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期刊论文 [4]
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2020 [1]
2017 [1]
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phenology [4]
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globalchange

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A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level [期刊论文]
Global Change Biology, 2020-01-01, 26 (3
Jiang H.;  Hu H.;  Zhong R.;  Xu J.;  Xu J.;  Huang J.;  Wang S.;  Ying Y.;  Lin T.
View/Download：41/0
 
Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment [期刊论文]
Global Change Biology, 2017-01-01, 23 (9
De Kauwe M.G.;  Medlyn B.E.;  Walker A.P.;  Zaehle S.;  Asao S.;  Guenet B.;  Harper A.B.;  Hickler T.;  Jain A.K.;  Luo Y.;  Lu X.;  Luus K.;  Parton W.J.;  Shu S.;  Wang Y.-P.;  Werner C.;  Xia J.;  Pendall E.;  Morgan J.A.;  Ryan E.M.;  Carrillo Y.;  Dijkstra F.A.;  Zelikova T.J.;  Norby R.J.
View/Download：44/0
 
Unexpected role of winter precipitation in determining heat requirement for spring vegetation green-up at northern middle and high latitudes [期刊论文]
Global Change Biology, 2014-01-01, 20 (12
Fu Y.H.;  Piao S.;  Zhao H.;  Jeong S.-J.;  Wang X.;  Vitasse Y.;  Ciais P.;  Janssens I.A.
View/Download：30/0
 
Changes in satellite-derived spring vegetation green-up date and its linkage to climate in China from 1982 to 2010: A multimethod analysis [期刊论文]
Global Change Biology, 2013-01-01, 19 (3
Cong N.;  Wang T.;  Nan H.;  Ma Y.;  Wang X.;  Myneni R.B.;  Piao S.
View/Download：16/0
 

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