-----------------Publication----------------
——2026——

Yang,X. et al. (2026). Amazon rainforestsare rejuvenating their canopies by producing more photosynthetically efficientyoung leaves under climate change. NaturePlants. DOI: https://doi.org/10.1038/s41477-026-02240-9

Xu,R. et al. (2026). Do CMIP6 earthsystem models outperform their predecessors in simulating global vegetationchanges?. Agricultural and ForestMeteorology. DOI: https://doi.org/10.1016/j.agrformet.2026.111067

Anniwaer,N. et al. (2026). Intensifiedseasonal droughts and carryover effects amplify negative growth anomalies inEurasian grasslands during the past four decades. Ecological Indicators. DOI: https://doi.org/10.1016/j.ecolind.2026.114641

Zhuo,W. et al. (2026). Predictability ofEarth's greenness. ISPRS Journal ofPhotogrammetry and Remote Sensing. DOI: https://doi.org/10.1016/j.isprsjprs.2026.02.038

Zhao,W. et al. (2026). Prevalent GreeningConceals the Forgone Ecological Potential of Forest Loss in Southeast Asia. Geophysical Research Letters. DOI: https://doi.org/10.1029/2025GL121593


——2025——

Li,Z. et al. (2025). Altitudinal Shiftsas a Climate Resilience Strategy for Angelica sinensis Production in ItsPrimary Cultivation Region. RemoteSensing. DOI: https://doi.org/10.3390/rs17122085

Zheng,Y. et al. (2025). Assessing theDirect Impact of Typhoons on Vegetation Canopy Structure and Photosynthesis. Journal of Remote Sensing. DOI: https://doi.org/10.34133/remotesensing.0430

Duanmu,Z. et al. (2025). Changes in leafand root carbon allocation of global vegetation simulated by the optimallyintegrated ecosystem models. Agriculturaland Forest Meteorology. DOI: https://doi.org/10.1016/j.agrformet.2024.110366

Wang,F. et al. (2025). Contrastingage-dependent leaf acclimation strategies drive vegetation greening acrossdeciduous broadleaf forests in mid- to high latitudes. Nature Plants. DOI: https://doi.org/10.1038/s41477-025-02096-5

Anniwaer,N. et al. (2025). Decadal changes insummer and autumn soil moisture drive dual shifts in Eurasian grasslandvegetation growth trends during 1982–2018. Globaland Planetary Change. DOI: https://doi.org/10.1016/j.gloplacha.2025.105137

Wang,Z. et al. (2025). Estimating canopyleaf angle from leaf to ecosystem scale: a novel deep learning approach usingunmanned aerial vehicle imagery. NewPhytologist. DOI: https://doi.org/10.1111/nph.70197

Wang,Z. et al. (2025). Land Use ChangeForcing Data Undermine the Modeling of China's Greening Efforts. Geophysical Research Letters. DOI: https://doi.org/10.1029/2024GL113403

Liang,Y. et al. (2025). Three Decades ofLand Cover Changes Shifted Environment-Driven Greening Towards Browning inCoastal China. Global Change Biology. DOI: https://doi.org/10.1111/gcb.70134


——2024——

Yu,M. et al. (2024). Warming and RisingAtmospheric CO2 Concentration Drive Global Woody Encroachment from 2001 to2020. Ecosystem Health andSustainability. DOI: https://doi.org/10.34133/ehs.0272

Zhao,W. et al. (2024). A global datasetof the fraction of absorbed photosynthetically active radiation for 1982–2022. Scientific Data. DOI: https://doi.org/10.1038/s41597-024-03561-0

Zheng,X. et al. (2024). Characterizationand Evaluation of Global Solar-Induced Chlorophyll Fluorescence Products:Estimation of Gross Primary Productivity and Phenology. Journal of Remote Sensing. DOI: https://doi.org/10.34133/remotesensing.0173

Li,D. et al. (2024). Desertificationsensitivity and its impacts on land use change in the Tarim Basin, NorthwestChina. Science of the Total Environment. DOI: https://doi.org/10.1016/j.scitotenv.2024.177601

Fu,Z. et al. (2024). Global criticalsoil moisture thresholds of plant water stress. Nature Communications. DOI: https://doi.org/10.1038/s41467-024-49244-7

Luo,Y. et al. (2024). Hybrid GlobalAnnual 1-km IGBP Land Cover Maps for the Period 2000–2020. Journal of Remote Sensing. DOI: https://doi.org/10.34133/remotesensing.0122

Chen,J.N. et al. (2024). Scientific landgreening under climate change: Theory, modeling, and challenges. Advances in Climate Change Research. DOI: https://doi.org/10.1016/j.accre.2024.08.003

Pu,J. et al. (2024). Sensor-independentLAI/FPAR CDR: reconstructing a global sensor-independent climate data record ofMODIS and VIIRS LAI/FPAR from 2000 to 2022. EarthSystem Science Data. DOI: https://doi.org/10.5194/essd-16-15-2024

