Spatiotemporal variation of land surface temperature and its driving factors in Xinjiang,China

作     者：ZHANG Mingyu CAO Yu ZHANG Zhengyong ZHANG Xueying LIU Lin CHEN Hongjin GAO Yu YU Fengchen LIU Xinyi ZHANG Mingyu;CAO Yu;ZHANG Zhengyong;ZHANG Xueying;LIU Lin;CHEN Hongjin;GAO Yu;YU Fengchen;LIU Xinyi

作者机构：College of SciencesShihezi UniversityShihezi 832000China Key Laboratory of Oasis Town and Mountain-Basin System EcologyXinjiang Production and Construction CorpsShihezi 832000China Yantai Institute of Coastal Zone ResearchChinese Academy of SciencesYantai 264003China 

出 版 物：《Journal of Arid Land》 (干旱区科学（英文版）)

年 卷 期：2024年第16卷第3期

页      面：373-395页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 0706[理学-大气科学] 

基　　金：supported by the Third Xinjiang Scientific Expedition Program(2021xjkk0801) 

主　　题：land surface temperature MOD11C3 climate change geographical detector(Geodetector) geographically weighted regression(GWR) source-sink effect Xinjiang 

摘      要：Land surface temperature(LST) directly affects the energy balance of terrestrial surface systems and impacts regional resources, ecosystem evolution, and ecosystem structures. Xinjiang Uygur Autonomous Region is located at the arid Northwest China and is extremely sensitive to climate change. There is an urgent need to understand the distribution patterns of LST in this area and quantitatively measure the nature and intensity of the impacts of the major driving factors from a spatial perspective, as well as elucidate the formation mechanisms. In this study, we used the MOD11C3 LST product developed on the basis of Moderate Resolution Imaging Spectroradiometer(MODIS) to conduct regression analysis and determine the spatiotemporal variation and differentiation pattern of LST in Xinjiang from 2000 to 2020. We analyzed the driving mechanisms of spatial heterogeneity of LST in Xinjiang and the six geomorphic zones(the Altay Mountains, Junggar Basin, Tianshan Mountains, Tarim Basin, Turpan-Hami(Tuha) Basin, and Pakakuna Mountain Group) using geographical detector(Geodetector) and geographically weighted regression(GWR) models. The warming rate of LST in Xinjiang during the study period was 0.24℃/10a, and the spatial distribution pattern of LST had obvious topographic imprints, with 87.20% of the warming zone located in the Gobi desert and areas with frequent human activities, and the cooling zone mainly located in the mountainous areas. The seasonal LST in Xinjiang was at a cooling rate of 0.09℃/10a in autumn, and showed a warming trend in other seasons. Digital elevation model(DEM), latitude, wind speed, precipitation, normalized difference vegetation index(NDVI), and sunshine duration in the single-factor and interactive detections were the key factors driving the LST changes. The direction and intensity of each major driving factor on the spatial variations of LST in the study area were heterogeneous. The negative feedback effect of DEM on the spatial differentiation o