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Journal of Arid Land
Journal of Arid Land  2026, Vol. 18 Issue (3): 501-523    DOI: 10.1016/j.jaridl.2026.03.008     CSTR: 32276.14.JAL.20250294
Research article     
Dynamic vegetation change response to topography based on Landsat observations in the Tianshan Mountains, China during 2000-2022
WEN Di1,2, LI Jun1,2,3,*(), XU Weifeng1,2, CHEN Zhixiang1,2, PENG Dailiang4
1College of Geography and Tourism, Chongqing Normal University, Chongqing 401331, China
2Key Laboratory of GIS Application of Chongqing, Chongqing 401331, China
3Chongqing Key Laboratory of Earth Surface Processes and Environmental Remote Sensing in Three Gorges Reservoir area, Chongqing 401331, China
4Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
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Abstract  

In the arid regions of Northwest China, vegetation cover plays a crucial role in maintaining unique terrestrial ecosystems. Vegetation growth is highly sensitive to variations in topographical factors, and the influence of topography on vegetation cover has attracted increasing attention. This study analyzed vegetation dynamics and their relationship with topography in the Tianshan Mountains of China using Landsat Normalized Difference Vegetation Index (NDVI) data during 2000-2022 and Shuttle Radar Topography Mission (SRTM)-derived topographical factors (elevation, slope, and aspect). Theil-Sen slope estimation and Mann-Kendall trend tests were applied to quantify temporal changes in vegetation, while a terrain area correction coefficient (K) was used to assess spatial associations of vegetation with topography. Random Forest (RF) regression and SHapley Additive exPlanations (SHAP) analysis evaluated the relative importance of topographical factors in shaping vegetation cover (multi-year mean NDVI) distribution. Key findings included that over the 23-a period, 59.46% of the vegetated area exhibited significant improvement (P<0.05), with the southern Tianshan Mountains showing the most pronounced increase (70.59%), whereas vegetation degradation (3.10%) was primarily concentrated in river valleys with intensive human activities. RF-SHAP analysis revealed that elevation is the primary driver of vegetation cover patterns, explaining 52.00% of the NDVI variation. The peak NDVI (0.42) occurred at elevations between 2800 and 3200 m. Slope and aspect also significantly influenced vegetation distribution, and higher NDVI values and greater improvement trends were observed on shady (north-facing) slopes compared to sunny (south-facing) slopes. K-index analysis indicated pronounced vegetation change—both degradation and improvement—in areas with elevations between 1100 and 2800 m and slopes exceeding 5°, particularly on sunny slopes. Low-elevation desert areas in the southern Tianshan Mountains were highly susceptible to degradation. This study underscores the critical role of topography in regulating vegetation cover and its spatiotemporal dynamics, providing a scientific basis for sustainable management of arid mountain ecosystems.

Key words： topography      vegetation dynamics      Normalized Difference Vegetation Index (NDVI)      Random Forest (RF)      SHapley Additive exPlanations (SHAP)      Tianshan Mountains     
Received: 28 June 2025      Published: 31 March 2026
Corresponding Authors: *LI Jun (E-mail: junli@cqnu.edu.cn)
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WEN Di
LI Jun
XU Weifeng
CHEN Zhixiang
PENG Dailiang
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WEN Di, LI Jun, XU Weifeng, CHEN Zhixiang, PENG Dailiang. Dynamic vegetation change response to topography based on Landsat observations in the Tianshan Mountains, China during 2000-2022. Journal of Arid Land, 2026, 18(3): 501-523.

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http://jal.xjegi.com/10.1016/j.jaridl.2026.03.008     OR     http://jal.xjegi.com/Y2026/V18/I3/501

Fig. 1 Vertical natural belts of Tomur Peak (a) and Bogda Peak (b) in the Tianshan Mountains, China
Fig. 2 Overview of the elevation distribution (a) and vegetation type distribution (b) in the Tianshan Mountains and three subregions. STS, CTS, and NTS represent the southern Tianshan, central Tianshan, and northern Tianshan, respectively.
Fig. 3 Spatial distribution of elevation (a), slope (b), and aspect (c) in the Tianshan Mountains and three subregions
SNDVI Z Vegetation change type SNDVI Z Vegetation change type
<0 Z≤ -2.58 Highly significant decrease >0 1.96<Z<2.58 Significant increase
<0 -2.58<Z< -1.96 Significant decrease >0 Z≥2.58 Highly significant increase
0 -1.96<Z<1.96 Nonsignificant change
Table 1 Vegetation change classification table
Fig. 4 Interannual variation of Normalized Difference Vegetation Index (NDVI) in the Tianshan Mountains and three subregions during 2000-2022. Shaded areas indicate 95% confidence intervals, while dashed lines represent time-series trend lines.
Fig. 5 Statistical significance of vegetation change trends in the Tianshan Mountains during 2000-2022
Fig. 6 Area proportion for different vegetation change types in the Tianshan Mountains and three subregions during 2000-2022
Fig. 7 Area proportion of each vegetation change type at different elevation zones in the Tianshan Mountains (a) and three subregions of STS (b), CTS (c), and NTS (d) during 2000-2022
Fig. 8 Area proportion of vegetation change types along the slope gradient in the Tianshan Mountains (a) and three subregions of STS (b), CTS (c), and NTS (d) during 2000-2022
Fig. 9 Area proportion of vegetation change types along the aspect gradient in the Tianshan Mountains (a) and three subregions of STS (b), CTS (c), and NTS (d) during 2000-2022. Ⅰ, Ⅱ, Ⅲ, Ⅳ, and Ⅴ represent flat terrain, shady slope, semi-shady slope, semi-sunny slope, and sunny slope, respectively.
Fig. 10 Variation of terrain area correction coefficient (K) with elevation depending on vegetation change types in the Tianshan Mountains (a) and three subregions of STS (b), CTS (c), and NTS (d). The dotted line indicates K=1.00.
Fig. 11 Variation of K with slope depending on vegetation change types in the Tianshan Mountains (a) and three subregions of STS (b), CTS (c), and NTS (d). The dotted line indicates K=1.00.
Fig. 12 Variation of K with aspect depending on vegetation change types in the Tianshan Mountains (a) and three subregions of STS (b), CTS (c), and NTS (d). Ⅰ, Ⅱ, Ⅲ, Ⅳ, and Ⅴ represent flat terrain, shady slope, semi-shady slope, semi-sunny slope, and sunny slope, respectively. The dotted line indicates K=1.00.
Fig. 13 Distribution of NDVI across various topographical combinations in the Tianshan Mountains (a1-f1) and three subregions of STS (a2-f2), CTS (a3-f3), and NTS (a4-f4). Ⅰ, Ⅱ, Ⅲ, Ⅳ, and Ⅴ represent flat terrain, shady slope, semi-shady slope, semi-sunny slope, and sunny slope, respectively.
Fig. 14 SHAP dependence plot for elevation (a), slope (b), aspect (c), profile curvature (d), and planar curvature (e). The aspect in Figure 14c is indicated by an angle, ranging from 0° to 360°.
Fig. 15 Important ranking of topographical factors to NDVI (a) and correlation coefficient between topographical factors and NDVI (b)
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