{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T22:36:37Z","timestamp":1774478197215,"version":"3.50.1"},"reference-count":73,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2021,8,30]],"date-time":"2021-08-30T00:00:00Z","timestamp":1630281600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["2016YFC0502700"],"award-info":[{"award-number":["2016YFC0502700"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Global greening over the past 30 years since 1980s has been confirmed by numerous studies. However, a single-dimensional indicator and non-spatial modelling approaches might exacerbate uncertainties in our understanding of global change. Thus, comprehensive monitoring for vegetation\u2019s various properties and spatially explicit models are required. In this study, we used the newest enhanced vegetation index (EVI) products of Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 to detect the inconsistency trend of annual peak and average global vegetation growth using the Mann\u2013Kendall test method. We explored the climatic factors that affect vegetation growth change from 2001 to 2018 using the spatial lag model (SLM), spatial error model (SEM) and geographically weighted regression model (GWR). The results showed that EVImax and EVImean in global vegetated areas consistently showed linear increasing trends during 2001\u20132018, with the global averaged trend of 0.0022 yr\u22121 (p &lt; 0.05) and 0.0030 yr\u22121 (p &lt; 0.05). Greening mainly occurred in the croplands and forests of China, India, North America and Europe, while browning was almost in the grasslands of Brazil and Africa (18.16% vs. 3.08% and 40.73% vs. 2.45%). In addition, 32.47% of the global vegetated area experienced inconsistent trends in EVImax and EVImean. Overall, precipitation and mean temperature had positive impacts on vegetation variation, while potential evapotranspiration and vapour pressure had negative impacts. The GWR revealed that the responses of EVI to climate change were inconsistent in an arid or humid area, in cropland or grassland. Climate change could affect vegetation characteristics by changing plant phenology, consequently rendering the inconsistency between peak and mean greening. In addition, anthropogenic activities, including land cover change and land use management, also could lead to the differences between annual peak and mean vegetation variations.<\/jats:p>","DOI":"10.3390\/rs13173442","type":"journal-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T22:58:15Z","timestamp":1630450695000},"page":"3442","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Inconsistency of Global Vegetation Dynamics Driven by Climate Change: Evidences from Spatial Regression"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3586-9625","authenticated-orcid":false,"given":"Dou","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China"}]},{"given":"Xiaolei","family":"Geng","sequence":"additional","affiliation":[{"name":"Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China"}]},{"given":"Wanxu","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Geography, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8902-1817","authenticated-orcid":false,"given":"Lei","family":"Fang","sequence":"additional","affiliation":[{"name":"Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China"}]},{"given":"Rui","family":"Yao","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}]},{"given":"Xiangrong","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China"}]},{"given":"Xiao","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Public Administration, China University of Geosciences, Wuhan 430074, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/S0168-1923(02)00104-1","article-title":"Environmental controls over carbon dioxide and water vapor exchange of terrestrial vegetation","volume":"113","author":"Law","year":"2002","journal-title":"Agric. 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