{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T20:19:11Z","timestamp":1776111551916,"version":"3.50.1"},"reference-count":78,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,6,3]],"date-time":"2020-06-03T00:00:00Z","timestamp":1591142400000},"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":["41790422, 41771049 and 41471033"],"award-info":[{"award-number":["41790422, 41771049 and 41471033"]}],"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>In this paper, cross-spectrum analysis was used to verify the agreement of periodicity between the global LAI (leaf area index) and climate factors. The results demonstrated that the LAI of deciduous forests and permanent wetlands have high agreement with temperature, rainfall and radiation over annual cycles. A low agreement between the LAI and seasonal climate variables was observed for some of the temperate and tropical vegetation types including shrublands and evergreen broadleaf forests, possibly due to the diversity of vegetation and human activities. Across all vegetation types, the LAI demonstrated a large time lag following variation in radiation (&gt;1 month), whereas relatively short lag periods were observed between the LAI and annual temperature (around 2 weeks)\/rainfall patterns (less than 10 days), suggesting that the impact of radiation on global vegetation growth is relatively slow, which is in accord with the results of previous studies. This work can provide a benchmark of the phenological drivers in global vegetation, from the perspective of periodicity, as well as helping to parameterize and refine the DGVMs (Dynamic Global Vegetation Models) for different vegetation types.<\/jats:p>","DOI":"10.3390\/rs12111805","type":"journal-article","created":{"date-parts":[[2020,6,4]],"date-time":"2020-06-04T04:36:09Z","timestamp":1591245369000},"page":"1805","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Periodic Relations between Terrestrial Vegetation and Climate Factors across the Globe"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3972-4754","authenticated-orcid":false,"given":"Boyi","family":"Liang","sequence":"first","affiliation":[{"name":"College of Urban and Environment Sciences, Peking University, Beijing 100871, China"},{"name":"Geography, College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4RJ, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6721-4439","authenticated-orcid":false,"given":"Hongyan","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Urban and Environment Sciences, Peking University, Beijing 100871, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3012-7091","authenticated-orcid":false,"given":"Xiaoqiu","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Urban and Environment Sciences, Peking University, Beijing 100871, China"}]},{"given":"Xinrong","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Urban and Environment Sciences, Peking University, Beijing 100871, China"}]},{"given":"Elizabeth L.","family":"Cressey","sequence":"additional","affiliation":[{"name":"Geography, College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4RJ, UK"}]},{"given":"Timothy A.","family":"Quine","sequence":"additional","affiliation":[{"name":"Geography, College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4RJ, UK"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1016\/j.rse.2013.08.022","article-title":"Using satellite based soil moisture to quantify the water driven variability in NDVI: A case study over mainland Australia","volume":"140","author":"Chen","year":"2014","journal-title":"Remote Sens. 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