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Journal of Arid Land  2024, Vol. 16 Issue (3): 373-395    DOI: 10.1007/s40333-024-0072-5
Research article     
Spatiotemporal variation of land surface temperature and its driving factors in Xinjiang, China
ZHANG Mingyu1,2, CAO Yu1,2, ZHANG Zhengyong1,2,*(), ZHANG Xueying3, LIU Lin1,2, CHEN Hongjin1,2, GAO Yu1,2, YU Fengchen1,2, LIU Xinyi1,2
1College of Sciences, Shihezi University, Shihezi 832000, China
2Key Laboratory of Oasis Town and Mountain-Basin System Ecology, Xinjiang Production and Construction Corps, Shihezi 832000, China
3Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China
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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°C/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°C/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 of LST was the strongest. Lower latitudes, lower vegetation coverage, lower levels of precipitation, and longer sunshine duration increased LST. Unused land was the main heat source landscape, water body was the most important heat sink landscape, grassland and forest land were the land use and land cover (LULC) types with the most prominent heat sink effect, and there were significant differences in different geomorphic zones due to the influences of their vegetation types, climatic conditions, soil types, and human activities. The findings will help to facilitate sustainable climate change management, analyze local climate and environmental patterns, and improve land management strategies in Xinjiang and other arid areas.

Key wordsland surface temperature      MOD11C3      climate change      geographical detector (Geodetector)      geographically weighted regression (GWR)      source-sink effect      Xinjiang     
Received: 20 October 2023      Published: 31 March 2024
Corresponding Authors: *ZHANG Zhengyong (E-mail:
About author: First author contact:

The first and second authors contributed equally to this work.

Cite this article:

ZHANG Mingyu, CAO Yu, ZHANG Zhengyong, ZHANG Xueying, LIU Lin, CHEN Hongjin, GAO Yu, YU Fengchen, LIU Xinyi. Spatiotemporal variation of land surface temperature and its driving factors in Xinjiang, China. Journal of Arid Land, 2024, 16(3): 373-395.

