{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T08:14:32Z","timestamp":1768464872434,"version":"3.49.0"},"reference-count":68,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"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":["42071306"],"award-info":[{"award-number":["42071306"]}],"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>The vegetation green-up date (GUD) of the Tibetan Plateau (TP) is highly sensitive to climate change. Accurate estimation of GUD is essential for understanding the dynamics and stability of terrestrial ecosystems and their interactions with climate. The GUD is usually determined from a time-series of vegetation indices (VIs). The adoption of different VIs and GUD extraction methods can lead to different GUDs. However, our knowledge of the uncertainty in these GUDs on TP is still limited. In this study, we evaluated the performance of different VIs and GUD extraction methods on TP from 2003 to 2020. The GUDs were determined from six Moderate Resolution Imaging Spectroradiometer (MODIS) derived VIs: normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), normalized difference infrared index (NDII), phenology index (PI), normalized difference phenology index (NDPI), and normalized difference greenness index (NDGI). Four extraction methods (\u03b2max, CCRmax, G20, and RCmax) were applied individually to each VI to determine GUD. The GUDs obtained from all VIs showed similar patterns of early green-up in the eastern and late green-up in the western plateau, and similar trend of GUD advancement in the eastern and postponement in the western plateau. The accuracy of the derived GUDs was evaluated by comparison with ground-observed GUDs from 19 agrometeorological stations. Our results show that two snow-free VIs, NDGI and NDPI, had better performance in GUD extraction than the snow-calibrated conventional VIs, NDVI and EVI. Among all the VIs, NDGI gave the highest GUD accuracy when combined with the four extraction methods. Based on NDGI, the GUD extracted by the CCRmax method was found to have the highest consistency (r = 0.62, p &lt; 0.01, RMSE = 11 days, bias = \u22123.84 days) with ground observations. The NDGI also showed the highest accuracy for preseason snow-covered site-years (r = 0.71, p &lt; 0.01, RMSE = 10.69 days, bias = \u22124.05 days), indicating its optimal resistance to snow cover influence. In comparison, NDII and PI hardly captured GUD. NDII was seriously affected by preseason snow cover, as indicated by the negative correlation coefficient (r = \u22120.34, p &lt; 0.1), high RMSE and bias (RMSE = 50.23 days, bias = \u221224.25 days).<\/jats:p>","DOI":"10.3390\/rs14133160","type":"journal-article","created":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T20:59:18Z","timestamp":1656968358000},"page":"3160","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Evaluation of Vegetation Indexes and Green-Up Date Extraction Methods on the Tibetan Plateau"],"prefix":"10.3390","volume":"14","author":[{"given":"Jingyi","family":"Xu","sequence":"first","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yao","family":"Tang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahui","family":"Xu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6529-712X","authenticated-orcid":false,"given":"Kaixu","family":"Bai","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Song","family":"Shu","sequence":"additional","affiliation":[{"name":"Department of Geography and Planning, Appalachian State University, Boone, NC 28608, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5628-0003","authenticated-orcid":false,"given":"Bailang","family":"Yu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianping","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Huang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"},{"name":"Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1038\/454393a","article-title":"The third pole","volume":"454","author":"Qiu","year":"2008","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.agrformet.2012.07.013","article-title":"Trends in the thermal growing season throughout the Tibetan Plateau during 1960\u20132009","volume":"166\u2013167","author":"Dong","year":"2012","journal-title":"Agric. For. Meteorol."},{"key":"ref_3","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_4","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_5","doi-asserted-by":"crossref","first-page":"1476","DOI":"10.1016\/j.agrformet.2010.08.003","article-title":"Interannual variation of evapotranspiration from forest and grassland ecosystems in Western Canada in relation to drought","volume":"150","author":"Zha","year":"2010","journal-title":"Agric. For. Meteorol."},{"key":"ref_6","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. For. Meteorol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1016\/j.tree.2005.05.011","article-title":"Using the satellite-derived NDVI to assess ecological responses to environmental change","volume":"20","author":"Pettorelli","year":"2005","journal-title":"Trends Ecol. Evol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1038\/nature11014","article-title":"Warming experiments underpredict plant phenological responses to climate change","volume":"485","author":"Wolkovich","year":"2012","journal-title":"Nature"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"5995","DOI":"10.5194\/bg-12-5995-2015","article-title":"Interpreting canopy development and physiology using a European phenology camera network at flux sites","volume":"12","author":"Wingate","year":"2015","journal-title":"Biogeosciences"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.rse.2019.01.010","article-title":"Assessing spring phenology of a temperate woodland: A multiscale comparison of ground, unmanned aerial vehicle and Landsat satellite observations","volume":"223","author":"Berra","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1111\/geb.12044","article-title":"Interannual variability of net ecosystem productivity in forests is explained by carbon flux phenology in autumn","volume":"22","author":"Wu","year":"2013","journal-title":"Global Ecol. Biogeogr."