Huang,D. et al. (2024). Urban greeningamidst global change: A comparative study of vegetation dynamics in two urbanagglomerations in China under climatic and anthropogenic pressures. Ecological Indicators. DOI: https://doi.org/10.1016/j.ecolind.2024.111739

Zheng,Y. et al. (2024). Vegetation canopystructure mediates the response of gross primary production to environmentaldrivers across multiple temporal scales. Scienceof the Total Environment. DOI: https://doi.org/10.1016/j.scitotenv.2024.170439

Li,X. et al. (2024). Vegetationgreenness in 2023. Nature Reviews Earth& Environment. DOI: https://doi.org/10.1038/s43017-024-00543

——2023——

Chen,Y. et al. (2023). The direct andindirect effects of the environmental factors on global terrestrial grossprimary productivity over the past four decades. Environmental Research Letters. DOI: https://doi.org/10.1088/1748-9326/ad107f

Su,Y. et al. (2023). Asymmetricinfluence of forest cover gain and loss on land surface temperature. Nature Climate Change. DOI: https://doi.org/10.1038/s41558-023-01757-7

Li,L. et al. (2023). Competitionbetween biogeochemical drivers and land-cover changes determines urban greeningor browning. Remote Sensing ofEnvironment. DOI: https://doi.org/10.1016/j.rse.2023.113481

Zou,L. et al. (2023). Dynamic globalvegetation models may not capture the dynamics of the leaf area index in thetropical rainforests: A data-model intercomparison. Agricultural and Forest Meteorology. DOI:https://doi.org/10.1016/j.agrformet.2023.109562

Li,H. et al. (2023). Nitrogen additiondelays the emergence of an aridity-induced threshold for plant biomass. National Science Review. DOI: https://doi.org/10.1093/nsr/nwad242

Tian,F. et al. (2023). Satellite-observedincreasing coupling between vegetation productivity and greenness in thesemiarid Loess Plateau of China not captured by process-based models. Science of the Total Environment. DOI: https://doi.org/10.1016/j.scitotenv.2023.167664

Cao,S. et al. (2023). Spatiotemporallyconsistent global dataset of the GIMMS leaf area index (GIMMS LAI4g) from 1982to 2020. Earth System Science Data. DOI: https://doi.org/10.5194/essd-15-4877-2023

Li,M. et al. (2023). Spatiotemporallyconsistent global dataset of the GIMMS Normalized Difference Vegetation Index(PKU GIMMS NDVI) from 1982 to 2022. EarthSystem Science Data. DOI: https://doi.org/10.5194/essd-15-4181-2023

——2022——

Luo,Y. et al. (2022). Exploring habitatpatch clusters based on network community detection to identify restoredpriority areas of ecological networks in urban areas. Urban Forestry & Urban Greening. DOI:https://doi.org/10.1016/j.ufug.2022.127771

Zhao,W. et al. (2022). Exploring theBest-Matching Plant Traits and Environmental Factors for Vegetation Indices inEstimates of Global Gross Primary Productivity. Remote Sensing. DOI: https://doi.org/10.3390/rs14246316

Zou,L. et al. (2022). Object-OrientedUnsupervised Change Detection Based on Neighborhood Correlation Images andk-Means Clustering for the Multispectral and High Spatial Resolution Images. Canadian Journal of Remote Sensing. DOI: https://doi.org/10.1080/07038992.2022.2056434

Zhao,Q. et al. (2022). Seasonal peakphotosynthesis is hindered by late canopy development in northern ecosystems. Nature Plants. DOI:https://doi.org/10.1038/s41477-022-01278-9


——2021——

Zou,L. et al. (2021). Assessment of theresponse of tropical dry forests to El Niño Southern Oscillation. Ecological Indicators. DOI: https://doi.org/10.1016/j.ecolind.2021.108390

Zhu,Z. et al. (2021). Comment on “Recentglobal decline of CO2 fertilization effects on vegetation photosynthesis”. Science. DOI:https://doi.org/10.1126/science.abg5673

Huang,B. et al. (2021). Effects ofurbanization on vegetation conditions in coastal zone of China. Progress in Physical Geography: Earth andEnvironment. DOI: https://doi.org/10.1177/0309133320979501

Yu,X. et al. (2021). Research in CropYield Estimation Models on Different Scales Based on Remote Sensing and CropGrowth Model / 基于遥感和作物生长模型的多尺度冬小麦估产研究.Spectroscopy and Spectral Analysis. DOI: https://doi.org/10.3964/j.issn.1000-0593(2021)07-2205-07

Zhu,Z. (2021). Toward an in-depthevaluation of the ecosystem component of CMIP6 Earth system models. Advances in Climate Change Research. DOI: https://doi.org/10.1016/j.accre.2021.08.006

——2020、2019——

Song,G. et al. (2019). Shift from feedingto sustainably nourishing urban China: A crossing-disciplinary methodology forglobal environment-food-health nexus. Scienceof the Total Environment. DOI: https://doi.org/10.1016/j.scitotenv.2018.08.040

