{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T16:48:12Z","timestamp":1770742092694,"version":"3.49.0"},"reference-count":78,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2022,7,29]],"date-time":"2022-07-29T00:00:00Z","timestamp":1659052800000},"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":["41977415"],"award-info":[{"award-number":["41977415"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["265QZ2022001"],"award-info":[{"award-number":["265QZ2022001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["41977415"],"award-info":[{"award-number":["41977415"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["265QZ2022001"],"award-info":[{"award-number":["265QZ2022001"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In high-elevation mountains, seasonal snow cover affects land surface phenology and the functioning of the ecosystem. However, studies regarding the long-term effects of snow cover on phenological changes for high mountains are still limited. Our study is based on MODIS data from 2003 to 2021. First, the NDPI was calculated, time series were reconstructed, and an SG filter was used. Land surface phenology metrics were estimated based on the dynamic thresholding method. Then, snow seasonality metrics were also estimated based on snow seasonality extraction rules. Finally, correlation and significance between snow seasonality and land surface phenology metrics were tested. Changes were analyzed across elevation and vegetation types. Results showed that (1) the asymmetry in the significant correlation between the snow seasonality and land surface phenology metrics suggests that a more snow-prone non-growing season (earlier first snow, later snowmelt, longer snow season and more snow cover days) benefits a more flourishing vegetation growing season in the following year (earlier start and later end of growing season, longer growing season). (2) Vegetation phenology metrics above 3500 m is sensitive to the length of the snow season and the number of snow cover days. The effect of first snow day on vegetation phenology shifts around 3300 m. The later snowmelt favors earlier and longer vegetation growing season regardless of the elevation. (3) The sensitivity of land surface phenology metrics to snow seasonality varied among vegetation types. Grass and shrub are sensitive to last snow day, alpine vegetation to snow season length, desert to number of snow cover days, and forest to first snow day. In this study, we used a more reliable NDPI at high elevations and confirmed the past conclusions about the impact of snow seasonality metrics. We also described in detail the curves of snow seasonal metrics effects with elevation change. This study reveals the relationship between land surface phenology and snow seasonality in the Qilian Mountains and has important implications for quantifying the impact of climate change on ecosystems.<\/jats:p>","DOI":"10.3390\/rs14153629","type":"journal-article","created":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T04:04:00Z","timestamp":1659326640000},"page":"3629","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Phenological Responses to Snow Seasonality in the Qilian Mountains Is a Function of Both Elevation and Vegetation Types"],"prefix":"10.3390","volume":"14","author":[{"given":"Yantao","family":"Liu","sequence":"first","affiliation":[{"name":"School of Land Science and Technology, China University of Geosciences Beijing, Beijing 100083, China"}]},{"given":"Wei","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Land Science and Technology, China University of Geosciences Beijing, Beijing 100083, China"},{"name":"Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, Beijing 100035, China"},{"name":"Technology Innovation Center for Ecological Restoration in Mining Areas, Ministry of Natural Resources, Beijing 100083, China"}]},{"given":"Si","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Land Science and Technology, China University of Geosciences Beijing, Beijing 100083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1499-8476","authenticated-orcid":false,"given":"Xuanlong","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4262-1772","authenticated-orcid":false,"given":"Kai","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Land Science and Technology, China University of Geosciences Beijing, Beijing 100083, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,29]]},"reference":[{"key":"ref_1","unstructured":"IPCC (2018). 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