{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T04:55:55Z","timestamp":1773809755741,"version":"3.50.1"},"reference-count":68,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["41907289"],"award-info":[{"award-number":["41907289"]}]},{"name":"National Natural Science Foundation of China","award":["41971275"],"award-info":[{"award-number":["41971275"]}]},{"name":"National Natural Science Foundation of China","award":["31971458"],"award-info":[{"award-number":["31971458"]}]},{"name":"National Natural Science Foundation of China","award":["2020A1515010910"],"award-info":[{"award-number":["2020A1515010910"]}]},{"name":"National Natural Science Foundation of China","award":["2020GDASYL-20200102002"],"award-info":[{"award-number":["2020GDASYL-20200102002"]}]},{"name":"National Natural Science Foundation of China","award":["2020GDASYL-20200302001"],"award-info":[{"award-number":["2020GDASYL-20200302001"]}]},{"name":"National Natural Science Foundation of China","award":["GML2019ZD0301"],"award-info":[{"award-number":["GML2019ZD0301"]}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong","doi-asserted-by":"publisher","award":["41907289"],"award-info":[{"award-number":["41907289"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong","doi-asserted-by":"publisher","award":["41971275"],"award-info":[{"award-number":["41971275"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong","doi-asserted-by":"publisher","award":["31971458"],"award-info":[{"award-number":["31971458"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong","doi-asserted-by":"publisher","award":["2020A1515010910"],"award-info":[{"award-number":["2020A1515010910"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong","doi-asserted-by":"publisher","award":["2020GDASYL-20200102002"],"award-info":[{"award-number":["2020GDASYL-20200102002"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong","doi-asserted-by":"publisher","award":["2020GDASYL-20200302001"],"award-info":[{"award-number":["2020GDASYL-20200302001"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong","doi-asserted-by":"publisher","award":["GML2019ZD0301"],"award-info":[{"award-number":["GML2019ZD0301"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"name":"\u2018GDAS\u2019 project of Science and Technology Development","award":["41907289"],"award-info":[{"award-number":["41907289"]}]},{"name":"\u2018GDAS\u2019 project of Science and Technology Development","award":["41971275"],"award-info":[{"award-number":["41971275"]}]},{"name":"\u2018GDAS\u2019 project of Science and Technology Development","award":["31971458"],"award-info":[{"award-number":["31971458"]}]},{"name":"\u2018GDAS\u2019 project of Science and Technology Development","award":["2020A1515010910"],"award-info":[{"award-number":["2020A1515010910"]}]},{"name":"\u2018GDAS\u2019 project of Science and Technology Development","award":["2020GDASYL-20200102002"],"award-info":[{"award-number":["2020GDASYL-20200102002"]}]},{"name":"\u2018GDAS\u2019 project of Science and Technology Development","award":["2020GDASYL-20200302001"],"award-info":[{"award-number":["2020GDASYL-20200302001"]}]},{"name":"\u2018GDAS\u2019 project of Science and Technology Development","award":["GML2019ZD0301"],"award-info":[{"award-number":["GML2019ZD0301"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["41907289"],"award-info":[{"award-number":["41907289"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["41971275"],"award-info":[{"award-number":["41971275"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["31971458"],"award-info":[{"award-number":["31971458"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["2020A1515010910"],"award-info":[{"award-number":["2020A1515010910"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["2020GDASYL-20200102002"],"award-info":[{"award-number":["2020GDASYL-20200102002"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["2020GDASYL-20200302001"],"award-info":[{"award-number":["2020GDASYL-20200302001"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["GML2019ZD0301"],"award-info":[{"award-number":["GML2019ZD0301"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Multiple methods have been developed to identify the transition threshold from the reconstructed satellite-derived normalized difference vegetation indices (NDVI) time series and to determine the inflection point corresponding to a certain phenology phase (e.g., the spring green-up date (GUD)). We address an issue that large uncertainties might occur in the inflection point identification of spring GUD using the traditional satellite-based methods since different vegetation types exhibit asynchronous phenological phases over a heterogeneous ecoregion. We tentatively developed a Maximum-derivative-based (MDB) method and provided inter-comparisons with two traditional methods to detect the turning points by the reconstructed time-series data of NDVI for identifying the GUD against long-term observations from the sites covered by a mixture of deciduous forest and herbages in the Pan European Phenology network. Results showed that higher annual mean temperature would advance the spring GUD, but the sensitive magnitudes differed depending on the vegetation type. Therefore, the asynchronization of phenological phases among different vegetation types would be more pronounced in the context of global warming. We