Publications

Daniel Mederer, Hannes Feilhauer, Eya Cherif, Katja Berger, Tobias B. Hank, Kyle R. Kovach, Phuong D. Dao, Bing Lu, Philip A. Townsend, and 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, December 2024. [PUMA: topic_earthenvironment xack yaff] URL

Sina Mehrdad, Dörthe Handorf, Ines Höschel, Khalil Karami, Johannes Quaas, Sudhakar Dipu, and Christoph Jacobi. Arctic climate response to European radiative forcing: a deep learning study on circulation pattern changes. Weather and Climate Dynamics, (5)4:1223-1268, Copernicus Publications, 2024. [PUMA: topic_earthenvironment yaff]

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

Jessenia Gonzalez, Sudhakar Dipu, Odran Sourdeval, Alexandre Siméon, Gustau Camps-Valls, and 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 yaff]

Olivier C. Pasche, Jonathan Wider, Zhongwei Zhang, Jakob Zscheischler, and 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 xack yaff] URL

Taís Maria Nunes Carvalho, Francisco de Assis de Souza Filho, and Mariana Madruga de Brito. Water management assessment with text mining. EGU General Assembly Conference Abstracts, EGU-8349, 2023. [PUMA: Zno topic_earthenvironment]

Sina Mehrdad, Dörthe Handorf, Ines Höschel, Khalil Karami, Johannes Quaas, Sudhakar Dipu, and Christoph Jacobi. Arctic Climate Response to European Radiative Forcing: A Deep Learning Approach. EGUsphere, (2024):1-55, Copernicus Publications, 2024. [PUMA: Yaff topic_earthenvironment]

Chaonan Ji, Tonio Fincke, Vitus Benson, Gustau Camps-Valls, Miguel-Ángel Fernández-Torres, Fabian Gans, Guido Kraemer, Francesco Martinuzzi, David Montero, Karin Mora, Oscar J. Pellicer-Valero, Claire Robin, Maximilian Söchting, Mélanie Weynants, and Miguel D. Mahecha. DeepExtremeCubes: Earth system spatio-temporal data for assessing compound heatwave and drought impacts. Scientific Data, (12)1:149, Jan 25, 2025. [PUMA: Yaff topic_earthenvironment] URL

Florian Knutzen, Paul Averbeck, Caterina Barrasso, Laurens M. Bouwer, Barry Gardiner, José M. Grünzweig, Sabine Hänel, Karsten Haustein, Marius Rohde Johannessen, Stefan Kollet, Joni-Pekka Pietikaeinen, Karolina Pietras-Couffignal, Joaquim G. Pinto, Diana Rechid, Efi Rousi, Ana Russo, Laura Suarez-Gutierrez, Julian Wendler, Elena Xoplaki, and Daniel Gliksman. Impacts and damages of the European multi-year drought and heat event 2018–2022 on forests, a review. Jul 26, 2023. [PUMA: FIS_scads imported topic_earthenvironment yaff]

Caterina Barrasso, Robert Krüger, Anette Eltner, and Anna F. Cord. Mapping indicator species of segetal flora for result-based payments in arable land using UAV imagery and deep learning. Ecological indicators, (169)Elsevier Science B.V., December 2024. [PUMA: FIS_scads imported topic_earthenvironment xack yaff]

S. Mehrdad, D. Handorf, I. Höschel, K. Karami, J. Quaas, S. Dipu, and C. Jacobi. Arctic Climate Response to European Radiative Forcing: A Deep Learning Approach. EGUsphere, (2024):1--55, 2024. [PUMA: Yaff topic_earthenvironment] URL

Maria Novitasari, Johannes Quaas, and Miguel Rodrigues. ALAS: Active Learning for Autoconversion Rates Prediction from Satellite Data. NeurIPS 2023 AI for Science Workshop, 2023. [PUMA: topic_earthenvironment imported] URL

J. Lenhardt, J. Quaas, and D. Sejdinovic. Marine cloud base height retrieval from MODIS cloud properties using machine learning. Atmospheric Measurement Techniques, to appear, 2024. [PUMA: topic_earthenvironment imported] URL

Maria C Novitasari, Johannes Quaas, and Miguel Rodrigues. Unleashing the Autoconversion Rates Forecasting: Evidential Regression from Satellite Data. NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning, 2023. [PUMA: topic_earthenvironment imported] URL

Francesco Martinuzzi, Chris Rackauckas, Anas Abdelrehim, Miguel D Mahecha, and Karin Mora. ReservoirComputing.Jl: An efficient and modular library for reservoir computing models. arXiv, 2022. [PUMA: topic_earthenvironment]

Jordi Cortés-Andrés, Gustau Camps-Valls, Sebastian Sippel, Enikő Székely, Dino Sejdinovic, Emiliano Diaz, Adrián Pérez-Suay, Zhu Li, Miguel Mahecha, and Markus Reichstein. Physics-aware nonparametric regression models for Earth data analysis. Environ. Res. Lett., (17)5:054034, IOP Publishing, May 2022. [PUMA: topic_earthenvironment]

Teja Kattenborn, Ronny Richter, Claudia Guimarães-Steinicke, Hannes Feilhauer, and Christian Wirth. AngleCam : Predicting the temporal variation of leaf angle distributions from image series with deep learning. Methods Ecol. Evol., (13)11:2531--2545, Wiley, November 2022. [PUMA: topic_earthenvironment]

Teja Kattenborn, Felix Schiefer, Julian Frey, Hannes Feilhauer, Miguel D Mahecha, and Carsten F Dormann. Spatially autocorrelated training and validation samples inflate performance assessment of convolutional neural networks. ISPRS Open Journal of Photogrammetry and Remote Sensing, (5)100018:100018, Elsevier BV, August 2022. [PUMA: topic_earthenvironment]

Maximilian Lange, Hannes Feilhauer, Ingolf Kühn, and Daniel Doktor. Mapping land-use intensity of grasslands in Germany with machine learning and Sentinel-2 time series. Remote Sens. Environ., (277)112888:112888, Elsevier BV, August 2022. [PUMA: topic_earthenvironment]

Eya Cherif, Maximilian Hell, and Melanie Brandmeier. DeepForest: Novel deep learning models for land use and land cover classification using multi-temporal and -modal Sentinel data of the Amazon basin. Remote Sens. (Basel), (14)19:5000, MDPI AG, October 2022. [PUMA: topic_earthenvironment]