Income Driven Patterns of the Urban Environment
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Institute of Physics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre 91501-970, Brazil
2
Urban Climates Research Project (UCR), University of South Australia (UniSA), Adelaide SA 5001, Australia
3
Graduate Program in Architecture and Urbanism, University of Vale do Rio dos Sinos (UNISINOS), São Leopoldo 93022-000, Brazil
4
Centre for Industrial and Applied Mathematics, University of South Australia (UniSA), Adelaide SA 5001, Australia
5
Undergraduate Program in Civil Engineering, University of do Vale do Rio dos Sinos (UNISINOS), São Leopoldo 93022-750, Brazil
6
Cooperative Research Centre for Low Carbon Living (CRC-LCL), University of New South Wales (UNSW), Sydney NSW 2052, Australia
*
Author to whom correspondence should be addressed.
Academic Editor: Giuseppe Ioppolo
Sustainability 2017, 9(2), 275; https://doi.org/10.3390/su9020275
Received: 15 December 2016 / Revised: 9 February 2017 / Accepted: 9 February 2017 / Published: 15 February 2017
(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)
This study investigates the land surface temperature (LST) distribution from thermal infrared data for analyzing the characteristics of surface coverage using the Vegetation–Impervious–Soil (VIS) approach. A set of ten images, obtained from Landsat-5 Thematic Mapper, between 2001 and 2010, were used to study the urban environmental conditions of 47 neighborhoods of Porto Alegre city, Brazil. Porto Alegre has had the smallest population growth rate of all 27 state capitals in the last two decades in Brazil, with an increase of 11.55% in inhabitants from 1.263 million in 1991 to 1.409 million in 2010. We applied the environmental Kuznets curve (EKC) theory in order to test the influence of the economically-related scenario on the spatial nature of social-environmental arrangement of the city at neighborhood scale. Our results suggest that the economically-related scenario exerts a non-negligible influence on the physically driven characteristics of the urban environmental conditions as predicted by EKC theory. The linear inverse correlation R2 between household income (HI) and LST is 0.36 and has shown to be comparable to all other studied variables. Future research may investigate the relation between other economically-related indicators to specific land surface characteristics.
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Keywords:
thermal remote sensing; EKC theory; urban development
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MDPI and ACS Style
Gusso, A.; Silva, A.; Boland, J.; Lenz, L.; Philipp, C. Income Driven Patterns of the Urban Environment. Sustainability 2017, 9, 275. https://doi.org/10.3390/su9020275
AMA Style
Gusso A, Silva A, Boland J, Lenz L, Philipp C. Income Driven Patterns of the Urban Environment. Sustainability. 2017; 9(2):275. https://doi.org/10.3390/su9020275
Chicago/Turabian StyleGusso, Anibal, André Silva, John Boland, Leticia Lenz, and Conrad Philipp. 2017. "Income Driven Patterns of the Urban Environment" Sustainability 9, no. 2: 275. https://doi.org/10.3390/su9020275
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