{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T14:55:42Z","timestamp":1770044142539,"version":"3.49.0"},"reference-count":81,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T00:00:00Z","timestamp":1660262400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42071306"],"award-info":[{"award-number":["42071306"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Variations in snow cover resulting from global warming inevitably affect alpine vegetation growth on the Tibetan Plateau (TP), but our knowledge of such influences is still limited. Here, we investigated the relationship between snow cover and alpine vegetation during 2003\u20132020 on the TP using the satellite-derived vegetation green-up date (GUD) and metrics of snow cover phenology, namely the snow cover onset date (SCOD), snow cover end date (SCED), snow cover duration (SCD), and snowmelt onset date (SMOD). In this study, we first analyzed the spatiotemporal changes in the GUD and the snow cover phenology metrics on the TP. Pearson\u2019s correlation, gray relation analysis, and linear regression were then employed to determine the impact of snow cover phenology on the GUD. Overall, with the SCOD, SCED, and SMOD delayed by one day, the GUD was advanced by 0.07 and 0.03 days and was postponed by 0.32 days, respectively, and a one-day extension of the SCD resulted in a 0.04-day advance in the GUD. In addition, the roles of vegetation type, topography, and climate factors (temperature and precipitation) in modulating the relationships between snow cover phenology and the GUD were evaluated. The GUD of alpine steppes was negatively correlated with the SCOD and SCED, contrary to that of the other vegetation types. The GUD of alpine steppes was also more sensitive to snow cover phenology than that of other vegetation types. The increase in elevation generally enhanced the sensitivity of the GUD to snow cover phenology. The GUD showed a stronger negative sensitivity to the SCD in warmer areas and a stronger positive sensitivity to the SMOD in wetter areas. Our findings revealed the essential impact of variation in snow cover phenology on the GUD and indicated the complex interference of environmental factors in the relationship between snow cover and vegetation growth.<\/jats:p>","DOI":"10.3390\/rs14163909","type":"journal-article","created":{"date-parts":[[2022,8,15]],"date-time":"2022-08-15T23:44:03Z","timestamp":1660607043000},"page":"3909","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Impact of Snow Cover Phenology on the Vegetation Green-Up Date on the Tibetan Plateau"],"prefix":"10.3390","volume":"14","author":[{"given":"Jingyi","family":"Xu","sequence":"first","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}]},{"given":"Yao","family":"Tang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}]},{"given":"Jiahui","family":"Xu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}]},{"given":"Song","family":"Shu","sequence":"additional","affiliation":[{"name":"Department of Geography and Planning, Appalachian State University, Boone, NC 28608, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5628-0003","authenticated-orcid":false,"given":"Bailang","family":"Yu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}]},{"given":"Jianping","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}]},{"given":"Yan","family":"Huang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.agrformet.2018.03.004","article-title":"Snow cover phenology affects alpine vegetation growth dynamics on the Tibetan Plateau: Satellite observed evidence, impacts of different biomes, and climate drivers","volume":"256","author":"Wang","year":"2018","journal-title":"Agric. 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