{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T23:43:27Z","timestamp":1775000607728,"version":"3.50.1"},"reference-count":85,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,5,29]],"date-time":"2024-05-29T00:00:00Z","timestamp":1716940800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Third Xinjiang Scientific Expedition Program","award":["2022xjkk0405"],"award-info":[{"award-number":["2022xjkk0405"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Tianshan Mountains, the largest arid mountain range in Central Asia, feature diverse terrains and significant landscape heterogeneity. The grasslands within the Xinjiang Tianshan region are particularly sensitive to climate change and human activities. However, until recently, the patterns and mechanisms underlying grassland changes in this region have been unclear. In this study, we analyzed spatial and temporal changes in grassland fractional vegetation cover (FVC) from 2001 to 2020, analyzed spatial and temporal changes in grassland, and predicted future trends using Global Land Surface Satellite (GLASS) FVC data, trend analysis, and the Hurst index method. We also explored the driving mechanisms behind these changes through the structural equation model (SEM). The results showed that from 2001 to 2020, the grassland FVC in the Tianshan region of Xinjiang was higher in the central and western regions and lower in the northern and southern regions, showing an overall fluctuating growth trend, with a change in the growth rate of 0. 0017\/a (p &lt; 0.05), and that this change was spatially heterogeneous, with the sum of significant improvement (20.6%) and slight improvement (29.9%) being much larger than the sum of significant degradation (0.6%) and slight degradation (9.5%). However, the Hurst index (H = 0.47) suggests that this trend may not continue, and there is a risk of degradation. Our study uncovers the complex interactions between the Tianshan barrier effect and grassland ecosystems, highlighting regional differences in driving mechanisms. Although the impacts of climatic conditions in grasslands vary over time in different regions, the topography and its resulting hydrothermal conditions are still dominant, and the extent of the impact is susceptible to fluctuations of varying degrees due to extreme climatic events. Additionally, the number of livestock changes significantly affects the grasslands on the southern slopes of the Tianshan Mountains, while the effects of nighttime light are minimal. By focusing on the topographical barrier effect, this study enhances our understanding of grassland vegetation dynamics in the Tianshan Mountains of Xinjiang, contributing to improved ecosystem management strategies under climate change.<\/jats:p>","DOI":"10.3390\/rs16111952","type":"journal-article","created":{"date-parts":[[2024,5,29]],"date-time":"2024-05-29T06:58:07Z","timestamp":1716965887000},"page":"1952","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Analyzing Spatiotemporal Variations and Driving Factors of Grassland in the Arid Region of Northwest China Surrounding the Tianshan Mountains"],"prefix":"10.3390","volume":"16","author":[{"given":"Yutong","family":"Fang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0155-6735","authenticated-orcid":false,"given":"Xiang","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6701-3864","authenticated-orcid":false,"given":"Naijing","family":"Liu","sequence":"additional","affiliation":[{"name":"POWERCHINA Northwest Engineering Corporation Limited, Xi\u2019an 710065, China"}]},{"given":"Wenjie","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Wenxi","family":"Shi","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"858","DOI":"10.1038\/s43017-021-00226-z","article-title":"Drivers and impacts of changes in China\u2019s drylands","volume":"2","author":"Li","year":"2021","journal-title":"Nat. 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