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.