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Assessing the cooling efficiency of urban parks using data envelopment analysis and remote sensing data

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Abstract

Urban parks can contribute to significant cooling effect for the city microclimate and, therefore, promote urban residents’ outdoor thermal comfort. As the enhancement of the urban heat island effect, understanding the cooling efficiency of urban park and associated determinants has become critical for maximizing the ecological benefits of urban ecological infrastructure. In this paper, we measured holistically the cooling efficiency of urban parks from a relative and absolute perspective by using the data envelopment analysis (DEA) model and Landsat 8 OLI/TIRS satellite imageries. We adopted two novel cooling effect indices to rank and identify the inefficient park: DEA-based cooling efficiency index for relative efficiency and park cooling intensity index (PCII) for absolute efficiency. A total of 146 urban parks within the Shanghai metropolitan city was selected to conduct the empirical research. The correlation analysis and machine learning techniques (XGBoost) were also used to examine the relationships between the characteristics of parks and two cooling effect indices. The findings revealed that the average cooling efficiency of urban park in summer was approximately 2.7 times higher than that in winter. Park size and vegetation greenness (NDVI) were identified as the dominant factors for park cooling efficiency. Moreover, larger parks with area > 5 ha showed better cooling performance on average. In the current study area, increasing the water body coverage ratio also played an important role on the improvement of cooling effect in both summer and winter. The research findings could provide valuable references for designing urban parks and for urban planning to maximize the cooling benefits and mitigate the UHI effects.

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Acknowledgements

This work was sponsored by K.C. Wong Magna Fund in Ningbo University and National Natural Science Foundation of China (41771174), (41571018), and (41871024). The authors also acknowledge Professor Weiwei Sun from Ningbo University for his assistance with the high-resolution remote sensing images acquisition.

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Authors and Affiliations

  1. Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, 315211, China

    Yanwei Sun, Chao Gao, Jialin Li, Mengying Gao & Renfeng Ma

  2. Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research at Ningbo University, Ningbo, 315211, China

    Yanwei Sun, Chao Gao, Jialin Li & Renfeng Ma

  3. Institute of East China Sea, Ningbo University, Ningbo, 315211, China

    Yanwei Sun, Chao Gao, Jialin Li & Renfeng Ma

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  1. Yanwei Sun
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  2. Chao Gao
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  3. Jialin Li
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  4. Mengying Gao
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Contributions

All authors contributed to the study conception and design. Yanwei Sun: data collection, analyzing the results, and writing the article. Mengying Gao: data collection. Chao Gao: supervising the article and improving the expressions. Jialin Li: supervising the article. Renfeng Ma: supervising the article.

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Correspondence to Chao Gao.

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Sun, Y., Gao, C., Li, J. et al. Assessing the cooling efficiency of urban parks using data envelopment analysis and remote sensing data. Theor Appl Climatol 145, 903–916 (2021). https://doi.org/10.1007/s00704-021-03665-2

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