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Estimation of Urban–Rural Land Surface Temperature Difference at Different Elevations in the Qinling–Daba Mountains Using MODIS and the Random Forest Model

Author

Listed:
  • Jiale Tang

    (College of Geography and Environmental Science, Henan University, Kaifeng 475004, China)

  • Xincan Lan

    (College of Geography and Environmental Science, Henan University, Kaifeng 475004, China)

  • Yuanyuan Lian

    (College of Geography and Environmental Science, Henan University, Kaifeng 475004, China)

  • Fang Zhao

    (College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
    Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475004, China)

  • Tianqi Li

    (College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
    Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475004, China)

Abstract

Land surface temperature (LST) variations are very complex in mountainous areas owing to highly heterogeneous terrain and varied environment, which complicates the surface urban heat island (SUHI) in mountain cities. Previous studies on the urban heat island (UHI) effect mostly focus on the flat terrain areas; there are few studies on the UHI effect in mountainous areas, especially on the influence of elevation on the SUHI effect. To determine the SUHI in the Qinling–Daba mountains (China), MODIS LST data were first preprocessed and converted to the same elevations (1500 m, 2000 m, 2500 m, 3000 m, and 3500 m) using a digital elevation model and the random forest method. Then, the average LSTs in urban land, rural land, and cultivated land were calculated separately based on the ranges of the invariable urban, rural, and cultivated areas during 2010–2018, and the urban, rural, and cultivated land LST difference were estimated for the same elevations. Results showed that the accuracy of LST estimated using the random forest method is very high (R 2 ≥ 0.9) at elevations of 1500 m, 2000 m, 2500 m, 3000 m and 3500 m. The difference in urban, rural, and cultivated lands’ LST has a trend of decrease with increasing elevation, meaning that the SUHI weakens at higher elevations. The average LST of urban areas is 0.52–0.59 °C (0.42–0.57 °C) higher than that of rural and cultivated areas at an elevation of 1500 m (2000 m). The average LST of urban areas is 0.10–1.25 °C lower than that of rural and cultivated areas at elevations of 2500 m, 3000 m, and 3500 m, indicating absence of the SUHI at those elevations.

Suggested Citation

  • Jiale Tang & Xincan Lan & Yuanyuan Lian & Fang Zhao & Tianqi Li, 2022. "Estimation of Urban–Rural Land Surface Temperature Difference at Different Elevations in the Qinling–Daba Mountains Using MODIS and the Random Forest Model," IJERPH, MDPI, vol. 19(18), pages 1-12, September.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:18:p:11442-:d:912398
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    References listed on IDEAS

    as
    1. Yaoping Cui & Xinliang Xu & Jinwei Dong & Yaochen Qin, 2016. "Influence of Urbanization Factors on Surface Urban Heat Island Intensity: A Comparison of Countries at Different Developmental Phases," Sustainability, MDPI, vol. 8(8), pages 1-14, July.
    2. Fang Zhao & Xincan Lan & Wuyang Li & Wenbo Zhu & Tianqi Li, 2021. "Influence of Land Use Change on the Surface Albedo and Climate Change in the Qinling-Daba Mountains," Sustainability, MDPI, vol. 13(18), pages 1-15, September.
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