{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T20:11:34Z","timestamp":1783455094108,"version":"3.55.0"},"reference-count":80,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T00:00:00Z","timestamp":1639094400000},"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":["NO. 41771047"],"award-info":[{"award-number":["NO. 41771047"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["No. 2020YFA0608504"],"award-info":[{"award-number":["No. 2020YFA0608504"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The accurate evaluation of shifts in vegetation phenology is essential for understanding of vegetation responses to climate change. Remote-sensing vegetation index (VI) products with multi-day scales have been widely used for phenology trend estimation. VI composites should be interpolated into a daily scale for extracting phenological metrics, which may not fully capture daily vegetation growth, and how this process affects phenology trend estimation remains unclear. In this study, we chose 120 sites over four vegetation types in the mid-high latitudes of the northern hemisphere, and then a Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A4 daily surface reflectance data was used to generate a daily normalized difference vegetation index (NDVI) dataset in addition to an 8-day and a 16-day NDVI composite datasets from 2001 to 2019. Five different time interpolation methods (piecewise logistic function, asymmetric Gaussian function, polynomial curve function, linear interpolation, and spline interpolation) and three phenology extraction methods were applied to extract data from the start of the growing season and the end of the growing season. We compared the trends estimated from daily NDVI data with those from NDVI composites among (1) different interpolation methods; (2) different vegetation types; and (3) different combinations of time interpolation methods and phenology extraction methods. We also analyzed the differences between the trends estimated from the 8-day and 16-day composite datasets. Our results indicated that none of the interpolation methods had significant effects on trend estimation over all sites, but the discrepancies caused by time interpolation could not be ignored. Among vegetation types with apparent seasonal changes such as deciduous broadleaf forest, time interpolation had significant effects on phenology trend estimation but almost had no significant effects among vegetation types with weak seasonal changes such as evergreen needleleaf forests. In addition, trends that were estimated based on the same interpolation method but different extraction methods were not consistent in showing significant (insignificant) differences, implying that the selection of extraction methods also affected trend estimation. Compared with other vegetation types, there were generally fewer discrepancies between trends estimated from the 8-day and 16-day dataset in evergreen needleleaf forest and open shrubland, which indicated that the dataset with a lower temporal resolution (16-day) can be applied. These findings could be conducive for analyzing the uncertainties of monitoring vegetation phenology changes.<\/jats:p>","DOI":"10.3390\/rs13245018","type":"journal-article","created":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T08:17:58Z","timestamp":1639124278000},"page":"5018","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Assessing the Effects of Time Interpolation of NDVI Composites on Phenology Trend Estimation"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4070-5235","authenticated-orcid":false,"given":"Xueying","family":"Li","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Department of Physical Geography and Ecosystem Science, Lund University, 22362 Lund, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3011-444X","authenticated-orcid":false,"given":"Wenquan","family":"Zhu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiying","family":"Xie","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pei","family":"Zhan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lixin","family":"Sun","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4411-8196","authenticated-orcid":false,"given":"Zheng","family":"Duan","sequence":"additional","affiliation":[{"name":"Department of Physical Geography and Ecosystem Science, Lund University, 22362 Lund, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,10]]},"reference":[{"key":"ref_1","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. Cycle"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1174","DOI":"10.1111\/j.1365-2486.2006.01164.x","article-title":"Phenology of a northern hardwood forest canopy","volume":"12","author":"Richardson","year":"2006","journal-title":"Glob. Chang. Biol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1255","DOI":"10.1111\/geb.12210","article-title":"Recent spring phenology shifts in western Central Europe based on multiscale observations","volume":"23","author":"Fu","year":"2014","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_4","first-page":"1","article-title":"A comprehensive framework for seasonal controls of leaf abscission and productivity in evergreen broadleaved tropical and subtropical forests","volume":"2","author":"Yang","year":"2021","journal-title":"Innovation"},{"key":"ref_5","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_6","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_7","doi-asserted-by":"crossref","first-page":"886","DOI":"10.1111\/j.1365-2486.2010.02281.x","article-title":"Evidence of increased net ecosystem productivity associated with a longer vegetated season in a deciduous forest in south-central Indiana, USA","volume":"17","author":"Dragoni","year":"2011","journal-title":"Glob. Chang. Biol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1016\/j.ecolind.2019.05.004","article-title":"Effects of data