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Seasonal and Diurnal Variation of Land Surface Temperature Distribution and Its Relation to Land Use/Land Cover Patterns

Author

Listed:
  • Ruirui Dong

    (Earth Observation Center (EOC), German Aerospace Center (DLR), 82234 Oberpfaffenhofen, Germany)

  • Michael Wurm

    (Earth Observation Center (EOC), German Aerospace Center (DLR), 82234 Oberpfaffenhofen, Germany)

  • Hannes Taubenböck

    (Earth Observation Center (EOC), German Aerospace Center (DLR), 82234 Oberpfaffenhofen, Germany
    Institute for Geography and Geology, Julius-Maximilians-Universität Würzburg, 97074 Würzburg, Germany)

Abstract

The surface urban heat island (SUHI) affects the quality of urban life. Because varying urban structures have varying impacts on SUHI, it is crucial to understand the impact of land use/land cover characteristics for improving the quality of life in cities and urban health. Satellite-based data on land surface temperatures (LST) and derived land use/cover pattern (LUCP) indicators provide an efficient opportunity to derive the required data at a large scale. This study explores the seasonal and diurnal variation of spatial associations from LUCP and LST employing Pearson correlation and ordinary least squares regression analysis. Specifically, Landsat-8 images were utilized to derive LSTs in four seasons, taking Berlin as a case study. The results indicate that: (1) in terms of land cover, hot spots are mainly distributed over transportation, commercial and industrial land in the daytime, while wetlands were identified as hot spots during nighttime; (2) from the land composition indicators, the normalized difference built-up index (NDBI) showed the strongest influence in summer, while the normalized difference vegetation index (NDVI) exhibited the biggest impact in winter; (3) from urban morphological parameters, the building density showed an especially significant positive association with LST and the strongest effect during daytime.

Suggested Citation

  • Ruirui Dong & Michael Wurm & Hannes Taubenböck, 2022. "Seasonal and Diurnal Variation of Land Surface Temperature Distribution and Its Relation to Land Use/Land Cover Patterns," IJERPH, MDPI, vol. 19(19), pages 1-20, October.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12738-:d:934118
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    References listed on IDEAS

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    1. Harlan, Sharon L. & Brazel, Anthony J. & Prashad, Lela & Stefanov, William L. & Larsen, Larissa, 2006. "Neighborhood microclimates and vulnerability to heat stress," Social Science & Medicine, Elsevier, vol. 63(11), pages 2847-2863, December.
    2. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
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    Cited by:

    1. Xiangming Mao & Gula Tang & Jiaqiang Du & Xiaotong Tian, 2023. "Biophysical Effects of Land Cover Changes on Land Surface Temperature on the Sichuan Basin and Surrounding Regions," Land, MDPI, vol. 12(11), pages 1-14, October.
    2. Mengze Fu & Kangjia Ban & Li Jin & Di Wu, 2024. "How Urban Street Spatial Composition Affects Land Surface Temperature in Areas with Different Population Densities: A Case Study of Zhengzhou, China," Sustainability, MDPI, vol. 16(22), pages 1-17, November.

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