Spatiotemporal Analysis of Land Use/Land Cover and Its Effects on Surface Urban Heat Island Using Landsat Data: A Case Study of Metropolitan City Tehran (1988–2018)

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Abstract

This article summarized the spatiotemporal pattern of land use/land cover (LU/LC) and urban heat island (UHI) dynamics in the Metropolitan city of Tehran between 1988 and 2018. The study showed dynamics of each LU/LC class and their role in influencing the UHI. The impervious surface area expanded by 286.04 (48.27% of total land) and vegetated land was depleted by 42.06 km2 (7.10% of total land) during the period of 1988–2018. The mean land surface temperature (LST) has enlarged by approximately 2–3 °C at the city center and 5–7 °C at the periphery between 1988 and 2018 based on the urban–rural gradient analysis. The lower mean LST was experienced by vegetation land (VL) and water body (WB) by approximately 4–5 °C and 5–7 °C, respectively, and the higher mean LST by open land (OL) by 7–11 °C than other LU/LC classes at all time-points during the time period, 1988–2018. The magnitude of mean LST was calculated based on the main LU/LC categories, where impervious land (IL) recorded the higher temperature difference compared to vegetation land (VL) and water bodies (WB). However, open land (OL) recorded the highest mean LST differences with all the other LU/LC categories. In addition to that, there was an overall negative correlation between LST and the normal difference vegetation index (NDVI). By contrast, there was an overall positive correlation between LST and the normal difference built-up index (NDBI). This article, executed through three decadal change analyses from 1988 to 2018 at 10-year intervals, has made a significant contribution to delineating the long records of change dynamics and could have a great influence on policy making to foster environmental sustainability.

Journal

  • Sustainability

    Sustainability 10(12), 4433, 2018-11

    MDPI

Codes

  • NII Article ID (NAID)
    120006582982
  • Text Lang
    ENG
  • Article Type
    journal article
  • ISSN
    2071-1050
  • Data Source
    IR 
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