found that the MDB method outperforms two other traditional methods (the 0.5-threshold-based method and the maximum-ratio-based method) in predicting the GUD of the subsequent-green-up vegetation type when compared with ground observation, especially at sites with observed GUD of herbages earlier than deciduous forest, while the Maximum-ratio-based method showed better performance for identifying GUDs of the foremost-green-up vegetation type. Although the new method improved in our study is not universally applicable on a global scale, our results, however, highlight the limitation of current inflection point identify algorithms in predicting the GUD derived from satellite-based vegetation indices datasets in an ecoregion with heterogeneous vegetation types and asynchronous phenological phases, which makes it helpful for us to better predict plant phenology on an ecoregion-scale under future ongoing climate warming.<\/jats:p>","DOI":"10.3390\/rs14174349","type":"journal-article","created":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T00:19:01Z","timestamp":1662077941000},"page":"4349","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Identification of the Spring Green-Up Date Derived from Satellite-Based Vegetation Index over a Heterogeneous Ecoregion"],"prefix":"10.3390","volume":"14","author":[{"given":"Jianping","family":"Wu","sequence":"first","affiliation":[{"name":"Guangdong Provincial Key Lab of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China"}]},{"given":"Zhongbing","family":"Chang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Tropical and Subtropical Natural Resources in South China, Surveying and Mapping Institute Lands and Resource Department of Guangdong Province, Guangzhou 510663, China"}]},{"given":"Yongxian","family":"Su","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Lab of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China"}]},{"given":"Chaoqun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Lab of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}]},{"given":"Xiong","family":"Wu","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Lab of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}]},{"given":"Chongyuan","family":"Bi","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Lab of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"},{"name":"Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3663-7981","authenticated-orcid":false,"given":"Liyang","family":"Liu","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Lab of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}]},{"given":"Xueqin","family":"Yang","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Lab of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}]},{"given":"Xueyan","family":"Li","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Lab of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1111\/j.1365-2486.2006.01220.x","article-title":"Climate controls on the carbon and water balances of a boreal aspen forest, 1994\u20132003","volume":"13","author":"Barr","year":"2007","journal-title":"Glob. Chang. Biol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1805","DOI":"10.1016\/j.rse.2010.04.005","article-title":"Land surface phenology from MODIS: Characterization of the Collection 5 global land cover dynamics product","volume":"114","author":"Ganguly","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.agrformet.2015.10.015","article-title":"Land surface phenology of China\u2019s temperate ecosystems over 1999\u20132013: Spatial-temporal patterns, interaction effects, covariation with climate and implications for productivity","volume":"216","author":"Wu","year":"2016","journal-title":"Agric. Forest Meteorol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1007\/s12524-019-00976-w","article-title":"Understanding Spatio-temporal Pattern of Grassland Phenology in the western Indian Himalayan State","volume":"47","author":"Rajan","year":"2019","journal-title":"J. Indian Soc. Remote"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"17638","DOI":"10.1038\/s41598-020-74563-2","article-title":"Improved NDVI based proxy leaf-fall indicator to assess rainfall sensitivity of deciduousness in the central Indian forests through remote sensing","volume":"10","author":"Singh","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.isprsjprs.2017.05.015","article-title":"Spring green-up date derived from GIMMS3g and SPOT-VGT NDVI of winter wheat cropland in the North China Plain","volume":"130","author":"Liu","year":"2017","journal-title":"ISPRS J. Photogram. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.agrformet.2012.09.012","article-title":"Climate change, phenology, and phenological control of vegetation feedbacks to the climate system","volume":"169","author":"Richardson","year":"2013","journal-title":"Agric. Forest Meteorol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"155154","DOI":"10.1016\/j.scitotenv.2022.155154","article-title":"Urban warming increases the temperature sensitivity of spring vegetation phenology at 292 cities across China","volume":"834","author":"Wang","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"6911","DOI":"10.1038\/ncomms7911","article-title":"Leaf onset in the northern hemisphere triggered by daytime temperature","volume":"6","author":"Piao","year":"2015","journal-title":"Nat. Commum."