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Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches
Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches
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Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

Cai, Yaping ; Guan, Kaiyu ; Lobell, David ; Potgieter, Andries B. ; Wang, Shaowen ; Peng, Jian ; Xu, Tianfang ; Asseng, Senthold ; Zhang, Yongguang ; You, Liangzhi ; Peng, Bin

Agricultural and forest meteorology, 2019-08, Vol.274, p.144-159 [Periódico revisado por pares]

Elsevier B.V

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Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates of China
Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates of China
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Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates of China

Fan, Junliang ; Yue, Wenjun ; Wu, Lifeng ; Zhang, Fucang ; Cai, Huanjie ; Wang, Xiukang ; Lu, Xianghui ; Xiang, Youzhen

Agricultural and forest meteorology, 2018-12, Vol.263, p.225-241 [Periódico revisado por pares]

Elsevier B.V

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3
The Arctic is burning like never before - and that's bad news for climate change
The Arctic is burning like never before - and that's bad news for climate change
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The Arctic is burning like never before - and that's bad news for climate change

Witze, Alexandra

Nature (London), 2020-09, Vol.585 (7825), p.336-337 [Periódico revisado por pares]

England: Nature Publishing Group

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4
Inter-annual variability of net and gross ecosystem carbon fluxes: A review
Inter-annual variability of net and gross ecosystem carbon fluxes: A review
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Inter-annual variability of net and gross ecosystem carbon fluxes: A review

Baldocchi, Dennis ; Chu, Housen ; Reichstein, Markus

Agricultural and forest meteorology, 2018-02, Vol.249 (C), p.520-533 [Periódico revisado por pares]

United States: Elsevier B.V

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5
Increasing Tibetan Plateau terrestrial evapotranspiration primarily driven by precipitation
Increasing Tibetan Plateau terrestrial evapotranspiration primarily driven by precipitation
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Increasing Tibetan Plateau terrestrial evapotranspiration primarily driven by precipitation

Ma, Ning ; Zhang, Yongqiang

Agricultural and forest meteorology, 2022-04, Vol.317, p.108887, Article 108887 [Periódico revisado por pares]

Elsevier B.V

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6
Diverse responses of vegetation growth to meteorological drought across climate zones and land biomes in northern China from 1981 to 2014
Diverse responses of vegetation growth to meteorological drought across climate zones and land biomes in northern China from 1981 to 2014
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Diverse responses of vegetation growth to meteorological drought across climate zones and land biomes in northern China from 1981 to 2014

Xu, Hao-jie ; Wang, Xin-ping ; Zhao, Chuan-yan ; Yang, Xue-mei

Agricultural and forest meteorology, 2018-11, Vol.262, p.1-13 [Periódico revisado por pares]

Elsevier B.V

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7
Assessing the effects of climate change on the phenology of European temperate trees
Assessing the effects of climate change on the phenology of European temperate trees
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Assessing the effects of climate change on the phenology of European temperate trees

Vitasse, Yann ; François, Christophe ; Delpierre, Nicolas ; Dufrêne, Eric ; Kremer, Antoine ; Chuine, Isabelle ; Delzon, Sylvain

Agricultural and forest meteorology, 2011-07, Vol.151 (7), p.969-980 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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8
Review of indirect optical measurements of leaf area index: Recent advances, challenges, and perspectives
Review of indirect optical measurements of leaf area index: Recent advances, challenges, and perspectives
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Review of indirect optical measurements of leaf area index: Recent advances, challenges, and perspectives

Yan, Guangjian ; Hu, Ronghai ; Luo, Jinghui ; Weiss, Marie ; Jiang, Hailan ; Mu, Xihan ; Xie, Donghui ; Zhang, Wuming

Agricultural and forest meteorology, 2019-02, Vol.265, p.390-411 [Periódico revisado por pares]

Elsevier B.V

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9
The AmeriFlux network: A coalition of the willing
The AmeriFlux network: A coalition of the willing
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The AmeriFlux network: A coalition of the willing

Novick, K.A. ; Biederman, J.A. ; Desai, A.R. ; Litvak, M.E. ; Moore, D.J.P. ; Scott, R.L. ; Torn, M.S.

Agricultural and forest meteorology, 2018-02, Vol.249, p.444-456 [Periódico revisado por pares]

Elsevier B.V

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10
Dynamic wheat yield forecasts are improved by a hybrid approach using a biophysical model and machine learning technique
Dynamic wheat yield forecasts are improved by a hybrid approach using a biophysical model and machine learning technique
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Dynamic wheat yield forecasts are improved by a hybrid approach using a biophysical model and machine learning technique

Feng, Puyu ; Wang, Bin ; Liu, De Li ; Waters, Cathy ; Xiao, Dengpan ; Shi, Lijie ; Yu, Qiang

Agricultural and forest meteorology, 2020-05, Vol.285-286, p.107922, Article 107922 [Periódico revisado por pares]

Elsevier B.V

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