A comparative analysis of the NDVIg and NDVI3g in monitoring vegetation phenology changes in the Northern Hemisphere

References

• Akin WE. 1990. Global patterns: climate, vegetation and soils. Norman: University of Oklahoma Press.
   Google Scholar
• Anyamba A, Small JL, Tucker CJ, Pak EW. 2014. Thirty-two years of Sahelian zone growing season non-stationary NDVI3g patterns and trends. Remote Sens. 6:3101–3122.10.3390/rs6043101
   Web of Science ®Google Scholar
• Baldocchi D. 2008. TURNER REVIEW No. 15. ‘Breathing’ of the terrestrial biosphere: lessons learned from a global network of carbon dioxide flux measurement systems. Aust J Bot. 56:1–26.10.1071/BT07151
   Web of Science ®Google Scholar
• Baldocchi D, Falge E, Gu L, Olson R, Hollinger D, Running S, Anthoni P, Bernhofer C, Davis K, Evans R. 2001. FLUXNET: a new tool to study the temporal and spatial variability of ecosystem – scale carbon dioxide, water vapor, and energy flux densities. Bull Am Meteorol Soc. 82:2415–2434.10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2
   Web of Science ®Google Scholar
• Baldocchi DD, Black TA, Curtis PS, Falge E, Fuentes JD, Granier A, Gu L, Knohl A, Pilegaard K, Schmid HP, et al. 2005. Predicting the onset of net carbon uptake by deciduous forests with soil temperature and climate data: a synthesis of FLUXNET data. Int J Biometeorol. 49:377–387.10.1007/s00484-005-0256-4
   PubMed Web of Science ®Google Scholar
• Beaubien E, Freeland H. 2000. Spring phenology trends in Alberta, Canada: links to ocean temperature. Int J Biometeorol. 44:53–59.10.1007/s004840000050
   PubMed Web of Science ®Google Scholar
• Bousquet P, Peylin P, Ciais P, Le Quere C, Friedlingstein P, Tans PP. 2000. Regional changes in carbon dioxide fluxes of land and oceans since 1980. Science. 290:1342–1346.10.1126/science.290.5495.1342
   PubMed Web of Science ®Google Scholar
• Brown ME, de Beurs KM. 2008. Evaluation of multi-sensor semi-arid crop season parameters based on NDVI and rainfall. Remote Sens Environ. 112:2261–2271.10.1016/j.rse.2007.10.008
   Web of Science ®Google Scholar
• Burnham KP, Anderson DR, Burnham KP, Anderson DR. 1998. Model selection and inference: a practical information-theoretic approach. New York: Springer-Verlag New York.10.1007/978-1-4757-2917-7
   Google Scholar
• Cao C, Vermote E, Xiong X. 2009. Using AVHRR lunar observations for NDVI long-term climate change detection. J Geophys Res Atmos. 114: D20105.
   Web of Science ®Google Scholar
• Chandola V, Hui D, Gu L, Bhaduri B, Vatsavai RR. 2010. Using time series segmentation for deriving vegetation phenology indices from MODIS NDVI data. In: 2010 IEEE International Conference on Data Mining Workshops (ICDMW); IEEE; Sydney. p. 202–208.
