基于2005-2019年的MYD11A2时间序列LST遥感数据,首先采用均值标准差法对LST进行分级,分析了天山北坡城市群的LST空间分布格局;其次利用Sen's斜率分析法、Mann-Kendal趋势检验法和Hurst指数揭示了天山北坡城市群LST在2005-2019年和未来的变化趋势;最后借助地理探测器模型并综合考虑地表覆盖、气候、社会经济和地形因素分析了多空间尺度下LST的主要影响因素。结果表明:(1)天山北坡城市群的吐鲁番市是高温(HT)和极高温(EHT)的主要集聚地;白天和夜间的LST格局差异大,在绿洲区域表现为典型的"昼冷岛,夜热岛"特征。(2)LST在白天和夜间的变化率分别为0.04 ℃/a和0.03 ℃/a,白天的升温幅度强于夜间;在乌鲁木齐市、昌吉回族自治州、石河子市和五家渠市LST表现出显著的升高趋势,且在未来也具有相同的趋势。(3)在不同的空间尺度上,LST的主要影响因素不同;从整个天山北坡城市群来看气候因素和地形因素是LST的主要影响因素,而在在石河子市、五家渠市和奎屯市LST的主要影响因素是社会经济因素。
Based on MYD11A2 time series LST remote sensing data from 2005-2019, firstly, the LST was classified by the mean standard deviation method, and the spatial distribution pattern of LST in the urban agglomeration on the northern slope of the Tianshan Mountains was analyzed. Secondly, Sen's slope analysis, Mann-Kendal trend test and Hurst index were used to reveal the changing trends of LST in the urban agglomeration on the northern slope of Tianshan Mountains from 2005-2019 and in the future. Finally, the main influencing factors of LST at multi-spatial scales were analyzed by the geographic detector model and comprehensively considering land cover, climate, socio-economic and topographic factors. The results showed that: (1) Turpan City in the urban agglomeration on the northern slope of the Tianshan Mountains was the main cluster area of high temperature (HT) and extremely high temperature (EHT). The LST patterns of daytime and nighttime were quite different. In the oasis area, it showed the typical characteristics of cool island in the daytime and heat island in the nighttime. (2) The warming rate of LST was stronger during the day than at night, with 0.04 ℃/a and 0.03 ℃/a during the day and night, respectively. In Urumqi City, Changji Hui Autonomous Prefecture, Shihezi City and Wujiaqu City, LST showed a significant increasing trend and had the same trend in the future. (3) The main influencing factors of LST were different at different scales. Climatic and topographic factors are the main influencing factors of LST from the scale of the whole urban agglomeration on the northern slope of Tianshan Mountains. From the city scale, the main influencing factors of LST in Shihezi, Wujiaqu and Kuitun cities are socio-economic factors.