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Investigating the relationship between urban sprawl and urban heat island using remote sensing and machine learning approaches

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Abstract

Urbanization is triggering the expansion in an unplanned and unrestricted manner, growth of outward expansion for some areas. One such important environmental and ecological hazard in recent decades is urban heat island (UHI) and urban thermal field variation index (UTFVI). Studies employing temporal satellite imagery from 1991 to 2021 focused on the appraisal of spatiotemporal patterns of urbanization and UHI in West Bengal’s mid-sized cities (Medinipur and Kharagpur city). This study examines competencies of remote sensing (RS) and GIS procedures in empathetic heat effects and urban thermal conditions using Landsat datasets and GEE cloud software-based time-consuming conventional method. The change detection analysis revealed that built-up lands developed since 7.88–26.94% (1991–2021). The UHI’s highest value in 1991 is 4.57 and in 2021 it increased by 6.87%. The highest 0.34% UTFVI value is found in the year 1991, but in 2021, the highest value was shown at 0.35% in this study area. The mean NDVI value increased from 1991 (0.29%) to 2021 (0.44%). The land surface temperature (LST) maps have been prepared using Landsat 5 and Landsat 8 surface reflectance datasets. Anthropogenic-related ecological changes in urbanized areas are concerning these days since they have the potential to negatively impact both the environment and human health. The investigation has shown that while LULC alterations were sufficiently large, unplanned changes to it can have a detrimental effect on the environment. Investigation established an operative systematic methods application to measure urbanization appearances and urban thermal conditions in Medinipur and Kharagpur city.

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Acknowledgements

The authors are thankful to the Vidyasagar University for this research opportunity and truly thankful for local government body for field survey and data collection.

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Authors and Affiliations

  1. Department of Remote Sensing and GIS, Vidyasagar University, Midnapore, 721102, India

    Biswarup Rana & Jatisankar Bandyopadhyay

  2. Department of Earth Sciences and Environment, Faculty of Sciences and Technology, Universiti Kebangsaan Malaysia, UKM, Bangi, Selangor, 43600, Malaysia

    Bijay Halder

  3. New Era and Development in Civil Engineering Research Group, Scientific Research Center, Al-Ayen University, Nasiriyah, 64001, Iraq

    Bijay Halder

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Biswarup Rana: conceptualization; data curation; formal analysis; investigation; software; visualization; writing—original draft, review and editing draft preparation; resources. Jatisankar Bandyopadhyay: supervision, investigation; visualization; writing—original draft, review and editing draft preparation Bijay Halder: conceptualization; data curation; formal analysis; methodology; supervision, investigation; project administration; software; visualization; writing—original draft, review and editing draft preparation.

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Rana, B., Bandyopadhyay, J. & Halder, B. Investigating the relationship between urban sprawl and urban heat island using remote sensing and machine learning approaches. Theor Appl Climatol 155, 4161–4188 (2024). https://doi.org/10.1007/s00704-024-04874-1

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