Publications of Basil Kraft

Journal Article (6)

Journal Article
Li, W.; Reichstein, M.; O, S.; May, C.; Destouni, G.; Migliavacca, M.; Kraft, B.; Weber, U.; Orth, R.: Contrasting drought propagation into the terrestrial water cycle between dry and wet regions. Earth's Future 11 (7), e2022EF003441 (2023)
Journal Article
Lee, H. T.; Jung, M.; Carvalhais, N.; Trautmann, T.; Kraft, B.; Reichstein, M.; Forkel, M.; Koirala, S.: Diagnosing modeling errors in global terrestrial water storage interannual variability. Hydrology and Earth System Sciences 27 (7), pp. 1531 - 1563 (2023)
Journal Article
ElGhawi, R.; Kraft, B.; Reimers, C.; Reichstein, M.; Körner, M.; Gentine, P.; Winkler, A. J.: Hybrid modeling of evapotranspiration: inferring stomatal and aerodynamic resistances using combined physics-based and machine learning. Environmental Research 18, 034039 (2023)
Journal Article
Kraft, B.; Jung, M.; Körner, M.; Koirala, S.; Reichstein, M.: Towards hybrid modeling of the global hydrological cycle. Hydrology and Earth System Sciences 26 (6), pp. 1579 - 1614 (2022)
Journal Article
Kraft, B.; Jung, M.; Körner, M.; Reichstein, M.: Hybrid modeling: Fusion of a deep approach and physics-based model for global hydrological modeling. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2020, pp. 1537 - 1544 (2020)
Journal Article
Kraft, B.; Jung, M.; Körner, M.; Requena Mesa, C.; Cortés, J.; Reichstein, M.: Identifying dynamic memory effects on vegetation state using recurrent neural networks. Frontiers in Big Data 2, 31 (2019)

Book Chapter (3)

Book Chapter
Reichstein, M.; Ahrens, B.; Kraft, B.; Camps-Valls, G.; Carvalhais, N.; Gans, F.; Gentine, P.; Winkler, A.: Combining system modeling and machine learning into hybrid ecosystem modeling. In: Knowledge-Guided Machine Learning, 9781003143376, pp. 327 - 352 (Eds. Kannan, R.; Kumar, V.). Chapman & Hall, London (2022)
Book Chapter
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, pp. 269 - 281 (Eds. Camps-Valls, G.; Tuia, D.; Zhu, X. X.; Reichstein, M.). John Wiley & Sons Ltd, Hoboken, New Jersey (2021)
Book Chapter
Requena-Mesa, C.; Reichstein, M.; Mahecha, M. D.; Kraft, B.; Denzler, J.: Predicting landscapes from environmental conditions using generative networks. In: Pattern Recognition, DAGM GCPR 2019, pp. 203 - 217 (Eds. FInk, G. A.; Frintrop, S.; Jiang, X.). Springer, Cham (2019)

Conference Paper (2)

Conference Paper
Reichstein, M.; Besnard, S.; Carvalhais, N.; Gans, F.; Jung, M.; Kraft, B.; Mahecha, M. D.: Modelling landsurface time-series with recurrent neural nets. In: 2018 IEEE International geoscience and remote sensing symposium (IGARSS), pp. 7640 - 7643. Valencia, 2018 (2018)
Conference Paper
Requena-Mesa, C.; Reichstein, M.; Mahecha, M. D.; Kraft, B.; Denzler, J.: Predicting landscapes as seen from space from environmental conditions. In: 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 1768 - 1771. (2018)

Thesis - PhD (1)

Thesis - PhD
Kraft, B.: Deep learning and hybrid modeling of global vegetation and hydrology. Dissertation, Technical University of Munich, München (2022)
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