Publikationen von Basil Kraft
Alle Typen
Zeitschriftenartikel (6)
Zeitschriftenartikel
21 (22), S. 5079 - 5115 (2024)
X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X. Biogeosciences
Zeitschriftenartikel
17 (17), S. 6683 - 6701 (2024)
DeepPhenoMem V1.0: Deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology. Geoscientific Model Development
Zeitschriftenartikel
24 (4), S. 2555 - 2582 (2024)
Constraining biospheric carbon dioxide fluxes by combined top-down and bottom-up approaches. Atmospheric Chemistry and Physics
Zeitschriftenartikel
27 (7), S. 1531 - 1563 (2023)
Diagnosing modeling errors in global terrestrial water storage interannual variability. Hydrology and Earth System Sciences
Zeitschriftenartikel
26 (6), S. 1579 - 1614 (2022)
Towards hybrid modeling of the global hydrological cycle. Hydrology and Earth System Sciences
Zeitschriftenartikel
XLIII-B2-2020, S. 1537 - 1544 (2020)
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 Buchkapitel (2)
Buchkapitel
Reichstein, M.). John Wiley & Sons Ltd, Hoboken, New Jersey (2021)
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.;
Buchkapitel
Predicting landscapes from environmental conditions using generative networks. In: Pattern Recognition, DAGM GCPR 2019, S. 203 - 217 (Hg. FInk, G. A.; Frintrop, S.; Jiang, X.). Springer, Cham (2019)
Konferenzbeitrag (1)
Konferenzbeitrag
Modelling landsurface time-series with recurrent neural nets. In: 2018 IEEE International geoscience and remote sensing symposium (IGARSS), S. 7640 - 7643. Valencia, 2018 (2018)
Hochschulschrift - Doktorarbeit (1)
Hochschulschrift - Doktorarbeit
Deep learning and hybrid modeling of global vegetation and hydrology. Dissertation, Technical University of Munich, München (2022)