The impact of built-up surfaces on land surface temperatures in Italian urban areas.

Urban areas are characterized by the very high degree of soil sealing and continuous built-up areas: Italy is one of the European countries with the highest artificial land cover rate, which causes a substantial spatial variation in the land surface temperature (LST), modifying the urban microclimate and contributing to the urban heat island effect. Nevertheless, quantitative data regarding the contribution of different densities of built-up surfaces in determining urban spatial LST changes is currently lacking in Italy. This study, which aimed to provide clear and quantitative city-specific information on annual and seasonal spatial LST modifications resulting from increased urban built-up coverage, was conducted generally throughout the whole year, and specifically in two different periods (cool/cold and warm/hot periods). Four cities (Milan, Rome, Bologna and Florence) were included in the study. The LST layer and the built-up-surface indicator were obtained via use of MODIS remote sensing data products (1km) and a very high-resolution map (5m) of built-up surfaces recently developed by the Italian National Institute for Environmental Protection and Research. The relationships between the dependent (mean daily, daytime and nighttime LST values) and independent (built-up surfaces) variables were investigated through linear regression analyses, and comprehensive built-up-surface-related LST maps were also developed. Statistically significant linear relationships (p<0.001) between built-up surfaces and spatial LST variations were observed in all the cities studied, with a higher impact during the warm/hot period than in the cool/cold ones. Daytime and nighttime LST slope patterns depend on the city size and relative urban morphology. If implemented in the existing city plan, the urban maps of built-up-surface-related LST developed in this study might be able to support more sustainable urban land management practices by identifying the critical areas (Hot-Spots) that would benefit most from mitigation actions by local authorities, land-use decision makers, and urban planners.

[1]  Qihao Weng,et al.  Remote sensing of impervious surfaces in the urban areas: Requirements, methods, and trends , 2012 .

[2]  P. Sutton,et al.  Paving the planet: impervious surface as proxy measure of the human ecological footprint , 2009 .

[3]  T. Oke City size and the urban heat island , 1973 .

[4]  Bernardino Romano,et al.  Land urbanization in Central Italy: 50 years of evolution , 2014 .

[5]  Yi‐Chen Wang,et al.  Dynamics of Land Surface Temperature in Response to Land-Use/Cover Change , 2011 .

[6]  M. Artmann Assessment of Soil Sealing Management Responses, Strategies, and Targets Toward Ecologically Sustainable Urban Land Use Management , 2014, AMBIO.

[7]  Roger Bivand,et al.  Bindings for the Geospatial Data Abstraction Library , 2015 .

[8]  A. Arnfield Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island , 2003 .

[9]  Bert Guindon,et al.  Multispectral analysis for manmade surface extraction from RapidEye and SPOT5 , 2012 .

[10]  F. Giorgi,et al.  Climate change hotspots , 2006 .

[11]  G. Carrus,et al.  Benefits and well-being perceived by people visiting green spaces in periods of heat stress. , 2009 .

[12]  K. Kawamura,et al.  Temporal change and its spatial variety on land surface temperature and land use changes in the Red River Delta, Vietnam, using MODIS time-series imagery , 2015, Environmental Monitoring and Assessment.

[13]  Piero Toscano,et al.  Urban-Hazard Risk Analysis: Mapping of Heat-Related Risks in the Elderly in Major Italian Cities , 2015, PloS one.

[14]  D. Lu,et al.  Extraction of urban impervious surfaces from an IKONOS image , 2009 .

[15]  Keechoo Choi,et al.  Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Dhaka, Bangladesh , 2013, Remote. Sens..

[16]  Yihui Xie,et al.  Create Interactive Web Maps with the JavaScript 'Leaflet'Library , 2015 .

[17]  Yogesh Kant,et al.  Assessment of land surface temperature and heat fluxes over Delhi using remote sensing data. , 2015, Journal of environmental management.

[18]  K. Oleson,et al.  Strong contributions of local background climate to urban heat islands , 2014, Nature.

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

[20]  Beniamino Murgante,et al.  Evaluation of urban sprawl from space using open source technologies , 2015, Ecol. Informatics.

[21]  L. Salvati,et al.  Estimating soil sealing rate at national level—Italy as a case study , 2013 .

[22]  R. Betts,et al.  Climate change in cities due to global warming and urban effects , 2010 .

[23]  Itai Kloog,et al.  Temporal and spatial assessments of minimum air temperature using satellite surface temperature measurements in Massachusetts, USA. , 2012, The Science of the total environment.

[24]  C. Arnold,et al.  IMPERVIOUS SURFACE COVERAGE: THE EMERGENCE OF A KEY ENVIRONMENTAL INDICATOR , 1996 .

[25]  Qihao Weng,et al.  The impact of land use and land cover changes on land surface temperature in a karst area of China. , 2007, Journal of environmental management.

[26]  Jan Verbesselt,et al.  Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology , 2013, Remote. Sens..

[27]  Changshan Wu,et al.  Quantifying high‐resolution impervious surfaces using spectral mixture analysis , 2009 .

[28]  F. Giorgi,et al.  Climate change projections for the Mediterranean region , 2008 .

[29]  Henning Nuissl,et al.  Does urban sprawl drive changes in the water balance and policy?: The case of Leipzig (Germany) 1870–2003 , 2007 .

[30]  F. Giorgi,et al.  Climate change hot‐spots , 2006 .

[31]  A. Mariotti,et al.  Decadal climate variability in the Mediterranean region: roles of large-scale forcings and regional processes , 2010, Climate Dynamics.

[32]  M. O. Obiakor,et al.  Effects of Vegetated and Synthetic (Impervious) Surfaces on the Microclimate of Urban Area , 2012 .