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Spatial variability of urban climate in response to quantitative trait of land cover based on GWR model

  • Xisheng Hu
  • Hanqiu XuEmail author
Article
  • 114 Downloads

Abstract

Land surface temperature and moisture are central components of the Earth’s surface heat budget. China has experienced substantial land use/cover change that has led to deterioration of the urban microclimate, thus affecting global climate change. Understanding the spatial non-stationarity in the relationships between climate and land cover across a highly heterogeneous surface of urban landscapes is important for improving urban planning and management. This study used Landsat-8 OLI/TIRS data to explore the relationship of the three components (index-based built-up index (IBI); bare soil index (SI); and normalized difference vegetation index (NDVI)) with the urban climate (land surface temperature (LST) and land surface moisture (LSM)) using both a global model (ordinary least squares (OLS)) and a local model (geographically weighted regression (GWR)) for a megacity in Southeast China. The global regression results showed that there were significant positive correlations between the LST and the IBI and SI, while significant negative correlations were observed between the LST and the NDVI; opposite results were observed for the LSM. The IBI is the factor having the greatest impact on the LST, while the SI is among the most important factors for the LSM. The local regression results showed that the response of urban climate to land surface is affected greatly by water areas, but the role of the water areas is impacted by their size and surrounding landscape patterns. Moreover, the effects of vegetation and built-up land on the urban climate vary across locations with different wind patterns.

Keywords

Global climate change Geographically weighted regression Land surface temperature Land surface moisture Land use/cover change Fuzhou 

Notes

Funding information

This research was funded by the China Postdoctoral Science Foundation (no. 2017M610390), the National Natural Science Foundation of China (no. 41201100), and the Natural Science Foundation of Fujian Province (no. 2015J01606), to which we are very grateful.

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interest.

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.College of Environment and ResourcesFuzhou UniversityFuzhouChina
  2. 2.College of Transportation and Civil EngineeringFujian Agriculture and Forestry UniversityFuzhouChina
  3. 3.Institute of Remote Sensing Information EngineeringFuzhou UniversityFuzhouChina
  4. 4.Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster ProtectionFuzhouChina

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