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1038\/sdata.2018.28","article-title":"Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery","volume":"5","author":"Richardson","year":"2018","journal-title":"Sci. Data"},{"key":"ref_13","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_14","doi-asserted-by":"crossref","first-page":"1027","DOI":"10.1002\/2015JD023969","article-title":"Reconciling the discrepancy in ground- and satellite-observed trends in the spring phenology of winter wheat in China from 1993 to 2008","volume":"121","author":"Guo","year":"2016","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_15","unstructured":"Freden, S.C., Mercanti, E.P., and Becker, M. (1973). Monitoring Vegetation Systems in the Great Plains with ERTS."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1109\/TGRS.1995.8746027","article-title":"A feedback based modification of the NDVI to minimize canopy background and atmospheric noise","volume":"33","author":"Liu","year":"1995","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2636","DOI":"10.3390\/s7112636","article-title":"Sensitivity of the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) to topographic effects: A case study in high-density cypress forest","volume":"7","author":"Matsushita","year":"2007","journal-title":"Sensors"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"E2329","DOI":"10.1073\/pnas.1304625110","article-title":"No evidence of continuously advanced green-up dates in the Tibetan Plateau over the last decade","volume":"110","author":"Shen","year":"2013","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.rse.2005.03.011","article-title":"Determination of phenological dates in boreal regions using normalized difference water index","volume":"97","author":"Delbart","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1029\/2012JG002070","article-title":"Land surface phenology from optical satellite measurement and CO2 eddy covariance technique","volume":"117","author":"Gonsamo","year":"2012","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3594","DOI":"10.1016\/j.rse.2008.04.016","article-title":"Fire-induced changes in green-up and leaf maturity of the Canadian boreal forest","volume":"112","author":"Peckham","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.rse.2019.03.028","article-title":"A semi-analytical snow-free vegetation index for improving estimation of plant phenology in tundra and grassland ecosystems","volume":"228","author":"Yang","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2017.04.031","article-title":"A snow-free vegetation index for improved monitoring of vegetation spring green-up date in deciduous ecosystems","volume":"196","author":"Wang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Cao, R.Y., Feng, Y., Liu, X.L., Shen, M.G., and Zhou, J. (2020). Uncertainty of vegetation green-up date estimated from vegetation indices due to snowmelt at northern middle and high latitudes. Remote Sens., 12.","DOI":"10.3390\/rs12010190"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"108019","DOI":"10.1016\/j.agrformet.2020.108019","article-title":"Comparison of MODIS-based vegetation indices and methods for winter wheat green-up date detection in Huanghuai region of China","volume":"288\u2013289","author":"Gan","year":"2020","journal-title":"Agric. For. Meteorol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.rse.2019.111511","article-title":"A review of vegetation phenological metrics extraction using time-series, multispectral satellite data","volume":"237","author":"Zeng","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_28","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_29","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_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":"361","DOI":"10.1109\/JSTARS.2010.2075916","article-title":"An enhanced TIMESAT algorithm for estimating vegetation phenology metrics from MODIS data","volume":"4","author":"Tan","year":"2011","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1080\/10106049.2012.760004","article-title":"Detecting winter wheat phenology with SPOT-VEGETATION data in the North China Plain","volume":"29","author":"Lu","year":"2014","journal-title":"Geocarto Int."},{"key":"ref_33","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":"Global Change Biol."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Zheng, Z.T., and Zhu, W.Q. (2017). Uncertainty of remote sensing data in monitoring vegetation phenology: A comparison of MODIS C5 and C6 vegetation index products on the Tibetan Plateau. Remote Sens., 9.","DOI":"10.3390\/rs9121288"},{"key":"ref_35","unstructured":"Hudson, I.L., and Keatley, M.R. (2010). Phenological Research Methods for Environmental and Climate Change Analysis Introduction and Overview, Springer."},{"key":"ref_36","unstructured":"Hudson, I.L., and Keatley, M.R. (2010). Spatio-Temporal Statistical Methods for Modelling Land Surface Phenology, Springer."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2146","DOI":"10.1016\/j.rse.2010.04.019","article-title":"A Two-Step Filtering approach for detecting maize and soybean phenology with time-series MODIS data","volume":"114","author":"Sakamoto","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_38","first-page":"188","article-title":"Mapping crop phenology using NDVI time-series derived from HJ-1 A\/B data","volume":"34","author":"Pan","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Xu, X.M., Conrad, C., and Doktor, D. (2017). Optimising phenological metrics extraction for different crop types in Germany using the Moderate Resolution Imaging Spectrometer (MODIS). Remote Sens., 9.","DOI":"10.3390\/rs9030254"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.rse.2016.03.039","article-title":"A hybrid approach for detecting corn and soybean phenology with time-series MODIS data","volume":"181","author":"Zeng","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_41","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_42","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1155\/2014\/474876","article-title":"Comparison of satellite and ground-based phenology in China\u2019s temperate monsoon area","volume":"2014","author":"Wang","year":"2014","journal-title":"Adv. Meteorol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"3592","DOI":"10.1080\/01431161.2019.1706780","article-title":"Evaluating the accuracy of and evaluating the potential errors in extracting vegetation phenology through remote sensing in China","volume":"41","author":"Zhang","year":"2020","journal-title":"Int. J. