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Journal of the Indian Society of Remote Sensing

, Volume 47, Issue 11, pp 1831–1845 | Cite as

Impacts of Large-Area Impervious Surfaces on Regional Land Surface Temperature in the Great Pearl River Delta, China

  • Yuling Ma
  • Kun YangEmail author
  • Shaohua ZhangEmail author
  • Mingchan Li
Research Article
  • 91 Downloads

Abstract

Rapid urbanization has led to an increase in urban land surface temperature (LST). In contrast to individual cities or megacity scale, urban agglomeration can increase LST in a continuous area due to decreasing or disappearing distance between cities. Thus, the impact of ISA on LST needs further understanding in the large scale of urban agglomerations. This study investigated the impacts of impervious surface area (ISA) on LST in urban agglomeration region. The distribution of ISA and LST of the Greater Pearl River Delta in 2015 was extracted using the Landsat 8 OLI and Aqua MODIS images. Next, the standard deviational ellipse methods were used to systematically analyze the spatial correlation of ISA and LST. Subsequently, the influences of ISA density and landscape pattern of ISA on LST were analyzed by various methods. The results showed that when the ISA density increased 10%, the daytime LST increased 0.46 °C at the density level lower than 70% and 0.55 °C at the density level higher than 70%, respectively. Likewise, when the ISA density increased 10%, the nighttime LST increased 0.285 °C at the density level lower than 70% and 0.39 °C at the density level higher than 70%, respectively. In addition, the results of correlation analysis indicated that landscape metrics of ISA and the density of ISA had significant correlation with the LST. However, the correlation was higher at daytime than at nighttime, due to the large terrain, complex environment and diverse surface cover types in the study area.

Keywords

Impervious surface Land surface temperature Landscape pattern Landscape metric Great Pearl River Delta 

Notes

Acknowledgements

The authors would like to thank the anonymous reviewers and editor for constructive comments and suggestions.

Funding

This work was supported by the Yunnan Normal University Postgraduate Innovation Fund [Grant Number yjs201680], Yunnan Provincial Department of Education Research Fund [Grant Number 2011Y307], National Natural Science Foundation of China [Grant Number 41461038], Yunnan Provincial Science and Technology Project [Grant Number 2011XX2005] and Specialized Research Fund for the Doctoral Program of Higher Education [Grant Number 20115303110002].

Compliance with Ethical Standards

Conflict of interest

No potential conflict of interest was reported by the authors.

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Copyright information

© Indian Society of Remote Sensing 2019

Authors and Affiliations

  1. 1.School of Tourism and Geographic ScienceYunnan Normal UniversityKunmingChina
  2. 2.The Engineering Research Centre of GIS Technology in Western China, Ministry of EducationYunnan Normal UniversityKunmingChina
  3. 3.School of Information Science and TechnologyYunnan Normal UniversityKunmingChina

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