying high-priority areas for intervention. The results of the present study for Ahmedabad city (where more than 8 million people resides) reveals that of the total 48 wards, 8 are under very high risk category followed by 23, 13 and 4 in High, Medium and Low risk category respectively.

This study provides a scientific basis for targeted UHI mitigation efforts, enabling policymakers to prioritize urban cooling strategies such as nature based solutions like green wall, green roofs, green cover, water bodies and water fountains; reflective surfaces, and many more. By integrating a data-driven methodology, the research contributes to strengthening the city’s Heat Action Plan, reducing heat-related mortalities, and enhancing outdoor thermal comfort for residents. The findings underscore the necessity of evidence-based urban climate policies to build heat-resilient cities, especially in climate-vulnerable regions. This approach serves as a replicable framework for other cities facing similar UHI challenges, ensuring efficient resource allocation and proactive climate adaptation strategies.