   Google Scholar
• Chapin F, Sturm M, Serreze M, McFadden J, Key J, Lloyd A, McGuire A, Rupp T, Lynch A, Schimel J. 2005. Role of land-surface changes in arctic summer warming. Science. 310:657–660.10.1126/science.1117368
   PubMed Web of Science ®Google Scholar
• Che M, Chen B, Innes JL, Wang G, Dou X, Zhou T, Zhang H, Yan J, Xu G, Zhao H. 2014. Spatial and temporal variations in the end date of the vegetation growing season throughout the Qinghai-Tibetan Plateau from 1982 to 2011. Agric For Meteorol. 189:81–90.10.1016/j.agrformet.2014.01.004
   Web of Science ®Google Scholar
• Chen B, Xu G, Coops NC, Ciais P, Innes JL, Wang G, Myneni RB, Wang T, Krzyzanowski J, Li Q, Cao L, Liu Y. 2014. Changes in vegetation photosynthetic activity trends across the Asia-Pacific region over the last three decades. Remote Sens Environ. 144:28–41.10.1016/j.rse.2013.12.018
   Web of Science ®Google Scholar
• Chen J, Jönsson P, Tamura M, Gu Z, Matsushita B, Eklundh L. 2004. A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky–Golay filter. Remote Sens Environ. 91:332–344.10.1016/j.rse.2004.03.014
   Web of Science ®Google Scholar
• Chen X, Xu L. 2012. Temperature controls on the spatial pattern of tree phenology in China’s temperate zone. Agric For Meteorol. 154:195–202.10.1016/j.agrformet.2011.11.006
   Web of Science ®Google Scholar
• Chmielewski F-M, Rötzer T. 2001. Response of tree phenology to climate change across Europe. Agric For Meteorol. 108:101–112.10.1016/S0168-1923(01)00233-7
   Web of Science ®Google Scholar
• Cleland EE, Chiariello NR, Loarie SR, Mooney HA, Field CB. 2006. Diverse responses of phenology to global changes in a grassland ecosystem. Proc Natl Acad Sci. 103:13740–13744.10.1073/pnas.0600815103
   PubMed Web of Science ®Google Scholar
• Cleland EE, Chuine I, Menzel A, Mooney HA, Schwartz MD. 2007. Shifting plant phenology in response to global change. Trends Ecol Evol. 22:357–365.10.1016/j.tree.2007.04.003
   PubMed Web of Science ®Google Scholar
• De Beurs KM, Henebry GM. 2005. Land surface phenology and temperature variation in the International geosphere–biosphere program high-latitude transects. Global Change Biol. 11:779–790.10.1111/gcb.2005.11.issue-5
   Web of Science ®Google Scholar
• Ding M, Li L, Zhang Y, Sun X, Liu L, Gao J, Wang Z, Li Y. 2015. Start of vegetation growing season on the Tibetan Plateau inferred from multiple methods based on GIMMS and SPOT NDVI data. J Geog Sci. 25:131–148.10.1007/s11442-015-1158-y
   Web of Science ®Google Scholar
• Ding M, Zhang Y, Sun X, Liu L, Wang Z, Bai W. 2013. Spatiotemporal variation in alpine grassland phenology in the Qinghai-Tibetan Plateau from 1999 to 2009. Chin Sci Bull. 58:396–405.10.1007/s11434-012-5407-5
   Google Scholar
• Fan S, Gloor M, Mahlman J, Pacala S, Sarmiento J, Takahashi T, Tans P. 1998. A large terrestrial carbon sink in North America implied by atmospheric and oceanic carbon dioxide data and models. Science. 282:442–446.10.1126/science.282.5388.442
   PubMed Web of Science ®Google Scholar
• Fensholt R, Langanke T, Rasmussen K, Reenberg A, Prince SD, Tucker C, Scholes RJ, Le QB, Bondeau A, Eastman R. 2012. Greenness in semi-arid areas across the globe 1981–2007 – an earth observing satellite based analysis of trends and drivers. Remote Sens Environ. 121:144–158.10.1016/j.rse.2012.01.017
   Web of Science ®Google Scholar
• Fensholt R, Proud SR. 2012. Evaluation of earth observation based global long term vegetation trends – comparing GIMMS and MODIS global NDVI time series. Remote Sens Environ. 119:131–147.10.1016/j.rse.2011.12.015
   Web of Science ®Google Scholar
• Fensholt R, Rasmussen K, Nielsen TT, Mbow C. 2009. Evaluation of earth observation based long term vegetation trends – intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT data. Remote Sens Environ. 113:1886–1898.10.1016/j.rse.2009.04.004
   Web of Science ®Google Scholar
• Ficetola GF, Denoel M. 2009. Ecological thresholds: an assessment of methods to identify abrupt changes in species–habitat relationships. Ecography. 32:1075–1084.10.1111/eco.2009.32.issue-6
   Web of Science ®Google Scholar
• Fu Y, Zhang H, Dong W, Yuan W. 2014. Comparison of phenology models for predicting the onset of growing season over the Northern Hemisphere. PloS One. 9: e(109544).
