International Journal of Digital Earth (Dec 2023)

Feedback and contribution of vegetation, air temperature and precipitation to land surface temperature in the Yangtze River Basin considering statistical analysis

  • Jinlian Liu,
  • Xinyao Zhou,
  • Hanya Tang,
  • Fengqin Yan,
  • Shiwei Liu,
  • Xuguang Tang,
  • Zhi Ding,
  • Ke Jiang,
  • Pujia Yu

DOI
https://doi.org/10.1080/17538947.2023.2241423
Journal volume & issue
Vol. 16, no. 1
pp. 2941 – 2961

Abstract

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Land surface temperature (LST), especially day-night LST difference $\lpar {{\rm LS}{\rm T}_{\rm d}-{\rm LS}{\rm T}_{\rm n}} \rpar$, is a key variable for the stability of terrestrial ecosystems, affected by vegetation and climate change. Quantifying the contribution and feedback of vegetation and climate to LST changes is critical to developing mitigation strategies. Based on LST, Normalized vegetation index (NDVI), land use (LU), air temperature (AT) and precipitation (Pre) from 2003 to 2021, partial correlation was used to analyze the response of LST to vegetation and climate. The feedback and contribution of both to LST were further quantified by using spatial linear relationships and partial derivatives analysis. The results showed that both interannual LST $\lpar {{\rm LS}{\rm T}_{\rm y}} \rpar$ and ${\rm LS}{\rm T}_{\rm d}-{\rm LS}{\rm T}_{\rm n}$ responded negatively to vegetation, and vegetation had a negative feedback effect in areas with significantly altered. Vegetation was also a major contributor to the decline of ${\rm LS}{\rm T}_{\rm d}-{\rm LS}{\rm T}_{\rm n}.$ With the advantage of positive partial correlation area of 94.99%, AT became the main driving factor and contributor to ${\rm LS}{\rm T}_{\rm y}$ change trend. Pre contributed negatively to both ${\rm LS}{\rm T}_{\rm y}$ and ${\rm LS}{\rm T}_{\rm d}-{\rm LS}{\rm T}_{\rm n}$, with contributions of −0.004 °C/y and −0.022 °C/y, respectively. AT played a decisive role in LST warming of YRB, which was partially mitigated by vegetation and Pre. The present research contributed to the detection of LST changes and improved understanding of the driving mechanism.

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