{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T18:21:44Z","timestamp":1784053304768,"version":"3.55.0"},"reference-count":65,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2021,9,22]],"date-time":"2021-09-22T00:00:00Z","timestamp":1632268800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42030612"],"award-info":[{"award-number":["42030612"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Second Tibetan Plateau Scientific Expedition and Research (STEP) program","award":["2019QZKK010206"],"award-info":[{"award-number":["2019QZKK010206"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Land surface temperature (LST) is an important parameter that affects the water cycle, environmental changes, and energy balance at global and regional scales. Herein, a time series analysis was conducted to estimate the monthly, seasonal, and interannual variations in LST during 2001\u20132019 in the Tarim Basin, China. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) LST, air temperature, air pressure, relative humidity, wind speed, precipitation, elevation, and land-cover type data, we analyzed the spatio-temporal change characteristics of LST and the influencing factors. High LSTs occurred in the desert and plains and low LSTs occurred in surrounding mountain regions. The highest LST was recorded in July (25.1 \u00b0C) and the lowest was in January (\u22129.5 \u00b0C). On a seasonal scale, LST decreased in the order: summer &gt; spring &gt; autumn &gt; winter. Annual LST showed an increasing trend of 0.2 \u00b0C\/10 a in the desert and mountain areas, while the plains indicated a decreasing trend. In spring and autumn, western regions were dominated by a downward trend, whereas in winter a downward trend occurred in eastern regions. In summer, areas covered by vegetation were dominated by a downward trend, and desert and bare lands were dominated by an upward trend. Random forest (RF) model analysis showed that elevation was the most significant influencing factor (22.1%), followed by mean air temperature (20.1%). Correlation analysis showed that the main climatic factors air temperature, relative humidity, and elevation have a good correlation with the LST. Land-cover type also affected LST; during February\u2013December the lowest LST was observed for permanent glacier snow and the highest was observed in the desert. El Nino and La Nina greatly influenced the LST variations. The North Atlantic Oscillation and Pacific Decadal Oscillation indices were consistent with the mean LST anomaly, indicating their considerable influence on LST variations.<\/jats:p>","DOI":"10.3390\/rs13193792","type":"journal-article","created":{"date-parts":[[2021,9,22]],"date-time":"2021-09-22T22:50:48Z","timestamp":1632351048000},"page":"3792","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Spatio-Temporal Changes of Land Surface Temperature and the Influencing Factors in the Tarim Basin, Northwest China"],"prefix":"10.3390","volume":"13","author":[{"given":"Alim","family":"Abbas","sequence":"first","affiliation":[{"name":"College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, China"},{"name":"Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China"},{"name":"Taklimagan Desert Meteorolgy Field Experiment Station of CMA, Qiemo 841000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qing","family":"He","sequence":"additional","affiliation":[{"name":"Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China"},{"name":"Taklimagan Desert Meteorolgy Field Experiment Station of CMA, Qiemo 841000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lili","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Atmospheric Sciences, Yunnan University, Kunming 650500, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinglong","family":"Li","sequence":"additional","affiliation":[{"name":"College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, China"},{"name":"Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China"},{"name":"Taklimagan Desert Meteorolgy Field Experiment Station of CMA, Qiemo 841000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Akida","family":"Salam","sequence":"additional","affiliation":[{"name":"Kezhou Meteorological Administration, Kezhou 845350, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Lu","sequence":"additional","affiliation":[{"name":"China National Climate Center, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yierpanjiang","family":"Yasheng","sequence":"additional","affiliation":[{"name":"Xinjiang Meteorological Observatory, Urumqi 830046, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,22]]},"reference":[{"key":"ref_1","unstructured":"Zhang, X.F., and Liao, C.H. 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