temporal resolution on phenology extractions from the alpine grasslands of the Tibetan Plateau","volume":"104","author":"Zhu","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_9","first-page":"68","article-title":"Parameterization of Leaf Phenology for the Terrestrial Ecosystem Models","volume":"25","author":"Gu","year":"2006","journal-title":"Prog. Geogr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1038\/416389a","article-title":"Ecological responses to recent climate change","volume":"416","author":"Walther","year":"2002","journal-title":"Nature"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1271","DOI":"10.1080\/01431168508948281","article-title":"Analysis of the Phenology of Global Vegetation Using Meteorological Satellite Data","volume":"6","author":"Justice","year":"1985","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1038\/386698a0","article-title":"Increased plant growth in the northern high latitudes from 1981 to 1991","volume":"386","author":"Myneni","year":"1997","journal-title":"Nature"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2004GL021961","article-title":"A global framework for monitoring phenological responses to climate change","volume":"32","author":"White","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2006JG000217","article-title":"Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): Evaluation of global patterns and comparison with in situ measurements","volume":"111","author":"Zhang","year":"2006","journal-title":"J. Geophys. Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1111\/j.1466-8238.2011.00675.x","article-title":"Extension of the growing season due to delayed autumn over mid and high latitudes in North America during 1982\u20132006","volume":"21","author":"Zhu","year":"2012","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1111\/gcb.12778","article-title":"Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010","volume":"21","author":"Yang","year":"2015","journal-title":"Glob. Chang. Biol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.rse.2018.06.047","article-title":"Generation and evaluation of the VIIRS land surface phenology product","volume":"216","author":"Zhang","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"112133","DOI":"10.1016\/j.rse.2020.112133","article-title":"Investigation of land surface phenology detections in shrublands using multiple scale satellite data","volume":"252","author":"Peng","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_19","first-page":"102487","article-title":"Development of a global annual land surface phenology dataset for 1982\u20132018 from the AVHRR data by implementing multiple phenology retrieving methods","volume":"103","author":"Wu","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_20","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_21","doi-asserted-by":"crossref","first-page":"2008","DOI":"10.1016\/j.rse.2011.04.003","article-title":"Characterizing vegetation cover in global savannas with an annual foliage clumping index derived from the MODIS BRDF product","volume":"115","author":"Hill","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1007\/s12665-012-2146-5","article-title":"Topographic controls on vegetation index in a hilly landscape: A case study in the Jiaodong Peninsula, eastern China","volume":"70","author":"Wang","year":"2013","journal-title":"Environ. Earth Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.rse.2012.03.012","article-title":"Ground-based Network of NDVI measurements for tracking temporal dynamics of canopy structure and vegetation phenology in different biomes","volume":"123","author":"Soudani","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"6024","DOI":"10.1080\/01431161.2013.793861","article-title":"Contemporary and historical classification of crop types in Arizona","volume":"34","author":"Hartfield","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.rse.2013.01.010","article-title":"Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements","volume":"132","author":"Hmimina","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.agrformet.2016.12.006","article-title":"Onset of drying and dormancy in relation to water dynamics of semi-arid grasslands from MODIS NDWI","volume":"234","author":"Ding","year":"2017","journal-title":"Agric. For. Meteorol."},{"key":"ref_27","first-page":"132","article-title":"MODIS-derived EVI, NDVI and WDRVI time series to estimate phenological metrics in French deciduous forests","volume":"64","author":"Testa","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"144011","DOI":"10.1016\/j.scitotenv.2020.144011","article-title":"The confounding effect of snow cover on assessing spring phenology from space: A new look at trends on the Tibetan Plateau","volume":"756","author":"Huang","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_29","first-page":"304","article-title":"Review of influencing factors of accuracy of plant phenology monitoring based on remote sensing data","volume":"35","author":"Fan","year":"2016","journal-title":"Prog. Geogr."},{"key":"ref_30","first-page":"1787","article-title":"Evaluation of the consistency of long-term NDVI time series derived from AVHRR, SPOT-Vegetation, SeaWiFS, MODIS, and Landsat ETM+ sensors","volume":"44","author":"Brown","year":"2006","journal-title":"IEEE Trans. Geosci. Electron."