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.ecolind.2011.08.011","article-title":"Trend analysis of vegetation dynamics in Qinghai\u2013Tibet Plateau using Hurst Exponent","volume":"14","author":"Peng","year":"2012","journal-title":"Ecol. Indic."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1007\/BF02837505","article-title":"Delineation of eco-geographic regional system of China","volume":"13","author":"Wu","year":"2003","journal-title":"J. Geog. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1029\/2007GL029262","article-title":"MODIS\/Terra observed seasonal variations of snow cover over the Tibetan Plateau","volume":"34","author":"Pu","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_47","unstructured":"Vermote, E.F., Roger, J.C., and Ray, J.P. (2020, December 08). MODIS Surface Reflectance Collection 6 User\u2019s Guide, Available online: https:\/\/modis-land.gsfc.nasa.gov\/pdf\/MOD09_UserGuide_v1.4.pdf."},{"key":"ref_48","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_49","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_50","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\u2013Golay filter","volume":"91","author":"Chen","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_51","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_52","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1029\/2007GL031447","article-title":"Diverse responses of vegetation phenology to a warming climate","volume":"34","author":"Zhang","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1016\/j.rse.2017.10.001","article-title":"Improving MODIS snow products with a HMRF-based spatio-temporal modeling technique in the Upper Rio Grande Basin","volume":"204","author":"Huang","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Huang, Y., Xu, J., Xu, J., Zhao, Y., Yu, B., Liu, H., Wang, S., Xu, W., Wu, J., and Zheng, Z. (Earth Syst. Sci. Data Discuss., 2022). HMRFS-TP: Long-term daily gap-free snow cover products over the Tibetan Plateau from 2002 to 2021 based on Hidden Markov Random Field model, Earth Syst. Sci. Data Discuss., in review.","DOI":"10.5194\/essd-2022-134"},{"key":"ref_55","first-page":"77","article-title":"The influence of soil salinity, growth form, and leaf moisture on the spectral radiance of Spartina alterniflora canopies","volume":"49","author":"Hardisky","year":"1983","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1016\/j.scitotenv.2017.07.237","article-title":"Land surface phenology: What do we really \u2018see\u2019 from space?","volume":"618","author":"Helman","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2718","DOI":"10.1002\/joc.5455","article-title":"Climatology of snow phenology over the Tibetan plateau for the period 2001\u20132014 using multisource data","volume":"38","author":"Chen","year":"2018","journal-title":"Int. J. Climatol."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Guo, H., Wang, X.Y., Guo, Z.C., and Chen, S.Y. (2022). Assessing snow phenology and its environmental driving factors in Northeast China. Remote Sens., 14.","DOI":"10.3390\/rs14020262"},{"key":"ref_59","unstructured":"Raj, B., and Koerts, J. (1992). A rank-invariant method of linear and polynomial regression analysis. Henri Theil\u2019s Contributions to Economics and Econometrics: Econometric Theory and Methodology, Springer."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1080\/01621459.1968.10480934","article-title":"Estimates of the regression coefficient based on Kendall\u2019s tau","volume":"63","author":"Sen","year":"1968","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1093\/biomet\/30.1-2.81","article-title":"A new measure of rank correlation","volume":"30","author":"Kendall","year":"1938","journal-title":"Biometrika"},{"key":"ref_62","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_63","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_64","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. For. Meteorol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.rse.2017.07.020","article-title":"The relationship between threshold-based and inflexion-based approaches for extraction of land surface phenology","volume":"199","author":"Shang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_66","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_67","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.rse.2005.11.012","article-title":"Remote sensing of spring phenology in boreal regions: A free of snow-effect method using NOAA-AVHRR and SPOT-VGT data (1982\u20132004)","volume":"101","author":"Delbart","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"6159","DOI":"10.3390\/rs5126159","article-title":"Trends in spring phenology of Western European deciduous forests","volume":"5","author":"Hamunyela","year":"2013","journal-title":"Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3160\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:41:42Z","timestamp":1760139702000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3160"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,1]]},"references-count":68,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2022,7]]}},"alternative-id":["rs14133160"],"URL":"https:\/\/doi.org\/10.3390\/rs14133160","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,1]]}}}