4.7 Article

Spatiotemporal Patterns of Land Surface Temperature Change in the Tibetan Plateau Based on MODIS/Terra Daily Product From 2000 to 2018

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSTARS.2021.3089851

Keywords

Land surface temperature; Land surface; Spatial resolution; Market research; MODIS; Spatiotemporal phenomena; Vegetation mapping; Land surface temperature (LST); moderate resolution imaging spectroradiometer (MODIS); Terra; spatiotemporal pattern; Tibetan plateau (TP); trend analysis

Funding

  1. Second Tibetan Plateau Scientific Expedition and Research Program [2019QZKK0404]
  2. National Natural Science Foundation of China [41771409, 42071349]
  3. Sichuan Science and Technology Program [2020JDJQ0003]
  4. CAS Light of West China Program

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Under the context of climate change, this study found a significant warming trend in land surface temperature on the Tibetan Plateau, with nighttime temperatures showing more pronounced changes and areas at elevations of 4500 to 5000 meters experiencing the strongest warming effect. Elevation was identified as the most important factor influencing the spatial distribution of LST.
Under the background of climate change, the Tibetan Plateau presents high spatial and temporal variability in land surface temperature (LST). To understand the spatiotemporal patterns of LST change, this article conducted a spatiotemporal analysis using the Mann-Kendall trend analysis method with time series of mean annual surface temperature extracted from the moderate resolution imaging spectroradiometer/Terra daily LST product from 2000 to 2018. The analysis indicated that both daytime and nighttime MASTs show an obvious warming trend with the average rates of 0.028 K/year and 0.069 K/year, and the nighttime variation has larger spatial coverage. Areas ranging from 4500 to 5000 m exhibited the strongest warming effect. The geodetector method was applied to detect the impacts from seven factors, including elevation, land cover type, latitude, normalized difference vegetation index (NDVI), precipitation, air temperature, and solar radiation on the spatial distribution of LST. The controlling effects of these factors were generally stronger in the nighttime than those in the daytime, and elevation was the most important factor with the contribution scores of 27.12% and 62.98% in the daytime and nighttime, respectively. In addition, the analysis revealed that the temporal changes of LST were mainly caused by surface properties (vegetation, snow cover, and water surface area) changes, radiant flux changes induced by cloud amount changes, and climate warming. In general, this article provides important insights into the spatiotemporal dynamics of LST in the TP since 2000 and helps to reveal the impact of climate change on ecoenvironmental conservation.

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