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The surface heat island of Rotterdam and its relationship with urban surface characteristics

Author

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  • Klok, Lisette
  • Zwart, Sander
  • Verhagen, Henk
  • Mauri, Elena

Abstract

Thermal infrared high resolution satellite images from Landsat sensors were used to spatially quantify the surface heat island (SHI) of Rotterdam in the Netherlands. Based on surface temperature maps retrieved on 15 summer days since 1984, the average surface temperature of each district and neighbourhood within the city was compared to the rural surface temperature outside the city, defined as the SHI intensity. The results showed that the daytime SHI intensity of Rotterdam can be as large as 10°C. Differences in the SHI between the neighbourhoods can be explained by urban surface characteristics. A statistical analysis shows that the SHI is largest for neighbourhoods with scarce vegetation that have a high fraction of impervious surface, and a low albedo. Furthermore, NOAA-AVHHR satellite images were used to monitor the heat wave of July 2006 and retrieve the diurnal variation in the SHI of Rotterdam. Average surface temperature differences between the warmest and coolest districts are maximum 12°C during day, and 9°C during night. Districts with a large night-time SHI differ from districts with a large daytime SHI.

Suggested Citation

  • Klok, Lisette & Zwart, Sander & Verhagen, Henk & Mauri, Elena, 2012. "The surface heat island of Rotterdam and its relationship with urban surface characteristics," Resources, Conservation & Recycling, Elsevier, vol. 64(C), pages 23-29.
    • Handle: RePEc:eee:recore:v:64:y:2012:i:c:p:23-29
    DOI: 10.1016/j.resconrec.2012.01.009
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    Cited by:

    1. Kim, Se Woong & Brown, Robert D., 2021. "Urban heat island (UHI) variations within a city boundary: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    2. Silva, Marcos Dornelas Freitas Machado e & Calijuri, Maria Lúcia & Sales, Francisco José Ferreira de & Souza, Mauro Henrique Batalha de & Lopes, Lucas Sampaio, 2014. "Integration of technologies and alternative sources of water and energy to promote the sustainability of urban landscapes," Resources, Conservation & Recycling, Elsevier, vol. 91(C), pages 71-81.
    3. Lan Thanh Ha & Wim G. M. Bastiaanssen, 2023. "Determination of Spatially-Distributed Hydrological Ecosystem Services (HESS) in the Red River Delta Using a Calibrated SWAT Model," Sustainability, MDPI, vol. 15(7), pages 1-24, April.
    4. Kaihua Zhang & Guoliang Yun & Peihao Song & Kun Wang & Ang Li & Chenyu Du & Xiaoli Jia & Yuan Feng & Meng Wu & Kexin Qu & Xiaoxue Zhu & Shidong Ge, 2023. "Discover the Desirable Landscape Structure of Urban Parks for Mitigating Urban Heat: A High Spatial Resolution Study Using a Forest City, Luoyang, China as a Lens," IJERPH, MDPI, vol. 20(4), pages 1-26, February.
    5. Jaehyun Ha & Yeri Choi & Sugie Lee & Kyushik Oh, 2020. "Diurnal and Seasonal Variations in the Effect of Urban Environmental Factors on Air Temperature: A Consecutive Regression Analysis Approach," IJERPH, MDPI, vol. 17(2), pages 1-21, January.
    6. Pauline Schmidt & Bryce T. Lawrence, 2022. "Association between Land Surface Temperature and Green Volume in Bochum, Germany," Sustainability, MDPI, vol. 14(21), pages 1-20, November.
    7. Shuang Liu & Xuefei Li & Long Chen & Qing Zhao & Chaohui Zhao & Xisheng Hu & Jian Li, 2022. "A New Approach to Investigate the Spatially Heterogeneous in the Cooling Effects of Landscape Pattern," Land, MDPI, vol. 11(2), pages 1-21, February.
    8. Youpeng Lu & Wenze Yue & Yaping Huang, 2021. "Effects of Land Use on Land Surface Temperature: A Case Study of Wuhan, China," IJERPH, MDPI, vol. 18(19), pages 1-18, September.

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