   Web of Science ®Google Scholar
• Fu YH, Piao S, Op de Beeck M, Cong N, Zhao H, Zhang Y, Menzel A, Janssens IA. 2014. Recent spring phenology shifts in western Central Europe based on multiscale observations. Global Ecol Biogeogr. 23:1255–1263.10.1111/geb.12210
   Google Scholar
• Garrity SR, Bohrer G, Maurer KD, Mueller KL, Vogel CS, Curtis PS. 2011. A comparison of multiple phenology data sources for estimating seasonal transitions in deciduous forest carbon exchange. Agric For Meteorol. 151:1741–1752.10.1016/j.agrformet.2011.07.008
   Web of Science ®Google Scholar
• Goodale CL, Apps MJ, Birdsey RA, Field CB, Heath LS, Houghton RA, Jenkins JC, Kohlmaier GH, Kurz W, Liu SR, et al. 2002. Forest carbon sinks in the Northern Hemisphere. Ecol Appl. 12:891–899.10.1890/1051-0761(2002)012[0891:FCSITN]2.0.CO;2
   Web of Science ®Google Scholar
• Guay KC, Beck PSA, Berner LT, Goetz SJ, Baccini A, Buermann W. 2014. Vegetation productivity patterns at high northern latitudes: a multi-sensor satellite data assessment. Global Change Biol. 20:3147–3158.10.1111/gcb.2014.20.issue-10
   PubMed Web of Science ®Google Scholar
• Heinsch FA, Zhao M, Running SW, Kimball JS, Nemani RR, Davis KJ, Bolstad PV, Cook BD, Desai AR, Ricciuto DM, et al. 2006. Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. IEEE Trans Geosci Remote Sens. 44:1908–1925.10.1109/TGRS.2005.853936
   Web of Science ®Google Scholar
• Hmimina G, Dufrêne E, Pontailler J-Y, Delpierre N, Aubinet M, Caquet B, de Grandcourt A, Burban B, Flechard C, Granier A. 2013. Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: an investigation using ground-based NDVI measurements. Remote Sens Environ. 132:145–158.10.1016/j.rse.2013.01.010
   Web of Science ®Google Scholar
• Huete A, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG. 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens Environ. 83:195–213.10.1016/S0034-4257(02)00096-2
   Web of Science ®Google Scholar
• Ivits E, Horion S, Fensholt R, Cherlet M. 2014. Drought footprint on European ecosystems between 1999 and 2010 assessed by remotely sensed vegetation phenology and productivity. Global Change Biol. 20:581–593.10.1111/gcb.2014.20.issue-2
   PubMed Web of Science ®Google Scholar
• Jeong S-J, Ho C-H, Gim H-J, Brown ME. 2011. Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008. Global Change Biol. 17:2385–2399.10.1111/j.1365-2486.2011.02397.x
   Web of Science ®Google Scholar
• Jiang N, Zhu W, Zheng Z, Chen G, Fan D. 2013. A comparative analysis between GIMSS NDVIg and NDVI3g for monitoring vegetation activity change in the northern hemisphere during 1982–2008. Remote Sens. 5:4031–4044.10.3390/rs5084031
   Web of Science ®Google Scholar
• Jonsson P, Eklundh L. 2002. Seasonality extraction by function fitting to time-series of satellite sensor data. IEEE Trans Geosci Remote Sens. 40:1824–1832.10.1109/TGRS.2002.802519
   Web of Science ®Google Scholar
• Jönsson P, Eklundh L. 2004. TIMESAT – a program for analyzing time-series of satellite sensor data. Comput Geosci. 30:833–845.10.1016/j.cageo.2004.05.006
   Web of Science ®Google Scholar
• Justice CO, Vermote E, Townshend JRG, Defries R, Roy DP, Hall DK, Salomonson VV, Privette JL, Riggs G, Strahler A, et al. 1998. The moderate resolution imaging spectroradiometer (MODIS): land remote sensing for global change research. IEEE Trans Geosci Remote Sens. 36:1228–1249.10.1109/36.701075
   Web of Science ®Google Scholar
• Landsberg H, Lippmann H, Paffen K, Troll C. 1965. Seasonal climates of the earth. Berlin: Springer.
   Google Scholar
• Lehman A. 2005. JMP for basic univariate and multivariate statistics: a step-by-step guide. Cary, NC: SAS Institute.
