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Volf, M.; Weinhold, A.; Seifert, C. L.; Holicová, T.; Uthe, H.; Alander, E.; Richter, R.; Salminen, J.-P.; Wirth, C.; van Dam, N. M.: Branch-localized induction promotes efficacy of volatile defences and herbivore predation in trees. Journal of Chemical Ecology 47, S. 99 - 111 (2021)
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Zhang, X.; Xu, B.; Li, J.; Xie, Y.; Gleixner, G.: Late-Holocene fluctuations of monsoonal Qiangyong Glacier, southern Tibetan Plateau. The Holocene 31 (7), S. 1138 - 1147 (2021)
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Zhang, Y.; Migliavacca, M.; Penuelas, J.; Ju, W.: Advances in hyperspectral remote sensing of vegetation traits and functions. Remote Sensing of Environment 252, 112121 (2021)

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Camps-Valls, G.; Tuia, D.; Zhu, X. X.; Reichstein, M. (Hg.): Deep learning for the earth sciences: A comprehensive approach to remote sensing, climate science, and geosciences. John Wiley & Sons Ltd, Hoboken, New Jersey (2021), 405 S.

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Camps-Valls, G.; Zhu, X. X.; Tuia, D.; Reichstein, M.: Introduction. In: Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences (Hg. Camps-Valls, G.; Tuia, D.; Zhu, X. X.; Reichstein, M.). John Wiley & Sons Ltd, Hoboken, New Jersey (2021)
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Kraft, B.; Besnard, S.; Koirala, S.: Emulating ecological memory with recurrent neural networks. In: Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences, S. 269 - 281 (Hg. Camps-Valls, G.; Tuia, D.; Zhu, X. X.; Reichstein, M.). John Wiley & Sons Ltd, Hoboken, New Jersey (2021)
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Mateo-García, G.; Laparra, V.; Requena Mesa, C.; Gómez-Chova, L.: Generative adversarial networks in the Geosciences. In: Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences, S. 24 - 36 (Hg. Camps-Valls, G.; Tuia, D.; Zhu, X. X.; Reichstein, M.). John Wiley & Sons Ltd, Hoboken, New Jersey (2021)
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Reichstein, M.; Camps-Valls, G.; Tuia, D.; Zhu, X. X.: Outlook. In: Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences, S. 328 - 330 (Hg. Camps-Valls, G.; Tuia, D.; Zhu, X. X.; Reichstein, M.). John Wiley & Sons Ltd, Hoboken, New Jersey (2021)
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Tibau, X.-A.; Reimers, C.; Requena Mesa, C.; Runge, J.: Spatio-temporal Autoencoders in Weather and Climate Research. In: Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences, S. 186 - 203 (Hg. Camps-Valls, G.; Tuia, D.; Zhu, X. X.; Reichstein, M.). John Wiley & Sons Ltd, Hoboken, New Jersey (2021)
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Kolle, O.; Kalthoff, N.; Kottmeier, C.; Munger, J. W.: Ground-based platforms. In: Handbook of Atmospheric Measurements, S. 155 - 182 (Hg. Foken, T.). Springer, Cham (2021)
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Reimers, C.; Bodesheim, P.; Runge, J.; Denzler, J.: Conditional adversarial debiasing: Towards learning unbiased classifiers from biased data. In: Pattern Recognition. DAGM GCPR 2021. Lecture Notes in Computer Science, Bd. 13024, S. 48 - 62. Springer International Publishing, Cham (2021)

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Gottfriedsen, J.; Berrendorf, M.; Gentine, P.; Hassler, B.; Reichstein, M.; Weigel, K.; Eyring, V.: On the generalization of agricultural drought classification from climate data. In: NeurIPS 2021. Workshop - Tackling Climate Change with Machine Learning On the Generalization of ML-based Agricultural Drought Classification from Climate Date, 2021. (2021)
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Körschens, M.; Bodesheim, P.; Römermann, C.; Bucher, S. F.; Migliavacca, M.; Ulrich, J.; Denzler, J.: Automatic plant cover estimation with convolutional neural networks. In: GI-Edition: lecture notes in informatics. Proceedings. Informatik 2021 : computer science & sustainability, Berlin / Gesellschaft für Informatik e.V. (GI) (Hrsg.) , 27. September 2021 - 01. Oktober 2021. Ges. für Informatik, Bonn (2021)
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Requena Mesa, C.; Benson, V.; Reichstein, M.; Runge, J.; Denzler, J.: EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction task. In: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW, Nashville, TN, USA , 19. Juni 2021 - 25. Juni 2021. IEEE, Nashville, TN, USA (2021)
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Ahrens, B.: Reconciling turnover models of roots and soil organic carbon with radiocarbon measurements. Dissertation, 232 S., Leibniz University Hannover, Hannover (2021)
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Benk, S.: Towards a Data-Driven Understanding of Dissolved Organic Matter in the Critical Zone. Dissertation, Friedrich Schiller University Jena, Jena (2021)
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Chowdhury, S.: Effect of plant inputs and nutrient acquisition strategies on soil microbial community. Dissertation, Friedrich Schiller University Jena, Jena (2021)
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