{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T14:34:09Z","timestamp":1781706849070,"version":"3.54.5"},"reference-count":79,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,3,14]],"date-time":"2022-03-14T00:00:00Z","timestamp":1647216000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003392","name":"Natural Science Foundation of Fujian Province","doi-asserted-by":"publisher","award":["2021J01627"],"award-info":[{"award-number":["2021J01627"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41601562"],"award-info":[{"award-number":["41601562"]}],"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>Due to the complex coupling between phenology and climatic factors, the influence mechanism of climate, especially preseason temperature and preseason precipitation, on vegetation phenology is still unclear. In the present study, we explored the long-term trends of phenological parameters of different vegetation types in China north of 30\u00b0N from 1982 to 2014 and their comprehensive responses to preseason temperature and precipitation. Simultaneously, annual double-season phenological stages were considered. Results show that the satellite-based phenological data were corresponding with the ground-based phenological data. Our analyses confirmed that the preseason temperature has a strong controlling effect on vegetation phenology. The start date of the growing season (SOS) had a significant advanced trend for 13.5% of the study area, and the end date of the growing season (EOS) showed a significant delayed trend for 23.1% of the study area. The impact of preseason precipitation on EOS was overall stronger than that on SOS, and different vegetation types had different responses. Compared with other vegetation types, SOS and EOS of crops were greatly affected by human activities while the preseason precipitation had less impact. This study will help us to make a scientific decision to tackle global climate change and regulate ecological engineering.<\/jats:p>","DOI":"10.3390\/rs14061396","type":"journal-article","created":{"date-parts":[[2022,3,15]],"date-time":"2022-03-15T02:56:20Z","timestamp":1647312980000},"page":"1396","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":81,"title":["Long-Term Vegetation Phenology Changes and Responses to Preseason Temperature and Precipitation in Northern China"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1089-1869","authenticated-orcid":false,"given":"Rongrong","family":"Zhang","sequence":"first","affiliation":[{"name":"Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion, College of Environment & Safety Engineering, Fuzhou University, Fuzhou 350116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junyu","family":"Qi","sequence":"additional","affiliation":[{"name":"Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6724-9597","authenticated-orcid":false,"given":"Song","family":"Leng","sequence":"additional","affiliation":[{"name":"School of Life Sciences, University of Technology Sydney, Sydney 2007, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8460-6821","authenticated-orcid":false,"given":"Qianfeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion, College of Environment & Safety Engineering, Fuzhou University, Fuzhou 350116, China"},{"name":"Key Lab of Spatial Data Mining & Information Sharing, Ministry of Education of China, Fuzhou 350116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1273","DOI":"10.1007\/s00484-020-01904-1","article-title":"Self-adapting extraction of cropland phenological transitions of rotation agroecosystems using dynamically fused NDVI images","volume":"64","author":"Tang","year":"2020","journal-title":"Int. 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