Chen,C. et al. (2019). China and Indialead in greening of the world through land-use management. Nature Sustainability. DOI: https://doi.org/10.1038/s41893-019-0220-7

Bastos,A. et al. (2019). Contrastingeffects of CO2 fertilization, land-use change and warming on seasonal amplitudeof Northern Hemisphere CO2 exchange. AtmosphericChemistry and Physics. DOI: https://doi.org/10.5194/acp-19-12361-2019

Zhao,Q. et al. (2020). Future greening ofthe Earth may not be as large as previously predicted. Agricultural and Forest Meteorology. DOI:https://doi.org/10.1016/j.agrformet.2020.108111

Zhang,W. et al. (2020). Landscapeecological risk assessment of Chinese coastal cities based on land use change. Applied Geography. DOI: https://doi.org/10.1016/j.apgeog.2020.102174

Yan,H. et al. (2020). Recent wettingtrend in China from 1982 to 2016 and the impacts of extreme El Niño events. International Journal of Climatology. DOI: https://doi.org/10.1002/joc.6530

Song,X. et al. (2020). Vegetation biomasschange in China in the 20th century: An assessment based on a combination ofmulti-model simulations and field observations. Environmental Research Letters. DOI: https://doi.org/10.1088/1748-9326/ab94e8


——2018、2017——

Chen,C. et al. (2019). China and Indialead in greening of the world through land-use management. Nature Sustainability. DOI: https://doi.org/10.1038/s41893-019-0220-7

Bastos,A. et al. (2019). Contrastingeffects of CO2 fertilization, land-use change and warming on seasonal amplitudeof Northern Hemisphere CO2 exchange. AtmosphericChemistry and Physics. DOI: https://doi.org/10.5194/acp-19-12361-2019

Song,G. et al. (2019). Shift from feedingto sustainably nourishing urban China: A crossing-disciplinary methodology forglobal environment-food-health nexus. Scienceof the Total Environment. DOI: https://doi.org/10.1016/j.scitotenv.2018.08.040

Zhang,X. et al. (2018). Dominant regionsand drivers of the variability of the global land carbon sink acrosstimescales. Global Change Biology. DOI: https://doi.org/10.1111/gcb.14275

Liu,M. et al. (2018). Factorscontrolling changes in evapotranspiration, runoff, and soil moisture over theconterminous U.S.: Accounting for vegetation dynamics. Journal of Hydrology. DOI: https://doi.org/10.1016/j.jhydrol.2018.07.068

Piao,S. et al. (2018). Lower land-useemissions responsible for increased net land carbon sink during the slowwarming period. Nature Geoscience. DOI: https://doi.org/10.1038/s41561-018-0204-7

Li,W. et al. (2018). Recent Changes inGlobal Photosynthesis and Terrestrial Ecosystem Respiration Constrained FromMultiple Observations. GeophysicalResearch Letters. DOI: https://doi.org/10.1002/2017GL076622

Zhu,Z. et al. (2018). The AcceleratingLand Carbon Sink of the 2000s May Not Be Driven Predominantly by the WarmingHiatus. Geophysical Research Letters. DOI: https://doi.org/10.1002/2017GL075808

Zhu,Z. et al. (2017). Attribution ofseasonal leaf area index trends in the northern latitudes with optimallyintegrated ecosystem models. GlobalChange Biology. DOI: https://doi.org/10.1111/gcb.13723

Jiang,C. et al. (2017). Inconsistencies ofinterannual variability and trends in long-term satellite leaf area indexproducts. Global Change Biology. DOI: https://doi.org/10.1111/gcb.13787

Yin,Y. et al. (2017). Nonlinearvariations of forest leaf area index over China during 1982–2010 based on EEMDmethod. International Journal ofBiometeorology. DOI: https://doi.org/10.1007/s00484-016-1277-x

Zhao,C. et al. (2017). Temperatureincrease reduces global yields of major crops in four independent estimates. Proceedings of the National Academy ofSciences. DOI: https://doi.org/10.1073/pnas.1701762114

Zhu,Z. et al. (2017). The effects ofteleconnections on carbon fluxes of global terrestrial ecosystems. Geophysical Research Letters. DOI: https://doi.org/10.1002/2016GL071743

Huang,M. et al. (2017). Velocity of changein vegetation productivity over northern high latitudes. Nature Ecology & Evolution. DOI: https://doi.org/10.1038/s41559-017-0328-y

Bastos,A. et al. (2017). Was the extremeNorthern Hemisphere greening in 2015 predictable?. Environmental Research Letters. DOI: https://doi.org/10.1088/1748-9326/aa67b5

Piao,S. et al. (2017). Weakeningtemperature control on the interannual variations of spring carbon uptakeacross northern lands. Nature ClimateChange. DOI: https://doi.org/10.1038/nclimate3277