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1741","DOI":"10.1016\/j.agrformet.2011.07.008","article-title":"A comparison of multiple phenology data sources for estimating seasonal transitions in deciduous forest carbon exchange","volume":"151","author":"Garrity","year":"2011","journal-title":"Agric. For. Meteorol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4309","DOI":"10.1073\/pnas.1210423110","article-title":"Green-up dates in the Tibetan Plateau have continuously advanced from 1982 to 2011","volume":"110","author":"Zhang","year":"2013","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_33","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_34","doi-asserted-by":"crossref","first-page":"8129","DOI":"10.1080\/01431161.2018.1482021","article-title":"Autumn leaf phenology: Discrepancies between in situ observations and satellite data at urban and rural sites","volume":"39","author":"Donnelly","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"7821","DOI":"10.1080\/01431161.2021.1969056","article-title":"Comparing in situ spring phenology and satellite-derived start of season at rural and urban sites in Ireland","volume":"42","author":"Donnelly","year":"2021","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.agrformet.2017.04.009","article-title":"Intercomparison and evaluation of spring phenology products using National Phenology Network and AmeriFlux observations in the contiguous United States","volume":"242","author":"Peng","year":"2017","journal-title":"Agric. For. Meteorol."},{"key":"ref_37","first-page":"035036","article-title":"Shifts in Arctic phenology in response to climate and anthropogenic factors as detected from multiple satellite time series","volume":"8","author":"Zeng","year":"2013","journal-title":"Environ. Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"045508","DOI":"10.1088\/1748-9326\/6\/4\/045508","article-title":"Recent changes in phenology over the northern high latitudes detected from multi-satellite data","volume":"6","author":"Zeng","year":"2011","journal-title":"Res. Lett."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"e03518","DOI":"10.1002\/ecy.3518","article-title":"Satellite-derived NDVI underestimates the advancement of alpine vegetation growth over the past three decades","volume":"102","author":"Wang","year":"2021","journal-title":"Ecology"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Hudson, I., and Keatley, M. (2010). Spatio-temporal statistical methods for modeling land surface phenology. Phenological Research, Springer.","DOI":"10.1007\/978-90-481-3335-2"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.rse.2014.03.017","article-title":"Remote sensing of spring phenology in northeastern forests: A comparison of methods, field metrics and sources of uncertainty","volume":"148","author":"White","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_42","first-page":"744","article-title":"Spatial variations in responses of vegetation autumn phenology to climate change on the Tibetan Plateau","volume":"10","author":"Cong","year":"2017","journal-title":"J. Plant Ecol."},{"key":"ref_43","first-page":"88","article-title":"Regional evaluation of satellite-based methods for identifying end of vegetation growing season","volume":"175","author":"Shen","year":"2021","journal-title":"Remote Sens. Ecol. Conserv."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1080\/01431168608948945","article-title":"Characteristics of Maximum-Value Composite Images from Temporal Avhrr Data","volume":"7","author":"Holben","year":"1986","journal-title":"Int. J. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1080\/01431169208904212","article-title":"The best index slope extraction (BISE)-a method for reducing noise in NDVI yime-series","volume":"13","author":"Viovy","year":"1992","journal-title":"Int. J. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2365","DOI":"10.1080\/014311697217657","article-title":"Maximum value interpolated (MVI): A maximum value composite method improvement in vegetation index profiles analysis","volume":"18","author":"Taddei","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"835","DOI":"10.1016\/j.asr.2005.08.037","article-title":"Reconstructing pathfinder AVHRR land NDVI time-series data for the Northwest of China","volume":"37","author":"Ma","year":"2006","journal-title":"Adv. Space Res."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1016\/j.rse.2009.11.001","article-title":"Comparison of cloud-reconstruction methods for time series of composite NDVI data","volume":"114","author":"Julien","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Fan, X.W., Liu, Y.B., Wu, G.P., and Zhao, X.S. (2020). Compositing the minimum NDVI for daily water surface mapping. Remote Sens., 12.","DOI":"10.3390\/rs12040700"},{"key":"ref_50","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_51","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1111\/gcb.13081","article-title":"Temperature, precipitation, and insolation effects on autumn vegetation phenology in temperate China","volume":"22","author":"Liu","year":"2016","journal-title":"Glob. Chang. Biol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"2385","DOI":"10.1111\/j.1365-2486.2011.02397.x","article-title":"Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982\u20132008","volume":"17","author":"Jeong","year":"2011","journal-title":"Glob. Chang. Biol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.rse.2010.08.013","article-title":"Validating satellite phenology through intensive ground observation and landscape scaling in a mixed seasonal forest","volume":"115","author":"Liang","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1109\/5.993400","article-title":"A chronology of interpolation: From ancient astronomy to modern signal and image processing","volume":"90","author":"Meijering","year":"2002","journal-title":"Proc. IEEE"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Wolberg, G., and Alfy, I. (1999). Monotonic cubic spline interpolation. Comput. Graph. Int., 188\u2013195.","DOI":"10.1109\/CGI.1999.777953"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1824","DOI":"10.1109\/TGRS.2002.802519","article-title":"Seasonality extraction by function fitting to time-series of satellite sensor data","volume":"40","author":"Eklundh","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sensing."