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3228","DOI":"10.1111\/j.1365-2486.2011.02419.x","article-title":"Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006","volume":"17","author":"Piao","year":"2011","journal-title":"Glob. Chang. Biol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3167","DOI":"10.1111\/gcb.12283","article-title":"Large-scale variations in the vegetation growing season and annual cycle of atmospheric CO2","volume":"19","author":"Barichivich","year":"2013","journal-title":"Glob. Chang. Biol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1038\/nature06444","article-title":"Net carbon dioxide losses of northern ecosystems in response to autumn warming","volume":"451","author":"Piao","year":"2008","journal-title":"Nature"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1038\/nclimate2253","article-title":"Net carbon uptake has increased through warming-induced changes in temperate forest phenology","volume":"4","author":"Keenan","year":"2014","journal-title":"Nat. Clim. Chang."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1038\/nclimate3299","article-title":"Climate mitigation from vegetation biophysical feedbacks during the past three decades","volume":"7","author":"Zeng","year":"2017","journal-title":"Nat. Clim. Chang."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.isprsjprs.2021.02.021","article-title":"Regional evaluation of satellite-based methods for identifying leaf unfolding date","volume":"175","author":"Shen","year":"2021","journal-title":"ISPRS J. Photogram. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"672","DOI":"10.1111\/j.1365-2486.2006.01123.x","article-title":"Variations in satellite-derived phenology in China\u2019s temperate vegetation","volume":"12","author":"Piao","year":"2006","journal-title":"Glob. Chang. Biol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1922","DOI":"10.1111\/gcb.14619","article-title":"Plant phenology and global climate change: Current progresses and challenges","volume":"25","author":"Piao","year":"2019","journal-title":"Glob. Chang. Biol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"703","DOI":"10.2307\/3235884","article-title":"Measuring phenological variability from satellite imagery","volume":"5","author":"Reed","year":"1994","journal-title":"J. Veg. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.agrformet.2016.11.193","article-title":"Land surface phenology derived from normalized difference vegetation index (NDVI) at global FLUXNET sites","volume":"233","author":"Wu","year":"2017","journal-title":"Agric. For. Meteorol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.isprsjprs.2019.07.011","article-title":"Evaluation of the MODIS collections 5 and 6 for change analysis of vegetation and land surface temperature dynamics in North and South America","volume":"156","author":"Heck","year":"2019","journal-title":"ISPRS J. Photogram. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2335","DOI":"10.1111\/j.1365-2486.2009.01910.x","article-title":"Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982\u20132006","volume":"15","author":"White","year":"2009","journal-title":"Glob. Chang. Biol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"054006","DOI":"10.1088\/1748-9326\/9\/5\/054006","article-title":"A tale of two springs: Using recent climate anomalies to characterize the sensitivity of temperate forest phenology to climate change","volume":"9","author":"Friedl","year":"2014","journal-title":"Environ. Res. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.ecolind.2017.02.024","article-title":"Spring green-up phenology products derived from MODIS NDVI and EVI: Intercomparison, interpretation and validation using National Phenology Network and AmeriFlux observations","volume":"77","author":"Peng","year":"2017","journal-title":"Ecol. Indic."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.rse.2004.03.014","article-title":"A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter","volume":"91","author":"Chen","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.agrformet.2012.06.009","article-title":"Spring vegetation green-up date in China inferred from SPOT NDVI data: A multiple model analysis","volume":"165","author":"Cong","year":"2012","journal-title":"Agric. For. Meteorol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.isprsjprs.2019.01.017","article-title":"A new algorithm for the estimation of leaf unfolding date using MODIS data over China\u2019s terrestrial ecosystems","volume":"149","author":"Wang","year":"2019","journal-title":"ISPRS J. Photogram. