Determining Cooling Green Space Planning Criteria for Mitigating the Urban Heat Island Effect Using the Delphi Technique

Abstract

The urban heat island (UHI) effect is one of the major environmental challenges associated with rapid urbanization, increasing impervious surfaces, and the loss of natural areas, leading to elevated temperatures in urban environments. Planning cooling green spaces is considered one of the most effective nature-based solutions for mitigating this effect. However, existing studies have primarily focused on the direct application of evaluation criteria in cooling green space planning, whereas the systematic identification of these criteria based on expert consensus has received limited attention. Therefore, this study aims to identify the evaluation criteria that should be considered in cooling green space planning for urban heat island mitigation using the Delphi technique. The study was conducted through a three-round Delphi process involving 14 experts from different disciplines. In the first round, expert opinions collected through open-ended questions were analyzed using content analysis to develop an initial set of evaluation criteria. In the second and third rounds, the importance of each criterion was assessed using a seven-point Likert scale. Consensus was evaluated using the median, quartiles (Q1–Q3), Decreasing Average Factor (DAF), and frequency distributions. Of the 19 criteria evaluated in the second round, consensus was achieved for 15, while the remaining four criteria were re-evaluated in the third round. Following the third round, two additional criteria reached consensus and were included in the final framework, whereas the remaining two criteria were excluded. As a result, a scientifically validated final set of evaluation criteria consisting of five main criteria and seventeen sub-criteria was established based on expert consensus. The proposed framework is expected to provide a methodological foundation for future GIS-based spatial suitability analyses, multi-criteria decision-making applications, and urban planning studies aimed at climate change adaptation.