Publications

David Montero, Guido Kraemer, Anca Anghelea, César Aybar, Gunnar Brandt, Gustau Camps-Valls, Felix Cremer, Ida Flik, Fabian Gans, Sarah Habershon, und et al.. Earth System Data Cubes: Avenues for advancing Earth system research. Environmental Data Science, (3):e27, 2024. [PUMA: topic_earthenvironment]

Olivier C. Pasche, Jonathan Wider, Zhongwei Zhang, Jakob Zscheischler, und Sebastian Engelke. Validating Deep Learning Weather Forecast Models on Recent High-Impact Extreme Events. Artificial Intelligence for the Earth Systems, (4)1:e240033, American Meteorological Society, Boston MA, USA, 2025. [PUMA: topic_earthenvironment] URL

Jessenia Gonzalez, Sudhakar Dipu, Odran Sourdeval, Alexandre Siméon, Gustau Camps-Valls, und Johannes Quaas. Emulation of Forward Modeled Top-of-Atmosphere MODIS-Based Spectral Channels Using Machine Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, (18):1896-1911, 2025. [PUMA: topic_earthenvironment]

Daniel Mederer, Hannes Feilhauer, Eya Cherif, Katja Berger, Tobias B. Hank, Kyle R. Kovach, Phuong D. Dao, Bing Lu, Philip A. Townsend, und Teja Kattenborn. Plant trait retrieval from hyperspectral data: Collective efforts in scientific data curation outperform simulated data derived from the PROSAIL model. ISPRS Open Journal of Photogrammetry and Remote Sensing, 100080, Elsevier BV, Dezember 2024. [PUMA: topic_earthenvironment] URL

Ni Li, Shorouq Zahra, Mariana Brito, Clare Flynn, Olof Görnerup, Koffi Worou, Murathan Kurfali, Chanjuan Meng, Wim Thiery, Jakob Zscheischler, Gabriele Messori, und Joakim Nivre. Using LLMs to Build a Database of Climate Extreme Impacts. Proceedings of the 1st Workshop on Natural Language Processing Meets Climate Change (ClimateNLP 2024), 93–110, Association for Computational Linguistics, 2024. [PUMA: imported topic_earthenvironment] URL

Mohit Anand, Friedrich J. Bohn, Gustau Camps-Valls, Rico Fischer, Andreas Huth, Lily-belle Sweet, und Jakob Zscheischler. Identifying compound weather drivers of forest biomass loss with generative deep learning. Environmental Data Science, (3)Cambridge University Press (CUP), 2024. [PUMA: imported topic_earthenvironment] URL

Daniel Klotz, Martin Gauch, Frederik Kratzert, Grey Nearing, und Jakob Zscheischler. Technical Note: The divide and measure nonconformity – how metrics can mislead when we evaluate on different data partitions. Hydrology and Earth System Sciences, (28)15:3665–3673, Copernicus GmbH, August 2024. [PUMA: imported topic_earthenvironment] URL

Ni Li, Wim Thiery, Jakob Zscheischler, Gabriele Messori, Liane Guillou, Joakim Nivre, Olof Görnerup, Seppe Lampe, Clare Flynn, Mariana Madruga de Brito, und Aglae Jezequel. A new climate impact database using generative AI. Copernicus GmbH, November 2024. [PUMA: imported topic_earthenvironment] URL

Brian Groenke, Kristoffer Aalstad, Norbert Pirk, Sebastian Westermann, Jakob Zscheischler, Guillermo Gallego, und Julia Boike. Simulation-based inference as a paradigm for scientific machine learning in the cryosphere and beyond. Copernicus GmbH, März 2024. [PUMA: imported topic_earthenvironment] URL

Shijie Jiang, Lily‐belle Sweet, Georgios Blougouras, Alexander Brenning, Wantong Li, Markus Reichstein, Joachim Denzler, Wei Shangguan, Guo Yu, Feini Huang, und Jakob Zscheischler. How Interpretable Machine Learning Can Benefit Process Understanding in the Geosciences. Earth’s Future, (12)7American Geophysical Union (AGU), Juli 2024. [PUMA: imported topic_earthenvironment] URL

Teja Kattenborn, Sebastian Wieneke, David Montero, Miguel D. Mahecha, Ronny Richter, Claudia Guimarães-Steinicke, Christian Wirth, Olga Ferlian, Hannes Feilhauer, Lena Sachsenmaier, Nico Eisenhauer, und Benjamin Dechant. Temporal dynamics in vertical leaf angles can confound vegetation indices widely used in Earth observations. Communications Earth & Environment, (5)1Springer Science and Business Media LLC, Oktober 2024. [PUMA: imported topic_earthenvironment] URL