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.rse.2018.08.022","article-title":"A simple method to improve the quality of NDVI time-series data by integrating spatiotemporal information with the Savitzky-Golay filter","volume":"217","author":"Cao","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"8664","DOI":"10.1002\/ece3.5408","article-title":"Discrepancies in vegetation phenology trends and shift patterns in different climatic zones in middle and eastern Eurasia between 1982 and 2015","volume":"9","author":"Li","year":"2019","journal-title":"Ecol. Evol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.agrformet.2014.09.009","article-title":"An improved logistic method for detecting spring vegetation phenology in grasslands from MODIS EVI time-series data","volume":"200","author":"Cao","year":"2015","journal-title":"Agric. Forest Meteorol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"22151","DOI":"10.1073\/pnas.1012490107","article-title":"Winter and spring warming result in delayed spring phenology on the Tibetan Plateau","volume":"107","author":"Yu","year":"2010","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2269","DOI":"10.1080\/01431169008955174","article-title":"A phenological classification of terrestrial vegetation cover using shortwave vegetation index imagery","volume":"11","author":"Lloyd","year":"1990","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1007\/s00484-003-0164-4","article-title":"West\u2013east contrast of phenology and climate in northern Asia revealed using a remotely sensed vegetation index","volume":"47","author":"Suzuki","year":"2003","journal-title":"Int. J. Biometeorol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1007\/s00376-017-6296-y","article-title":"Changing spring phenology dates in the Three-Rivers Headwater Region of the Tibetan Plateau during 1960\u20132013","volume":"35","author":"Yu","year":"2018","journal-title":"Adv. Atmos. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1038\/nclimate2533","article-title":"Three decades of multi-dimensional change in global leaf phenology","volume":"5","author":"Buitenwerf","year":"2015","journal-title":"Nat. Clim. Chang."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.agrformet.2014.01.003","article-title":"Increasing altitudinal gradient of spring vegetation phenology during the last decade on the Qinghai-Tibetan Plateau","volume":"189","author":"Shen","year":"2014","journal-title":"Agric. For. Meteorol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1029\/97GB00330","article-title":"A continental phenology model for monitoring vegetation responses to interannual climatic variability","volume":"11","author":"White","year":"1997","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1016\/j.rse.2018.04.030","article-title":"The mixed pixel effect in land surface phenology: A simulation study","volume":"211","author":"Chen","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Liu, L., Cao, R., Shen, M., Chen, J., Wang, J., and Zhang, X. (2019). How dose scale effect influence spring vegetation phenology estimated from satellite-derived vegetation indexes?. Remote Sens., 11.","DOI":"10.3390\/rs11182137"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1111\/j.1469-8137.2004.01059.x","article-title":"Responses of spring phenology to climate change","volume":"162","author":"Badeck","year":"2004","journal-title":"New Phytol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1038\/nature11056","article-title":"Extended leaf phenology and the autumn niche in deciduous forest invasions","volume":"485","author":"Fridley","year":"2012","journal-title":"Nature"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1111\/j.1365-2435.2005.01027.x","article-title":"Light gains and physiological capacity of understory woody plants during phenological avoidance of canopy shade","volume":"19","author":"Augspurger","year":"2005","journal-title":"Funct. Ecol."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Noormets, A. (2009). Phenological differences between understory and overstory: A case study using the long-term Harvard Forest records. Phenology of Ecosystem Processes, Springer.","DOI":"10.1007\/978-1-4419-0026-5"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2753","DOI":"10.5194\/essd-13-2753-2021","article-title":"GLC_FCS30: Global land-cover product with fine classification system at 30 m using time-series Landsat imagery","volume":"13","author":"Zhang","year":"2021","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4014","DOI":"10.1109\/TGRS.2008.2000798","article-title":"NOAA-AVHRR orbital drift correction from solar zenithal angle data","volume":"46","author":"Sobrino","year":"2008","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.ecolind.2018.01.042","article-title":"Improved modeling of gross primary productivity (GPP) by better representation of plant phenological indicators from remote sensing using a process model","volume":"88","author":"Wang","year":"2018","journal-title":"Ecol. Ind."},{"key":"ref_46","unstructured":"Viovy, N. (2018). CRUNCEP Version 7-Atmospheric Forcing Data for the Community Land Model, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1007\/s00484-014-0839-z","article-title":"Determining the relative importance of climatic drivers on spring phenology in grassland ecosystems of semi-arid areas","volume":"59","author":"Zhu","year":"2014","journal-title":"Int. J. Biometeorol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"926","DOI":"10.1111\/j.1469-8137.2011.03803.x","article-title":"Leaf-out phenology of temperate woody plants: From trees to ecosystems","volume":"191","author":"Polgar","year":"2011","journal-title":"New Phytol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3227","DOI":"10.1098\/rstb.2010.0102","article-title":"Influence of spring and autumn phenological transitions on forest ecosystem productivity","volume":"365","author":"Richardson","year":"2010","journal-title":"Phil. Trans. R. Soc. B."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1890\/070217","article-title":"Tracking the rhythm of the seasons in the face of global change: Phenological research in the 21st century","volume":"7","author":"Morisette","year":"2009","journal-title":"Front. Ecol. