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influencing factors of changes in vegetation NPP and the relative roles of climate\u2013human factors on the Qinghai\u2013Tibet Plateau (QTP) differ between historical periods and are unclear. Therefore, there is an urgent need to systematically and quantitatively analyze the evolution process of the QTP\u2019s ecosystem pattern and the driving factors of this process. Based on MOD17A3H and meteorological data, the Miami model, correlation analysis, and the residual coefficient method were used to investigate the spatiotemporal patterns of changes in vegetation NPP on the QTP from 2000 to 2020. We then quantitatively distinguished the relative roles of climate change and human activity in the process of vegetation NPP change during different historical periods. The results show the following: (1) From 2000 to 2020, zones with increasing vegetation NPP (10\u201330%) were the most widely distributed, and were mainly located in the Three-Rivers Headwater Region and the northern part of the Hengduan Mountains. (2) From 2000 to 2020, zones with a significant positive correlation between vegetation NPP and annual precipitation were mostly distributed in the northeastern QTP and the Three-Rivers Headwater Region, while zones with a positive correlation between vegetation NPP and annual average temperature were mostly located in southern Tibet. Zones with a significant positive correlation between NPP and annual sunshine hours were mainly distributed in the southeastern part of the QTP and the southern part of the Tanggula Mountains. In contrast, zones with a significant positive correlation between NPP and accumulated temperature (&gt;10 \u00b0C) were mainly concentrated in the northern and eastern parts of the QTP. (3) During different historical periods, the relative roles of climate\u2013human factors in the process of vegetation NPP change on the QTP had obvious spatiotemporal differences. These results could provide scientific support for the protection and restoration of regional ecosystems on the QTP.<\/jats:p>","DOI":"10.3390\/rs15092419","type":"journal-article","created":{"date-parts":[[2023,5,5]],"date-time":"2023-05-05T03:57:31Z","timestamp":1683259051000},"page":"2419","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["The Responses of Vegetation NPP Dynamics to the Influences of Climate\u2013Human Factors on Qinghai\u2013Tibet Plateau from 2000 to 2020"],"prefix":"10.3390","volume":"15","author":[{"given":"Xingming","family":"Yuan","sequence":"first","affiliation":[{"name":"School of Architecture and Information Engineering, Shandong Vocational College of Industry, Zibo 256414, China"},{"name":"School of Civil Architectural Engineering, Shandong University of Technology, Zibo 255000, China"}]},{"given":"Bing","family":"Guo","sequence":"additional","affiliation":[{"name":"School of Civil Architectural Engineering, Shandong University of Technology, Zibo 255000, China"}]},{"given":"Miao","family":"Lu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture and Rural Affairs\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1016\/j.scitotenv.2018.10.295","article-title":"Evaluating the responses of net primary productivity and carbon use efficiency of global grassland to climate variability along an aridity gradient","volume":"652","author":"Liu","year":"2019","journal-title":"Sci. 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