   Google Scholar
• Liu L, Liang L, Schwartz MD, Donnelly A, Wang Z, Schaaf CB, Liu L. 2015. Evaluating the potential of MODIS satellite data to track temporal dynamics of autumn phenology in a temperate mixed forest. Remote Sens Environ. 160:156–165.10.1016/j.rse.2015.01.011
   Web of Science ®Google Scholar
• Luo X, Chen X, Xu L, Myneni R, Zhu Z. 2013. Assessing performance of NDVI and NDVI3g in monitoring leaf unfolding dates of the deciduous broadleaf forest in Northern China. Remote Sens. 5:845–861.10.3390/rs5020845
   Web of Science ®Google Scholar
• Ma XL, Huete A, Moran S, Ponce-Campos G, Eamus D. 2015. Abrupt shifts in phenology and vegetation productivity under climate extremes. J Geophys Res Biogeosci. 120:2036–2052.10.1002/2015JG003144
   Web of Science ®Google Scholar
• Madden HH. 1978. Comments on the Savitzky-Golay convolution method for least-squares-fit smoothing and differentiation of digital data. Anal Chem. 50:1383–1386.10.1021/ac50031a048
   Web of Science ®Google Scholar
• Maignan F, Bréon FM, Bacour C, Demarty J, Poirson A. 2008. Interannual vegetation phenology estimates from global AVHRR measurements – comparison with in situ data and applications. Remote Sens Environ. 112:496–505.10.1016/j.rse.2007.05.011
   Web of Science ®Google Scholar
• McDonald KC, Kimball JS, Njoku E, Zimmermann R, Zhao M. 2004. Variability in springtime thaw in the terrestrial high latitudes: monitoring a major control on the biospheric assimilation of atmospheric CO2 with spaceborne microwave remote sensing. Earth Interact. 8:1–23.10.1175/1087-3562(2004)8<1:VISTIT>2.0.CO;2
   Web of Science ®Google Scholar
• Menzel A. 2000. Trends in phenological phases in Europe between 1951 and 1996. Int J Biometeorol. 44:76–81.10.1007/s004840000054
   PubMed Web of Science ®Google Scholar
• Menzel A. 2002. Phenology: its importance to the global change community. Clim Change. 54:379–385.10.1023/A:1016125215496
   Web of Science ®Google Scholar
• Menzel A, Sparks TH, Estrella N, Koch E, Aasa A, Ahas R, Alm-Kübler K, Bissolli P, Braslavská OG, Briede A. 2006. European phenological response to climate change matches the warming pattern. Global Change Biol. 12:1969–1976.10.1111/gcb.2006.12.issue-10
   Web of Science ®Google Scholar
• Moreno-Ruiz JA, Riano D, Garcia-Lazaro JR, Ustin SL. 2009. Intercomparison of AVHRR PAL and LTDR version 2 long-term data sets for Africa from 1982 to 2000 and its impact on mapping burned area. IEEE Geosci Remote Sens Lett. 6:738–742.10.1109/LGRS.2009.2024436
   Web of Science ®Google Scholar
• Myneni RB, Keeling C, Tucker C, Asrar G, Nemani R. 1997. Increased plant growth in the northern high latitudes from 1981 to 1991. Nature. 386:698–702.10.1038/386698a0
   Web of Science ®Google Scholar
• Niemand C, Köstner B, Prasse H, Grünwald T, Bernhofer C. 2005. Relating tree phenology with annual carbon fluxes at tharandt forest. Meteorol Z. 14:197–202.10.1127/0941-2948/2005/0022
   Web of Science ®Google Scholar
• Pedelty J, Devadiga S, Masuoka E, Brown M, Pinzon J, Tucker C, Roy D, Ju J, Vermote E, Prince S. 2007. Generating a long-term land data record from the AVHRR and MODIS instruments. In: Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International: IEEE; Barcelona. p. 1021–1025.