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.rse.2005.10.021","article-title":"Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI","volume":"100","author":"Beck","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_58","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_59","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_60","doi-asserted-by":"crossref","first-page":"1564","DOI":"10.1016\/j.rse.2011.02.015","article-title":"The effect of the temporal resolution of NDVI data on season onset dates and trends across Canadian broadleaf forests","volume":"115","author":"Kross","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1046\/j.1365-2486.2003.00507.x","article-title":"Northern hemisphere photosynthetic trends 1982-99","volume":"9","author":"Slayback","year":"2003","journal-title":"Glob. Chang. Biol."},{"key":"ref_62","first-page":"4305","article-title":"Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery","volume":"11","author":"Klosterman","year":"2014","journal-title":"Biogeoences."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2002JD002510","article-title":"Relation between interannual variations in satellite measures of northern forest greenness and climate between 1982 and 1999","volume":"108","author":"Zhou","year":"2003","journal-title":"J. Geophys. Res."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1007\/s11434-012-5407-5","article-title":"Spatiotemporal variation in alpine grassland phenology in the Qinghai-Tibetan Plateau from 1999 to 2009","volume":"58","author":"Ding","year":"2013","journal-title":"Chin. Sci. Bull."},{"key":"ref_65","first-page":"198","article-title":"Biological and climate factors co-regulated spatial-temporal dynamics of vegetation autumn phenology on the Tibetan Plateau","volume":"69","author":"Zu","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"144","DOI":"10.4097\/kjae.2017.70.2.144","article-title":"Central limit theorem: The cornerstone of modern statistics","volume":"70","author":"Kwak","year":"2017","journal-title":"Korean J. Anesthesiol."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.rse.2006.08.002","article-title":"A curve fitting procedure to derive inter-annual phenologies from time series of noisy satellite NDVI data","volume":"106","author":"Bradley","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1021\/ac60214a047","article-title":"Smoothing and differentiation of data by simplified least squares procedures","volume":"36","author":"Savitzky","year":"1964","journal-title":"Anal. Chem."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.rse.2008.09.003","article-title":"Noise reduction of NDVI time series: An empirical comparison of selected techniques","volume":"113","author":"Hird","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.isprsjprs.2021.08.015","article-title":"A practical approach to reconstruct high-quality Landsat NDVI time-series data by gap filling and the Savitzky-Golay filter","volume":"180","author":"Chen","year":"2021","journal-title":"ISPRS-J. Photogramm. Remote Sens."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1016\/S0034-4257(02)00135-9","article-title":"Monitoring vegetation phenology using MODIS","volume":"84","author":"Zhang","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1016\/j.rse.2006.11.025","article-title":"AVHRR derived phenological change in the Sahel and Soudan, Africa, 1982\u20132005","volume":"108","author":"Heumann","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_73","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_74","doi-asserted-by":"crossref","first-page":"973","DOI":"10.1093\/treephys\/22.14.973","article-title":"Evaluation of methods for the combination of phenological time series and outlier detection","volume":"22","author":"Schaber","year":"2002","journal-title":"Tree Physiol."},{"key":"ref_75","first-page":"1589","article-title":"Evaluation of the accuracy of phenology extraction methods for natural vegetation based on remote sensing","volume":"38","author":"Zhang","year":"2019","journal-title":"Chin. J. Ecol."},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Li, N., Zhan, P., Pan, Y.Z., Zhu, X.F., Li, M.Y., and Zhang, D.J. (2020). Comparison of Remote Sensing Time-Series Smoothing Methods for Grassland Spring Phenology Extraction on the Qinghai-Tibetan Plateau. Remote Sens., 12.","DOI":"10.3390\/rs12203383"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"1969","DOI":"10.1111\/j.1365-2486.2006.01193.x","article-title":"European phenological response to climate change matches the warming pattern","volume":"12","author":"Menzel","year":"2006","journal-title":"Glob. Chang. Biol."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"886","DOI":"10.1126\/science.1171542","article-title":"Seasons and Life Cycles","volume":"324","author":"Steltzer","year":"2009","journal-title":"Science"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"763","DOI":"10.1007\/s00484-019-01690-5","article-title":"New satellite-based estimates show significant trends in spring phenology and complex sensitivities to temperature and precipitation at northern European latitudes","volume":"63","author":"Jin","year":"2019","journal-title":"Int. J. Biometeorol."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"5446","DOI":"10.1080\/01431161.2017.1339925","article-title":"Satellite monitoring of boreal forest phenology and its climatic responses in Eurasia","volume":"38","author":"Li","year":"2017","journal-title":"Int. J. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/24\/5018\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:44:46Z","timestamp":1760168686000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/24\/5018"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,10]]},"references-count":80,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["rs13245018"],"URL":"https:\/\/doi.org\/10.3390\/rs13245018","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,10]]}}}