International Journal of Applied Earth Observation and Geoinformation · 2021 · 72 citations · 63 references
Natural SciencesEarth SciencesPhysical GeographyClimate ScienceClimatologyTime Series AnalysisClimate ChangeLand Surface ProcessesRemote Sensing Change DetectionAtmosphere-land InteractionClimate Trend AnalysisLand - Atmosphere CouplingSurface TemperatureSurface Temperature DynamicsSurface Temperature Time Series Analysis
Land surface temperature (LST) is an essential parameter in land–atmosphere interaction. However, it is still poorly understood about the effects of seasonal LST on the interannual LST change and the dominant driving force for the variation in LST. In this study, trends of time-series LST were analyzed by using both linear and nonlinear methods. Two indices were developed to evaluate the effects of seasonal LST trends on interannual LST change. The main driving factor of LST was identified based on each pixel. Two turning points were founded in 2007 and 2011 during the study period of 2003–2019. A significant cooling trend of LST appeared from 2007 to 2011/2012 with the rates of −0.2237 K/year (daytime) and −0.1239 K/year (nighttime). LST increased in almost all seasons except the daytime in autumn. The warming effect in spring and winter contributed 69.43% to interannual warming of daytime LST, and accounted for 59.02% of interannual warming of nighttime LST. In most regions of China, air temperature and vegetation were the dominant factors influencing the change of LST. The current research improved our understanding of changes of LST and the results can serve for mitigating and adapting to climate change.
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