The influence of socioeconomic and topographic factors on nocturnal urban heat islands: a case study in Shenzhen, China

Earlier studies on urban heat islands (UHIs) focused mostly on the phenomenon during the daytime, when temperature peaks could usually be observed. However, for people living and working in tropical and subtropical cities, night-time air temperatures are also important. Several studies have focused primarily on the impact of biophysical and meteorological factors on nocturnal land surface temperatures (LSTs). Less attention has been paid to study of the influence of socioeconomic and topographic factors on nocturnal UHIs within a city. In this study, the integration of remote sensing (RS), geographic information system (GIS) and landscape ecology methods was used to investigate the relationships between nocturnal UHIs and socioeconomic or topographic factors based on a case study of Shenzhen, China. Nocturnal Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and daytime Landsat Thematic Mapper (TM) images were used to derive and analyse night- and daytime LSTs, respectively. Land-use data were generated by onscreen digitizing, and an abundance of impervious surfaces was produced through a normalized spectral mixture analysis (NSMA) method with TM data. Socioeconomic variables were derived from the China 2000 census data. A 30 m digital elevation model (DEM) was used to calculate elevation and slope grids. The relationships between nocturnal UHIs and socioeconomic or topographic factors were analysed using traditional regression analysis. The results show that the nocturnal and daytime LST patterns in different land-use areas were significantly different. Nocturnal LSTs were closely related to socioeconomic and topographic factors. An increase of 5 K on nocturnal LST of sub-districts was associated with an increase of 66.0% on their impervious surface abundance, 39 810 people per km2, 1000 Yuan per month on housing rent, 9.5 km per km2 on road density or a decline of 217.5 m on elevation and 17.0° on slope.

[1]  M. Tiangco,et al.  ASTER‐based study of the night‐time urban heat island effect in Metro Manila , 2008 .

[2]  T. Oke,et al.  Thermal remote sensing of urban climates , 2003 .

[3]  D. Lu,et al.  Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies , 2004 .

[4]  D. Quattrochi,et al.  Thermal remote sensing of urban areas: An introduction to the special issue , 2006 .

[5]  Qihao Weng,et al.  Remote Sensing Sensors and Applications in Environmental Resources Mapping and Modelling , 2007, Sensors.

[6]  Hua Liu,et al.  The Spatial Variations of Urban Land Surface Temperatures: Pertinent Factors, Zoning Effect, and Seasonal Variability , 2008, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[7]  D. Quattrochi,et al.  A multi-scale approach to urban thermal analysis , 2006 .

[8]  W. Emery,et al.  Satellite-derived urban heat islands from three coastal cities and the utilization of such data in urban climatology , 1989 .

[9]  John B. Adams,et al.  Classification of multispectral images based on fractions of endmembers: Application to land-cover change in the Brazilian Amazon , 1995 .

[10]  Yasushi Yamaguchi,et al.  Analysis of urban heat-island effect using ASTER and ETM+ Data: Separation of anthropogenic heat discharge and natural heat radiation from sensible heat flux , 2005 .

[11]  George Xian,et al.  An analysis of urban thermal characteristics and associated land cover in Tampa Bay and Las Vegas using Landsat satellite data , 2006 .

[12]  S. Yamashita,et al.  Detailed structure of heat island phenomena from moving observations from electric tram-cars in Metropolitan Tokyo , 1996 .

[13]  Qihao Weng.  RECENT PROGRESS IN THERMAL REMOTE SENSING OF URBAN AREAS , 2010 .

[14]  R. C. Larson,et al.  An analysis of an urban heat sink , 1990 .

[15]  Timothy R. Oke,et al.  Urban heat island dynamics in Montreal and Vancouver , 1975 .

[16]  Takatoshi Hiraki,et al.  Characteristic Air Temperature Distributions Observed in Summer and Winter in Urban Area in Japan , 2007, Environmental monitoring and assessment.

[17]  S. Lau,et al.  Nocturnal heat island effect in urban residential developments of Hong Kong , 2005 .

[18]  G. Miliaresis,et al.  Regional thermal and terrain modelling of the Afar Depression from MODIS multi‐temporal monthly night LST data , 2009 .

[19]  Y. Yasuoka,et al.  Assessment with satellite data of the urban heat island effects in Asian mega cities , 2006 .

[20]  D. Streutker.  A remote sensing study of the urban heat island of Houston, Texas , 2002 .

[21]  D. Streutker,et al.  Satellite-measured growth of the urban heat island of Houston, Texas , 2003 .

[22]  Rita Pongrácz,et al.  Remotely sensed thermal information applied to urban climate analysis , 2006 .

