Income Driven Patterns of the Urban Environment

Anibal Gusso, André Silva, John Boland, Leticia Lenz and Conrad Philipp
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Anibal Gusso: Institute of Physics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre 91501-970, Brazil
André Silva: Graduate Program in Architecture and Urbanism, University of Vale do Rio dos Sinos (UNISINOS), São Leopoldo 93022-000, Brazil
John Boland: Urban Climates Research Project (UCR), University of South Australia (UniSA), Adelaide SA 5001, Australia
Leticia Lenz: Undergraduate Program in Civil Engineering, University of do Vale do Rio dos Sinos (UNISINOS), São Leopoldo 93022-750, Brazil
Conrad Philipp: Urban Climates Research Project (UCR), University of South Australia (UniSA), Adelaide SA 5001, Australia

Sustainability, 2017, vol. 9, issue 2, 1-20

Abstract: 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 R 2 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.

Keywords: thermal remote sensing; EKC theory; urban development (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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