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Characterizing Land Surface Temperature (LST) through Remote Sensing Data for Small-Scale Urban Development Projects in the Gulf Cooperation Council (GCC)

Author

Listed:
  • Maram Ahmed

    (College of Science, University of Bahrain, Zallaq 1054, Bahrain)

  • Mohammed A. Aloshan

    (Department of Architectural Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 12211, Saudi Arabia)

  • Wisam Mohammed

    (Landscape Architecture Department, College of Architecture and Planning, Imam Abdulrahman Bin Faisal University, Dammam 32210, Saudi Arabia)

  • Essam Mesbah

    (Department of Architectural Engineering, College of Engineering, University of Jeddah, Jeddah 21589, Saudi Arabia)

  • Naser A. Alsaleh

    (Department of Industrial Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 12211, Saudi Arabia)

  • Islam Elghonaimy

    (Department of Architecture and Interior Design, The College of Engineering, University of Bahrain, Zallaq 1054, Bahrain)

Abstract

In the context of global climate change, there is a projected increase in land surface temperature (LST) worldwide, amplifying its impacts. This poses a particular concern for countries with hot climates, including the Kingdom of Bahrain as an example for the Gulf Cooperation Council countries (GCC), which are countries with a hot climate. With a surge in population growth, there is a heightened demand for land to accommodate additional residential developments, creating an opportunity to investigate the influence of land use changes on LST variations. To achieve this goal, a residential development project spanning from 2013 to 2023 was undertaken. Landsat 8 OLI/TIRS remote sensing datasets were selected for four climate seasons, each set comprising images before and after development. The analysis involved extracting the LST, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-Up Index (NDBI) on various dates, followed by correlation and regression analyses to explore their interrelationships. The results revealed a significant increase in the mean LST during spring and autumn post-development. A consistent positive association between the LST and NDBI was observed across all seasons, strengthening after development completion. Conversely, there was a pre-development negative correlation between the LST and NDVI, shifting to a positive relationship post-development. These findings empirically support the idea that small-scale residential developments contribute to notable LST increases, primarily due to expanded impervious surfaces. These insights have the potential to inform localized adaptation strategies for small-scale residential development projects, crucial for managing the impacts of rising land surface temperatures.

Suggested Citation

  • Maram Ahmed & Mohammed A. Aloshan & Wisam Mohammed & Essam Mesbah & Naser A. Alsaleh & Islam Elghonaimy, 2024. "Characterizing Land Surface Temperature (LST) through Remote Sensing Data for Small-Scale Urban Development Projects in the Gulf Cooperation Council (GCC)," Sustainability, MDPI, vol. 16(9), pages 1-23, May.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:9:p:3873-:d:1389017
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    References listed on IDEAS

    as
    1. Karol Przeździecki & Jarosław Zawadzki, 2023. "Impact of the Variability of Vegetation, Soil Moisture, and Building Density between City Districts on Land Surface Temperature, Warsaw, Poland," Sustainability, MDPI, vol. 15(2), pages 1-14, January.
    2. Kumar Ashwini & Briti Sundar Sil, 2022. "Impacts of Land Use and Land Cover Changes on Land Surface Temperature over Cachar Region, Northeast India—A Case Study," Sustainability, MDPI, vol. 14(21), pages 1-31, October.
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