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<p>UHIs are exacerbated by urbanization, which is on the rise in both developed and developing countries and is seen as a marker of progress. Changes to metropolitan landscapes have led to varied climates, even among urban areas situated within the same climatic zone. Utilizing remote sensing data from Thailand between 2015 to 2023, this study examines the spatiotemporal patterns of night-time light (NTL) and night land surface temperature (LST), employing the Google Earth Engine (GEE). The geographical response relationship between these factors was also investigated using hotspot analysis, local Moran's I spatial autocorrelation, and standard deviation techniques. According to research findings, NTL increased while night LST decreased in Bangkok, Pattaya City, Phuket, Hat Yai, and Chiang Mai, falling from 28.13&#xa0;°C in 2015 to 27.54&#xa0;°C in 2023. From 2015 to 2023, the highest Bidirectional Reflectance Distribution Function's (BRDF) NTL rose from 232.36 nW/sr/cm<sup>2</sup> to 265.91 nW/sr/cm<sup>2</sup>. Reports indicate that 99% of hotspots in Bangkok, Chiang Mai, Hat Yai, and Phuket often form high clusters. The midnight LST and NTL for the years studied exhibit a strong correlation as indicated by R<sup>2</sup> values. A year-by-year analysis of national data suggests that innovative adaptation strategies should be implemented to protect Thailand's tourism assets.</p>

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Remote sensing-based impact analysis of artificial lighting on land surface temperature using google earth engine

  • 期刊论文

  • 发表日期：

    2025年7月2日

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  • Biswarup Rana,
  • Bijay Halder,
  • Neyara Radwan,
  • Malay Pramanik,
  • Minhaz Farid Ahmed,
  • Fahad Alshehri,
  • Chaitanya Baliram Pande

摘要

UHIs are exacerbated by urbanization, which is on the rise in both developed and developing countries and is seen as a marker of progress. Changes to metropolitan landscapes have led to varied climates, even among urban areas situated within the same climatic zone. Utilizing remote sensing data from Thailand between 2015 to 2023, this study examines the spatiotemporal patterns of night-time light (NTL) and night land surface temperature (LST), employing the Google Earth Engine (GEE). The geographical response relationship between these factors was also investigated using hotspot analysis, local Moran's I spatial autocorrelation, and standard deviation techniques. According to research findings, NTL increased while night LST decreased in Bangkok, Pattaya City, Phuket, Hat Yai, and Chiang Mai, falling from 28.13 °C in 2015 to 27.54 °C in 2023. From 2015 to 2023, the highest Bidirectional Reflectance Distribution Function's (BRDF) NTL rose from 232.36 nW/sr/cm2 to 265.91 nW/sr/cm2. Reports indicate that 99% of hotspots in Bangkok, Chiang Mai, Hat Yai, and Phuket often form high clusters. The midnight LST and NTL for the years studied exhibit a strong correlation as indicated by R2 values. A year-by-year analysis of national data suggests that innovative adaptation strategies should be implemented to protect Thailand's tourism assets.