Oscar J. Pellicer-Valero, Miguel-Ángel Fernández-Torres, Chaonan Ji, Miguel D. Mahecha, und Gustau Camps-Valls. Explainable Earth Surface Forecasting under Extreme Events. arXiv, 2024. [PUMA: (cs.LG), Computer FOS: Learning Machine and information sciences sciences, topic_earthenvironment] URL

Marco Hannemann, Almudena Garc\'ıa-Garc\'ıa, Rafael Poyatos, Miguel D Mahecha, und Jian Peng. Estimating transpiration globally by integrating the Priestley-Taylor model with neural networks. Environ. Res. Lett., (19)11:114089, IOP Publishing, November 2024. [PUMA: imported topic_earthenvironment]

Jan Sodoge, Christian Kuhlicke, Miguel D. Mahecha, und Mariana Madruga de Brito. Text mining uncovers the unique dynamics of socio-economic impacts of the 2018–2022 multi-year drought in Germany. Natural Hazards and Earth System Sciences, (24)5:1757–1777, Copernicus GmbH, Mai 2024. [PUMA: imported topic_earthenvironment] URL

Maximilian Söchting, Miguel D. Mahecha, David Montero, und Gerik Scheuermann. Lexcube: Interactive Visualization of Large Earth System Data Cubes. IEEE Computer Graphics and Applications, (44)1:25–37, Institute of Electrical and Electronics Engineers (IEEE), Januar 2024. [PUMA: imported topic_earthenvironment] URL

M. D. Mahecha, A. Bastos, F. J. Bohn, N. Eisenhauer, H. Feilhauer, T. Hickler, H. Kalesse‐Los, M. Migliavacca, F. E. L. Otto, J. Peng, S. Sippel, I. Tegen, A. Weigelt, M. Wendisch, C. Wirth, D. Al‐Halbouni, H. Deneke, D. Doktor, S. Dunker, G. Duveiller, A. Ehrlich, A. Foth, A. García‐García, C. A. Guerra, C. Guimarães‐Steinicke, H. Hartmann, S. Henning, H. Herrmann, P. Hu, C. Ji, T. Kattenborn, N. Kolleck, M. Kretschmer, I. Kühn, M. L. Luttkus, M. Maahn, M. Mönks, K. Mora, M. Pöhlker, M. Reichstein, N. Rüger, B. Sánchez‐Parra, M. Schäfer, F. Stratmann, M. Tesche, B. Wehner, S. Wieneke, A. J. Winkler, S. Wolf, S. Zaehle, J. Zscheischler, und J. Quaas. Biodiversity and Climate Extremes: Known Interactions and Research Gaps. Earth’s Future, (12)6American Geophysical Union (AGU), Juni 2024. [PUMA: imported topic_earthenvironment] URL

Sophie Wolf, Miguel D. Mahecha, Francesco Maria Sabatini, Christian Wirth, Helge Bruelheide, Jens Kattge, Álvaro Moreno Martínez, Karin Mora, und Teja Kattenborn. Citizen science plant observations encode global trait patterns. Nature Ecology & Evolution, (6)12:1850–1859, Springer Science and Business Media LLC, Oktober 2022. [PUMA: imported topic_earthenvironment] URL

David Montero, César Aybar, Chaonan Ji, Guido Kraemer, Maximilian Söchting, Khalil Teber, und Miguel D. Mahecha. On-Demand Earth System Data Cubes. IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 7529–7532, IEEE, Juli 2024. [PUMA: imported topic_earthenvironment] URL

Salim Soltani, Olga Ferlian, Nico Eisenhauer, Hannes Feilhauer, und Teja Kattenborn. From simple labels to semantic image segmentation: leveraging citizen science plant photographs for tree species mapping in drone imagery. Biogeosciences, (21)11:2909–2935, Copernicus GmbH, Juni 2024. [PUMA: imported topic_earthenvironment] URL

Karin Mora, Michael Rzanny, Jana Wäldchen, Hannes Feilhauer, Teja Kattenborn, Guido Kraemer, Patrick Mäder, Daria Svidzinska, Sophie Wolf, und Miguel D. Mahecha. Macrophenological dynamics from citizen science plant occurrence data. Methods in Ecology and Evolution, (15)8:1422–1437, Wiley, Juli 2024. [PUMA: imported topic_earthenvironment] URL