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Fig. 1 Overview of Xinjiang Uygur Autonomous Region and the six geomorphic zones (the Altay Mountains, Junggar Basin, Tianshan Mountains, Turpan-Hami (Tuha) Basin, Tarim Basin, and Pakakuna Mountain Group) based on the digital elevation model (DEM). Note that the figure is based on the standard map (GS(2023)2767) of the Map Service System (, and the standard map has not been modified. The Pamir Plateau, Karakoram Mountains, Kunlun Mountains, and Altun Mountains are collectively referred to as the Pakakuna Mountain Group.
Data name Unit Period Resolution Data source
LST 2000-2020 0.05° NASA (
NDVI - 2000-2020 250 m NASA (
Precipitation mm 2000-2020 1 km RESDC (
Wind speed m/s 2000-2020 1 km RESDC (
Sunshine duration h 2000-2020 1 km RESDC (
Population density persons/km2 2020 1 km WorldPop (
LULC - 2000, 2010, and 2020 30 m RESDC (
DEM m / 30 m Geospatial Data Cloud (
spatial distribution data
- / 1 km RESDC (
Table 1 Detailed description of data used in the study
Slope P Change trend
<0 ≥0.05 Non-significant deceasing
>0 ≥0.05 Non-significant increasing
<0 0.01-0.05 Significant decreasing
>0 0.01-0.05 Significant increasing
<0 <0.01 Highly significant decreasing
>0 <0.01 Highly significant increasing
Table 2 Classification criteria for the change trend of LST in Xinjiang
Description Interaction mode
q(X1X2)<Min[q(X1), q(X2)] Nonlinear weakening
Min[q(X1), q(X2)]<q(X1X2)<Max[q(X1), q(X2)] Single-factor nonlinear attenuation
q(X1X2)>Max[q(X1), q(X2)] Two-factor enhancement
q(X1X2)=q(X1)+q(X2) Independence
q(X1X2)>q(X1)+q(X2) Nonlinear enhancement
Table 3 Description of interaction modes caused by the interaction between driving factors
Fig. 2 Spatial distribution of multi-year average annual LST (a), rate of change in annual average LST (b), and change trend of annual average LST (c) in Xinjiang during 2000-2020. LST, land surface temperature. Numbers of 11, 21, and 31 represent non-significant, significant, and highly significant decreasing, respectively; numbers of 12, 22, and 32 represent non-significant, significant, and highly significant increasing, respectively. Note that the figures are based on the standard map (GS(2023)2767) of the Map Service System (, and the standard map has not been modified.
Fig. 3 Temporal variation of annual average LST in Xinjiang from 2000 to 2020
Fig. 4 Distribution characteristics of multi-year average annual LST in various geomorphic zones in Xinjiang. The upper and lower horizontal lines represent the maximum LST and minimum LST, respectively; the bottom and top lines of the box represent the 25th and 75th percentile quartiles, respectively; the line and square in the middle of the box represent the average and median of LST, respectively; and the right-hand dots and trend lines represent the data points and the distributions, respectively.
Geomorphic zone Multi-year average
annual LST (℃)
Rate of change
of annual LST (℃/10a)
Proportion of warming area (%) Proportion of cooling area (%)
Xinjiang 9.45 0.24 87.20 12.80
Tarim Basin 17.17 0.32 95.90 4.10
Pakakuna Mountain Group 0.54 0.13 73.18 26.82
Tuha Basin 19.02 0.44 99.93 0.07
Altay Mountains -1.35 0.27 97.19 2.81
Tianshan Mountains 5.77 0.22 85.16 14.84
Junggar Basin 11.06 0.30 93.72 6.28
Table 4 Statistical results of the multi-year average annual LST and rate of change of annual LST, as well as the area proportions of warming area and cooling area in Xinjiang and each geomorphic zone during 2000-2020
Fig. 5 Variations in the multi-year average annual LST and DEM along (a) the line of longitude (87.30°E) and (b) the line of latitude (43.30°N). A-H represent the Pakakuna Mountain Group, Tarim Basin, Tianshan Mountains, Junggar Basin, Altay Mountains, Ili River Valley, Bogda Mountains, and Barkol Mountains, respectively.
Geomorphic zone Correlation coefficient Vertical decline rate of LST (℃/100 m)
Xinjiang -0.80 0.45
Altay Mountains -0.87 0.72
Tianshan Mountains -0.86 0.66
Pakakuna Mountain Group -0.91 0.54
Table 5 Correlation coefficients between LST and DEM in Xinjiang and three mountainous regions
Fig. 6 Spatial distribution of multi-year average seasonal LST (a, d, g, and j), rate of change in seasonal average LST (b, e, h, and k), and change trend of seasonal average LST (c, f, i, and l) in Xinjiang during 2000-2020. Numbers of 11, 21, and 31 represent non-significant, significant, and highly significant decreasing, respectively; numbers of 12, 22, and 32 represent non-significant, significant, and highly significant increasing, respectively. Note that the figures are based on the standard map (GS(2023)2767) of the Map Service System (, and the standard map has not been modified.
Geomorphic zone Rate of change in seasonal LST (℃/10a)
Spring Summer Autumn Winter
Xinjiang 0.49 0.34 -0.09 0.48
Altay Mountains 0.88 0.32 -0.42 0.88
Junggar Basin 0.85 0.32 -0.16 0.71
Tianshan Mountains 0.48 0.30 -0.05 0.45
Tuha Basin 0.67 0.38 0.14 0.44
Tarim Basin 0.49 0.64 -0.11 0.53
Pakakuna Mountain Group 0.14 0.18 0.07 0.11
Table 6 Rate of change in seasonal LST in Xinjiang and each geomorphic zone during 2000-2020
Fig. 7 Factor detection and interactive detection results (indicated by the q values) for various driving factors influencing the spatial differentiation of LST in Xinjiang. (a), factor detection; (b), interaction detection. X1-X11 represent longitude, latitude, DEM, slope, aspect, precipitation, sunshine duration, wind speed, normalized difference vegetation index (NDVI), population density, and land use and land cover (LULC), respectively.
Fig. 8 Spatial distribution of regression coefficients of dominant factors driving the spatial heterogeneity of LST. (a), DEM; (b), latitude; (c), wind speed; (d), precipitation; (e), sunshine duration; (f), NDVI. Note that the figures are based on the standard map (GS(2023)2767) of the Map Service System (, and the standard map has not been modified.
Geomorphic zone DEM Latitude Wind speed Sunshine duration Precipitation NDVI
Xinjiang -29.79 -4.71 -8.68 7.18 -7.74 -5.48
Altay Mountains -38.88 -15.07 2.37 3.89 -2.80 -6.84
Junggar Basin -35.55 -13.62 0.06 3.95 -5.92 -5.77
Tianshan Mountains -31.95 -7.75 -6.38 6.43 -5.89 -5.14
Tuha Basin -35.98 -9.98 2.60 -0.39 -16.56 -6.04
Tarim Basin -29.56 -3.07 -11.22 8.28 -5.61 -5.39
Pakakuna Mountain Group -23.05 2.95 -17.43 11.71 -9.10 5.50
Table 7 Regression coefficients of major driving factors in Xinjiang and each geomorphic zone
Fig. 9 Area transfer among different LULC types (a), identification of the heat source and sink landscape (HSI; b), and contribution index (CI) of each LULC type to LST (c) in Xinjiang during 2000-2020. In Figure 9b, each color of the bar chart corresponds to each LULC type; numbers of 1-6 represent cultivated land, forest land, grassland, water body, construction land, and unused land, respectively.
Geomorphic zone Cultivated land Forest land Grassland Water body Construction land Unused land
Xinjiang 0.17 -0.0105 0.43 -0.0429 0.27 -0.4827 0.07 -0.0272 0.35 -0.0002 1.40 3.2874
Altay Mountains 2.19 0.0761 0.27 -0.2588 1.20 0.7801 0.29 -0.0667 2.68 0.0198 0.66 -0.5347
Junggar Basin 0.08 -0.2278 0.00 -0.0015 1.13 -0.0534 0.69 -0.0011 2.84 0.0097 1.03 0.2742
Tianshan Mountains 0.94 0.1109 0.07 -0.1475 0.49 -0.9431 0.23 -0.2640 1.24 0.0181 1.88 1.2357
Tuha Basin 0.86 -0.0031 3.92 0.0002 2.95 0.0124 0.00 -0.0001 1.07 -0.0013 0.98 0.0083
Tarim Basin 0.01 -0.2255 0.03 -0.1114 0.47 -0.1933 0.02 -0.0263 0.04 -0.0074 1.12 0.5638
Pakakuna Mountain Group 3.42 0.0241 2.19 0.0025 1.11 0.0819 0.15 -0.6998 3.40 0.0023 1.00 0.5928
Table 8 Identification of the heat source and sink landscape (HSI) and contribution index (CI) of each LULC type to LST in Xinjiang and each geomorphic zone in 2020
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