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.rse.2012.04.001","article-title":"Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology","volume":"123","author":"Atkinson","year":"2012","journal-title":"Remote Sen. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1781","DOI":"10.1002\/joc.823","article-title":"Relationships among phenological growing season, time-integrated normalized difference vegetation index and climate forcing in the temperate region of eastern China","volume":"22","author":"Chen","year":"2002","journal-title":"Int. J. Climatol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1111\/j.1365-2486.2006.01311.x","article-title":"Phenology model from surface meteorology does not capture satellite-based greenup estimations","volume":"13","author":"Fisher","year":"2007","journal-title":"Global Chang. Biol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.rse.2007.01.004","article-title":"Cross-scalar satellite phenology from ground, Landsat, and MODIS data","volume":"109","author":"Fisher","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"eaax1396","DOI":"10.1126\/sciadv.aax1396","article-title":"Increased atmospheric vapor pressure deficit reduces global vegetation growth","volume":"5","author":"Yuan","year":"2019","journal-title":"Sci. Adv."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.rse.2013.11.020","article-title":"Remotely sensed trends in the phenology of northern high latitude terrestrial vegetation, controlling for land cover change and vegetation type","volume":"143","author":"Jeganathan","year":"2014","journal-title":"Remote Sen. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1126\/science.329.5989.277-e","article-title":"Warming, photoperiods, and tree phenology","volume":"329","author":"Chuine","year":"2010","journal-title":"Science"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/j.tree.2007.04.003","article-title":"Shifting plant phenology in response to global change","volume":"22","author":"Cleland","year":"2007","journal-title":"Trends Ecol. Evol."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.rse.2016.02.020","article-title":"Latitudinal gradient of spruce forest understory and tundra phenology in Alaska as observed from satellite and ground-based data","volume":"177","author":"Kobayashi","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.rse.2016.11.021","article-title":"Application of satellite solar-induced chlorophyll fluorescence to understanding large-scale variations in vegetation phenology and function over northern high latitude forests","volume":"190","author":"Jeong","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1111\/j.1365-2486.2011.02562.x","article-title":"Terrestrial biosphere models need better representation of vegetation phenology: Results from the North American carbon program site synthesis","volume":"18","author":"Richardson","year":"2012","journal-title":"Glob. Chang. Biol."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1342","DOI":"10.1111\/gcb.13954","article-title":"Simulating the onset of spring vegetation growth across the Northern Hemisphere","volume":"24","author":"Liu","year":"2018","journal-title":"Glob. Chang. Biol."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"3743","DOI":"10.1111\/gcb.12610","article-title":"Unexpected role of winter precipitation in determining heat requirement for spring vegetation green-up at northern middle and high latitudes","volume":"20","author":"Fu","year":"2014","journal-title":"Glob. Chang. Biol."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1126\/science.1173004","article-title":"Phenology feedbacks on climate change","volume":"324","author":"Rutishauser","year":"2009","journal-title":"Science"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1111\/gcb.13360","article-title":"Bud break responds more strongly to daytime than night-time temperature under asymmetric experimental warming","volume":"23","author":"Rossi","year":"2017","journal-title":"Glob. Chang. Biol."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"145039","DOI":"10.1016\/j.scitotenv.2021.145039","article-title":"Declined trend in herbaceous plant green-up dates on the Qinghai\u2013Tibetan Plateau caused by spring warming slowdown","volume":"772","author":"Sun","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1353","DOI":"10.1111\/nph.15232","article-title":"Temperature and photoperiod drive spring phenology across all species in a temperate forest community","volume":"219","author":"Flynn","year":"2018","journal-title":"New Phytol."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1073\/pnas.1717342115","article-title":"Global warming leads to more uniform spring phenology across elevations","volume":"115","author":"Vitasse","year":"2018","journal-title":"Proc. Natl. Acad. Sci. USA"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/17\/4349\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:22:06Z","timestamp":1760142126000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/17\/4349"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,1]]},"references-count":68,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["rs14174349"],"URL":"https:\/\/doi.org\/10.3390\/rs14174349","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,1]]}}}