Study on vegetation cover change and its driving mechanism in the western section of Yili-Tianshan mountainous ecological functional reserve from 2000 to 2022

Vegetation cover serves as a crucial indicator of surface vegetation health and ecosystem stability. Using the GEE (Google Earth Engine) platform, kNDVI series data were generated from Landsat-5/8 remote sensing images for the western Yili-Tianshan mountainous region spanning 2000 to 2022. The research utilized Theil-Sen trend analysis, the Mann-Kendall significance test, the Hurst index, and a geographic detector to investigate spatial and temporal variations in vegetation cover and their driving factors over the last 2 decades. Results indicated that between 2000 and 2022, the kNDVI in the western Yili-Tianshan region initially declined before rising, with a multi-year average of 0.1452, reaching 0.1841 in 2022. The lower cover class consistently exceeded 36%, while the higher and high cover areas grew by 5.03% and 12.76%, respectively. Vegetation cover was sparse in the northern region, particularly along the southwest edge of the northern Junggar Basin, while it was dense in the southern region, especially on the north slope of the Tianshan Mountains. (2) The vegetation cover in the western part of the Yili-Tianshan mountainous region has been significantly improved, with the Yili Autonomous Prefecture in the northern part of the country being the region of greater improvement, and the trend of future changes in vegetation cover will continue to be dominated by improvement. Elevation, vegetation type, and slope are primary factors influencing kNDVI changes, each with q values exceeding 0.0944. Two-factor interactions amplify the impact of individual factors, with the interaction between elevation and mean annual temperature being the predominant interactive factor affecting vegetation cover changes in the study area.

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Publication Details

Journal
Frontiers in Environmental Science
Published
2025-11-25
DOI
https://doi.org/10.3389/fenvs.2025.1540789
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00

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article

Study on vegetation cover change and its driving mechanism in the western section of Yili-Tianshan mountainous ecological functional reserve from 2000 to 2022

Gang Sun, Jun Meng, Dong Zhang, Xiang Fei
Frontiers in Environmental Science
Remote Sensing in Agriculture
article

Study on vegetation cover change and its driving mechanism in the western section of Yili-Tianshan mountainous ecological functional reserve from 2000 to 2022

Gang Sun, Jun Meng, Dong Zhang, Xiang Fei
article en

Abstract

Vegetation cover serves as a crucial indicator of surface vegetation health and ecosystem stability. Using the GEE (Google Earth Engine) platform, kNDVI series data were generated from Landsat-5/8 remote sensing images for the western Yili-Tianshan mountainous region spanning 2000 to 2022. The research utilized Theil-Sen trend analysis, the Mann-Kendall significance test, the Hurst index, and a geographic detector to investigate spatial and temporal variations in vegetation cover and their driving factors over the last 2 decades. Results indicated that between 2000 and 2022, the kNDVI in the western Yili-Tianshan region initially declined before rising, with a multi-year average of 0.1452, reaching 0.1841 in 2022. The lower cover class consistently exceeded 36%, while the higher and high cover areas grew by 5.03% and 12.76%, respectively. Vegetation cover was sparse in the northern region, particularly along the southwest edge of the northern Junggar Basin, while it was dense in the southern region, especially on the north slope of the Tianshan Mountains. (2) The vegetation cover in the western part of the Yili-Tianshan mountainous region has been significantly improved, with the Yili Autonomous Prefecture in the northern part of the country being the region of greater improvement, and the trend of future changes in vegetation cover will continue to be dominated by improvement. Elevation, vegetation type, and slope are primary factors influencing kNDVI changes, each with q values exceeding 0.0944. Two-factor interactions amplify the impact of individual factors, with the interaction between elevation and mean annual temperature being the predominant interactive factor affecting vegetation cover changes in the study area.

Frontiers in Environmental ScienceVol. 13
Beijing Forestry University (CN), Ministry of Transport (CN), Research Institute of Highway (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 65%
Remote Sensing in Agriculture
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