   Google Scholar
• Peñuelas J, Filella I. 2001. Responses to a warming world. Science. 294:793–795.10.1126/science.1066860
   PubMed Web of Science ®Google Scholar
• Phillips RC, McMillan C, Bridges KW. 1983. Phenology of eelgrass, Zostera marina L., along latitudinal gradients in North America. Aquat Bot. 15:145–156.10.1016/0304-3770(83)90025-6
   Web of Science ®Google Scholar
• Piao S, Ciais P, Friedlingstein P, Peylin P, Reichstein M, Luyssaert S, Margolis H, Fang J, Barr A, Chen A. 2008. Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature. 451:49–52.10.1038/nature06444
   PubMed Web of Science ®Google Scholar
• Piao S, Fang J, Zhou L, Ciais P, Zhu B. 2006. Variations in satellite-derived phenology in China’s temperate vegetation. Global Change Biol. 12:672–685.10.1111/gcb.2006.12.issue-4
   Web of Science ®Google Scholar
• Piao S, Fang J, Zhou L, Guo Q, Henderson M, Ji W, Li Y, Tao S. 2003. Interannual variations of monthly and seasonal normalized difference vegetation index (NDVI) in China from 1982 to 1999. J Geophys Res D Atmos. 108: 4401.
   Web of Science ®Google Scholar
• Piao S, Friedlingstein P, Ciais P, Viovy N, Demarty J. 2007. Growing season extension and its impact on terrestrial carbon cycle in the Northern Hemisphere over the past 2 decades. Global Biogeochem Cycles. 21: GB3018. doi:10.1029/2006GB002888.
   Web of Science ®Google Scholar
• Piao S, Tan J, Chen A, Fu YH, Ciais P, Liu Q, Janssens IA, Vicca S, Zeng Z, Jeong S-J. 2015. Leaf onset in the northern hemisphere triggered by daytime temperature. Nat Commun. 6: 6911.
   Web of Science ®Google Scholar
• Piao S, Wang X, Ciais P, Zhu B, Wang T, Liu J. 2011. Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006. Global Change Biol. 17:3228–3239.10.1111/gcb.2011.17.issue-10
   Web of Science ®Google Scholar
• Piao SL, Friedlingstein P, Ciais P, Zhou LM, Chen AP. 2006. Effect of climate and CO2 changes on the greening of the Northern Hemisphere over the past two decades. Geophys Res Lett. 33:L23402.
   Web of Science ®Google Scholar
• Pinzon J, Brown ME, Tucker CJ. 2005a. EMD correction of orbital drift artifacts in satellite data stream. In: Huang NE, editor. Hilbert-Huang Transform and Its Applications. Singapore: Word Scientific Publishing Co Pte Ltd; p. 241–257.10.1142/IMS
   Google Scholar
• Pinzon J, Brown ME, Tucker CJ. 2005b. Satellite time series correction of orbital drift artifacts using empirical mode decomposition. In: Shen SSP, editor. Hilbert-Huang Transform: Introduction and Applications. Singapore: Word Scientific Publishing Co Pte Ltd; p. 167–186
   Google Scholar
• Pinzon JE, Tucker CJ. 2014. A non-stationary 1981–2012 AVHRR NDVI3g time series. Remote Sens. 6:6929–6960.10.3390/rs6086929
   Web of Science ®Google Scholar
• Sarmiento JL, Gloor M, Gruber N, Beaulieu C, Jacobson AR, Fletcher SEM, Pacala S, Rodgers K. 2010. Trends and regional distributions of land and ocean carbon sinks. Biogeosciences. 7:2351–2367.10.5194/bg-7-2351-2010
   Web of Science ®Google Scholar
• Savitzky A, Golay MJ. 1964. Smoothing and differentiation of data by simplified least squares procedures. Anal Chem. 36:1627–1639.10.1021/ac60214a047
   Web of Science ®Google Scholar
• Schwartz MD. 1997. Spring index models: an approach to connecting satellite and surface phenology. In: Lieth, H, Schwartz, MD, editor. Phenology in seasonal climates 1. Netherlands: Backhuys; p. 23–38.
   Google Scholar
• Schwartz MD. 2003a. Phenoclimatic measures. In: Schwartz M, editor. Phenology: an integrative environmental science. Netherlands: Kluwer Academic Publishers; p. 331–343.
