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Multi-Temporal Patterns of Urban Heat Island as Response to Economic Growth Management

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  • Anibal Gusso

    (Environmental Engineering, Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo-RS CP275, Brazil
    Advanced Visualization Laboratory, Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo-RS CP275, Brazil)

  • Cristina Cafruni

    (Graduate Program in Collective Health, Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo-RS CP275, Brazil)

  • Fabiane Bordin

    (Advanced Visualization Laboratory, Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo-RS CP275, Brazil
    Civil, Cartographic and Surveying Engineering, Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo-RS CP275, Brazil)

  • Mauricio Roberto Veronez

    (Advanced Visualization Laboratory, Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo-RS CP275, Brazil
    Graduate Program in Geology, Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo-RS CP275, Brazil)

  • Leticia Lenz

    (Advanced Visualization Laboratory, Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo-RS CP275, Brazil
    These authors contributed equally to this work.)

  • Sabrina Crija

    (Advanced Visualization Laboratory, Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo-RS CP275, Brazil
    These authors contributed equally to this work.)

Abstract

For a reliable assessment of sustainability in big cities, it is imperative to evaluate urban ecosystem conditions and the environment of the cities undergoing economic growth. Urban green spaces are valuable sources of evapotranspiration, which is generated by trees and vegetation; these spaces mitigate urban heat islands in cities. Land surface temperature (LST) is closely related to the distribution of land-use and land-cover characteristics and can be used as an indicator of urban environment conditions and development. This study evaluates the patterns of LST distribution through time by employing the thermal spatial distribution signature procedure using thermal infrared data obtained from Landsat-5 Thematic Mapper. A set of 18 images, between 1985 and 2010, was used to study the urban environment during summer in 47 neighborhoods of Porto Alegre, Brazil. On a neighborhood scale, results show a non-linear inverse correlation (R² = 0.55) between vegetation index and LST. The overall average of the LST is 300.23 K (27.8 °C) with a standard deviation of 1.25 K and the maximum average difference of 2.83 K between neighborhoods. Results show that the Thermal Spatial Distribution Signature (TSDS) analysis can help multi-temporal studies for the evaluation of UHI through time.

Suggested Citation

  • Anibal Gusso & Cristina Cafruni & Fabiane Bordin & Mauricio Roberto Veronez & Leticia Lenz & Sabrina Crija, 2015. "Multi-Temporal Patterns of Urban Heat Island as Response to Economic Growth Management," Sustainability, MDPI, vol. 7(3), pages 1-17, March.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:3:p:3129-3145:d:46853
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    References listed on IDEAS

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    1. World Commission on Environment and Development,, 1987. "Our Common Future," OUP Catalogue, Oxford University Press, number 9780192820808.
    2. Li Shen & Jared M. Kyllo & Xulin Guo, 2013. "An Integrated Model Based on a Hierarchical Indices System for Monitoring and Evaluating Urban Sustainability," Sustainability, MDPI, vol. 5(2), pages 1-36, February.
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    Cited by:

    1. Stefania Bonafoni & Giorgio Baldinelli & Paolo Verducci & Andrea Presciutti, 2017. "Remote Sensing Techniques for Urban Heating Analysis: A Case Study of Sustainable Construction at District Level," Sustainability, MDPI, vol. 9(8), pages 1-12, July.
    2. Yaoping Cui & Xinliang Xu & Jinwei Dong & Yaochen Qin, 2016. "Influence of Urbanization Factors on Surface Urban Heat Island Intensity: A Comparison of Countries at Different Developmental Phases," Sustainability, MDPI, vol. 8(8), pages 1-14, July.
    3. Quanlong Feng & Jianhua Gong & Jiantao Liu & Yi Li, 2015. "Monitoring Cropland Dynamics of the Yellow River Delta based on Multi-Temporal Landsat Imagery over 1986 to 2015," Sustainability, MDPI, vol. 7(11), pages 1-25, November.
    4. Anibal Gusso & André Silva & John Boland & Leticia Lenz & Conrad Philipp, 2017. "Income Driven Patterns of the Urban Environment," Sustainability, MDPI, vol. 9(2), pages 1-20, February.

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