Permafrost conditions in mountain ranges are sensitive to regional land surface temperature (LST), among other factors. To explore that relationship, this study carried out 3 steps: (1) validated Moderate Resolution Imaging Spectroradiometer 1-km daily LST data using data measured in situ, (2) used the Harmonic Analysis of Time Series (HANTS) algorithm for fitting and removing the influence of clouds, and (3) analyzed the spatial and temporal characteristics of LST dynamics in the central Tien Shan mountain range based on remote-sensing data improved by covariance and empirical orthogonal function analysis. The results indicate that the in situ data present a basic reference for rebuilding invalid values in the retrieved data, and the data gap in daily LST products can be logically reconstructed with the HANTS algorithm. Major long-term and large-scale patterns can be well extracted with the reconstructed LST data. The most dynamic and sensitive LST areas occurred in the buffers around the periglacial areas. Areas above the periglacial line mainly exhibited a decrease in LST, while areas below it showed an increase. This suggests that the periglacial line of the central Tien Shan region has risen during the past decade. These findings can provide a reference for how periglacial areas respond to climate change and how this may affect hydrological and ecological processes.