[23]  S. Kidder,et al.  A multispectral study of the St. Louis area under snow-covered conditions using NOAA-7 AVHRR data , 1987 .

[24]  T. Williamson,et al.  Intra‐urban differences in canopy layer air temperature at a mid‐latitude city , 2007 .

[25]  Maria Kolokotroni,et al.  Urban heat island characteristics in London during winter , 2009 .

[26]  P. Gong,et al.  Assessment of multi-resolution and multi-sensor data for urban surface temperature retrieval , 2006 .

[27]  G. Fu,et al.  Urban planning indicators, morphology and climate indicators: A case study for a north-south transec , 2011 .

[28]  Jianguo Wu,et al.  Urban heat islands and landscape heterogeneity: linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns , 2009, Landscape Ecology.

[29]  C. Small.  Estimation of urban vegetation abundance by spectral mixture analysis , 2001 .

[30]  Janet Nichol,et al.  Remote Sensing of Urban Heat Islands by Day and Night , 2005 .

[31]  M. G. Estes,et al.  A Decision Support Information System for Urban Landscape Management Using Thermal Infrared Data , 2000 .

[32]  L. Bounoua,et al.  Remote sensing of the urban heat island effect across biomes in the continental USA , 2010 .

[33]  Eyal Ben-Dor,et al.  Diurnal thermal behavior of selected urban objects using remote sensing measurements , 2004 .

[34]  Changshan Wu,et al.  Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery , 2004 .

[35]  Zhongyang Guo,et al.  Spatio-temporal exploratory analysis of urban surface temperature field in Shanghai, China , 2010 .

[36]  Robert C. Balling,et al.  High-resolution surface temperature patterns in a complex urban terrain , 1988 .

[37]  Y. Goldreich.  Urban climate studies in Israel—A review☆ , 1995 .

[38]  W. Yue,et al.  The relationship between land surface temperature and NDVI with remote sensing : application to Shanghai Landsat 7 ETM + data , 2009 .

[39]  J. Zhang,et al.  Change analysis of land surface temperature based on robust statistics in the estuarine area of Pearl River (China) from 1990 to 2000 by Landsat TM/ETM+ data , 2007 .

[40]  Shixiao Yu,et al.  Spatiotemporal dynamics of urban forest conversion through model urbanization in Shenzhen, China , 2011 .

[41]  M. Bauer,et al.  Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery , 2007 .

[42]  Xiaoling Chen,et al.  Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes , 2006 .

[43]  J. Sobrino,et al.  Land surface temperature retrieval from LANDSAT TM 5 , 2004 .

[44]  J. Monteith,et al.  Boundary Layer Climates. , 1979 .

[45]  N. Wong,et al.  The influence of land use on the urban heat island in Singapore , 2007 .

[46]  J. D. Tarpley,et al.  The use of NOAA AVHRR data for assessment of the urban heat island effect , 1993 .

[47]  M. Parry,et al.  The climate of London , 1966 .

[48]  G. D. Jenerette,et al.  Regional relationships between surface temperature, vegetation, and human settlement in a rapidly urbanizing ecosystem , 2007, Landscape Ecology.

[49]  P. Sutton,et al.  Characterizing relationships between population density and nighttime imagery for Denver, Colorado: issues of scale and representation , 2010 .

[50]  B. Dousseta,et al.  Satellite multi-sensor data analysis of urban surface temperatures and landcover , 2003 .

[51]  Qihao Weng,et al.  Managing the adverse thermal effects of urban development in a densely populated Chinese city. , 2004, Journal of environmental management.

[52]  Margaret E. Gardner,et al.  Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models , 1998 .

[53]  T. Oke.  The energetic basis of the urban heat island , 1982 .

[54]  D. Lu,et al.  Urban surface biophysical descriptors and land surface temperature variations , 2006 .

[55]  J. Hill,et al.  Trend analysis of Landsat-TM and -ETM+ imagery to monitor grazing impact in a rangeland ecosystem in Northern Greece , 2008 .

[56]  Qihao Weng.  Thermal infrared remote sensing for urban climate and environmental studies: Methods, applications, and trends , 2009 .

[57]  M. Bauer,et al.  Photogrammetric Engineering & Remote Sensing Comparison of Spectral Analysis Techniques for Impervious Surface Estimation Using Landsat Imagery , 2022 .

[58]  Alan T. Murray,et al.  Estimating impervious surface distribution by spectral mixture analysis , 2003 .

[59]  D. Lu,et al.  Spectral mixture analysis of ASTER images for examining the relationship between urban thermal features and biophysical descriptors in Indianapolis, Indiana, USA , 2006 .