   Google Scholar
• Schwartz MD. 2003b. In: Schwartz M, editor. Phenology: an integrative environmental science. Netherlands: Springer;P. 385–411.10.1007/978-94-007-0632-3
   Google Scholar
• Schwartz MD, Ahas R, Aasa A. 2006. Onset of spring starting earlier across the Northern Hemisphere. Global Change Biol. 12:343–351.10.1111/gcb.2006.12.issue-2
   Web of Science ®Google Scholar
• Schwartz MD, Reiter BE. 2000. Changes in North American spring. Int J Clim. 20:929–932.10.1002/(ISSN)1097-0088
   Web of Science ®Google Scholar
• Sobrino JA, Julien Y, Atitar M, Nerry F. 2008. NOAA-AVHRR orbital drift correction from solar zenithal angle data. IEEE Trans Geosci Remote Sens. 46:4014–4019.10.1109/TGRS.2008.2000798
   Web of Science ®Google Scholar
• Steinier J, Termonia Y, Deltour J. 1972. Smoothing and differentiation of data by simplified least square procedure. Anal Chem. 44:1906–1909.10.1021/ac60319a045
   PubMed Web of Science ®Google Scholar
• Stockfors J, Linder S. 1998. The effect of nutrition on the seasonal course of needle respiration in Norway spruce stands. Trees. 12:130–138.10.1007/s004680050131
   Web of Science ®Google Scholar
• Studer S, Appenzeller C, Defila C. 2005. Inter-annual variability and decadal trends in alpine spring phenology: a multivariate analysis approach. Clim Change. 73:395–414.10.1007/s10584-005-6886-z
   Web of Science ®Google Scholar
• Studer S, Stöckli R, Appenzeller C, Vidale PL. 2007. A comparative study of satellite and ground-based phenology. Int J Biometeorol. 51:405–414.10.1007/s00484-006-0080-5
   PubMed Web of Science ®Google Scholar
• Thurner M, Beer C, Santoro M, Carvalhais N, Wutzler T, Schepaschenko D, Shvidenko A, Kompter E, Ahrens B, Levick SR, Schmullius C. 2014. Carbon stock and density of northern boreal and temperate forests. Global Ecol Biogeogr. 23:297–310.10.1111/geb.12125
   Google Scholar
• Tian F, Fensholt R, Verbesselt J, Grogan K, Horion S, Wang Y. 2015. Evaluating temporal consistency of long-term global NDVI datasets for trend analysis. Remote Sens Environ. 163:326–340.10.1016/j.rse.2015.03.031
   Web of Science ®Google Scholar
• Toms JD, Lesperance ML. 2003. Piecewise regression: a tool for identifying ecological thresholds. Ecology. 84:2034–2041.10.1890/02-0472
   Web of Science ®Google Scholar
• Tucker CJ, Pinzon JE, Brown ME, Slayback DA, Pak EW, Mahoney R, Vermote EF, El Saleous N. 2005. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. Int J Remote Sens. 26:4485–4498.10.1080/01431160500168686
   Web of Science ®Google Scholar
• Van Leeuwen WJ. 2008. Monitoring the effects of forest restoration treatments on post-fire vegetation recovery with MODIS multitemporal data. Sensors. 8:2017–2042.10.3390/s8032017
   PubMed Web of Science ®Google Scholar
• Walther G-R, Post E, Convey P, Menzel A, Parmesan C, Beebee TJ, Fromentin J-M, Hoegh-Guldberg O, Bairlein F. 2002. Ecological responses to recent climate change. Nature. 416:389–395.10.1038/416389a
   PubMed Web of Science ®Google Scholar
• Wang C, Cao R, Chen J, Rao Y, Tang Y. 2015. Temperature sensitivity of spring vegetation phenology correlates to within-spring warming speed over the Northern Hemisphere. Ecol Indic. 50:62–68.10.1016/j.ecolind.2014.11.004
   Web of Science ®Google Scholar
• Wang J, Dong J, Liu J, Huang M, Li G, Running SW, Smith WK, Harris W, Saigusa N, Kondo H. 2014. Comparison of gross primary productivity derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia. Remote Sens. 6:2108–2133.10.3390/rs6032108
   Web of Science ®Google Scholar
• White MA, Beurs D, Kirsten M, Didan K, Inouye DW, Richardson AD, Jensen OP, O’Keefe J, Zhang G, Nemani RR. 2009. Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982–2006. Global Change Biol. 15:2335–2359.10.1111/gcb.2009.15.issue-10
   Web of Science ®Google Scholar
• White MA, Hoffman F, Hargrove WW, Nemani RR. 2005. A global framework for monitoring phenological responses to climate change. Geophys Res Lett. 32: L04705.
