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Relationship Between Land Cover Ratio and Urban Heat Island from Remote Sensing and Automatic Weather Stations Data

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Abstract

Urban heat island (UHI) effect has a close relation to land covers type. This paper investigates the relationship between land cover ratio and UHI in Guangzhou, south of China using remote sensing and automatic weather stations data. The temperature data were obtained by Automatic weather stations (AWS) of Guangzhou in October, 2004, at the same time with the CBERS remote sensing image acquired. Firstly, the hourly mean temperature was computed from hourly AWS data. Secondly, the CBERS remote sensing image was classified using support vector machine (SVM) and land covers classification were output. Thirdly, the classification result was overlapped with a round buffer with 1.5 KM radius centered on the AWS, and then the land cover ratio, Edge Density (ED) and Mean Fractal Dimension (MFRACT) of buffers were computed out. Finally, the correlation coefficient between hourly mean temperature and land cover ratio, ED and MFRACT was calculated. It concluded that UHI intensity was heavier during nighttime than daytime. Stations with higher vegetation ratio and higher ED had lower heat island effect. On the contrary, stations with higher impervious ratio and lower ED had more serious heat island effect. The positive–negative of correlation coefficient between hourly mean temperature and vegetation ratio during 11:00–17:00 h (local time) was opposite to that during other time. ED was negatively correlated with hourly mean temperature except during 11:00–17:00 h. On the contrary, MFRACT was positively correlated with hourly mean temperature. It implied that fragmentations of patches were favorable to UHI alleviation, and complexities of patch were unfavorable factors.

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Acknowledgment

The authors are grateful to anonymous reviewers for their valuable comments and suggestions that greatly improve the presentation of this paper. This study was jointly supported by the NSFC of Yunnan province, China (KKSA200921019), Scientific Research Foundation of Kunming University of Science and Technology (KKZ3200821048) and the innovation team of ore-forming dynamics and prediction of concealed deposits, Kunming University of Science and Technology, Kunming, China (2008).

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Authors and Affiliations

  1. Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming, China

    Xingping Wen

  2. Research Center for Analysis and Measurement, Kunming University of Science and Technology, Kunming, China

    Xiaofeng Yang

  3. Institute of Mathematic Geology and Remote Sensing Geology, China University of Geosciences, Wuhan, China

    Guangdao Hu

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  1. Xingping Wen
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  2. Xiaofeng Yang
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  3. Guangdao Hu
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Correspondence to Xingping Wen.

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Wen, X., Yang, X. & Hu, G. Relationship Between Land Cover Ratio and Urban Heat Island from Remote Sensing and Automatic Weather Stations Data. J Indian Soc Remote Sens 39, 193–201 (2011). https://doi.org/10.1007/s12524-011-0076-4

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  • DOI: https://doi.org/10.1007/s12524-011-0076-4

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