   Web of Science ®Google Scholar
• White MA, Thornton PE, Running SW. 1997. A continental phenology model for monitoring vegetation responses to interannual climatic variability. Global Biogeochem Cycles. 11:217–234.10.1029/97GB00330
   Web of Science ®Google Scholar
• White MA, Nemani RR. 2003. Canopy duration has little influence on annual carbon storage in the deciduous broad leaf forest. Global Change Biol. 9:967–972.10.1046/j.1365-2486.2003.00585.x
   Web of Science ®Google Scholar
• Wilson K, Baldocchi D. 2000. Esimating annual net ecosystem exchange of carbon over five years at a deciduous forest in the southern United States. Agric For Meteorol. 100:1–18.10.1016/S0168-1923(99)00088-X
   Web of Science ®Google Scholar
• Wu X, Liu H. 2013. Consistent shifts in spring vegetation green-up date across temperate biomes in China, 1982–2006. Global Change Biol. 19:870–880.10.1111/gcb.2013.19.issue-3
   PubMed Web of Science ®Google Scholar
• Wu CY, Chen JM, Black TA, Price DT, Kurz WA, Desai AR, Gonsamo A, Jassal RS, Gough CM, Bohrer G, et al. 2013. Interannual variability of net ecosystem productivity in forests is explained by carbon flux phenology in autumn. Global Ecol Biogeogr. 22:994–1006.10.1111/geb.12044
   Google Scholar
• Wu W, Shibasaki R, Yang P, Zhou Q, Tang H. 2008. Characterizing spatial patterns of phenology in China's cropland based on remotely sensed data. In: International Workshop on Earth Observation and Remote Sensing Applications, 2008. EORSA 2008; IEEE; Beijing. p. 1–6.
   Google Scholar
• Xu G, Zhang HF, Chen BZ, Zhang HR, Innes JL, Wang GY, Yan JW, Zheng YH, Zhu ZC, Myneni RB. 2014. Changes in vegetation growth dynamics and relations with climate over China’s landmass from 1982 to 2011. Remote Sens. 6:3263–3283.10.3390/rs6043263
   Web of Science ®Google Scholar
• Yin H, Wang S, Li J. 2014. Determination of snow cover for the Tibetan Plateau (1983–1999) from NOAA-AVHRR LTDR. In: SPIE Asia Pacific Remote Sensing: International Society for Optics and Photonics; Beijing. p. 92600L–92610.
   Google Scholar
• Yu F, Price KP, Ellis J, Shi P. 2003. Response of seasonal vegetation development to climatic variations in eastern central Asia. Remote Sens Environ. 87:42–54.10.1016/S0034-4257(03)00144-5
   Web of Science ®Google Scholar
• Yu H, Luedeling E, Xu J. 2010. Winter and spring warming result in delayed spring phenology on the Tibetan Plateau. Proc Natl Acad Sci. 107:22151–22156.10.1073/pnas.1012490107
   PubMed Web of Science ®Google Scholar
• Zhang G, Zhang Y, Dong J, Xiao X. 2013. Green-up dates in the Tibetan Plateau have continuously advanced from 1982 to 2011. Proc Natl Acad Sci. 110:4309–4314.10.1073/pnas.1210423110
   PubMed Web of Science ®Google Scholar
• Zhang X, Friedl MA, Schaaf CB, Strahler AH, Hodges JC, Gao F, Reed BC, Huete A. 2003. Monitoring vegetation phenology using MODIS. Remote Sens Environ. 84:471–475.10.1016/S0034-4257(02)00135-9
   Web of Science ®Google Scholar
• Zhou L, Tucker CJ, Kaufmann RK, Slayback D, Shabanov NV, Myneni RB. 2001. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. J Geophys Res Atmos. 106:20069-2008310.1029/2000JD000115
   Web of Science ®Google Scholar
• Zhu Z, Bi J, Pan Y, Ganguly S, Anav A, Xu L, Samanta A, Piao S, Nemani RR, Myneni RB. 2013. Global data sets of vegetation leaf area index (LAI)3g and fraction of photosynthetically active radiation (FPAR)3g derived from global inventory modeling and mapping studies (GIMMS) normalized difference vegetation index (NDVI3g) for the period 1981–2011. Remote Sens. 5:927–948.10.3390/rs5020927
   Web of Science ®Google Scholar