Spielmeyer, A.; Gebser, B.; Pohnert, G.: Investigations of the uptake of dimethylsulfoniopropionate by phytoplankton. Chembiochem 12 (15), pp. 2276 - 2279 (2011)

Mügler, I.; Gleixner, G.; Günther, F.; Mäusbacher, R.; Daut, G.; Schutt, B.; Berking, J.; Schwalb, A.; Schwark, L.; Xu, B. et al.; Yao, T.; Zhu, L.; Yi, C.: A multi-proxy approach to reconstruct hydrological changes and Holocene climate development of Nam Co, Central Tibet. Journal of Paleolimnology 43 (4), pp. 625 - 648 (2010)

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)

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, pp. 24 - 36 (Eds. Camps-Valls, G.; Tuia, D.; Zhu, X. X.; Reichstein, M.). John Wiley & Sons Ltd, Hoboken, New Jersey (2021)

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, pp. 186 - 203 (Eds. Camps-Valls, G.; Tuia, D.; Zhu, X. X.; Reichstein, M.). John Wiley & Sons Ltd, Hoboken, New Jersey (2021)

Blohm, A.; Sieburg, A.; Popp, J.; Frosch, T.: Detection of gas molecules by means of spectrometric and spectroscopic methods. In: Advanced Nanostructures for Environmental Health, pp. 251 - 294 (Eds. Baia, L.; Pap, Z.; Hernadi, K.; Baia, M.). Elsevier, Amsterdam (2020)

Mahecha, M. D.; Guha-Sapir, D.; Smits, J.; Gans, F.; Kraemer, G.: Data challenges limit our global understanding of humanitarian disasters triggered by climate extremes. In: Climate Extremes and Their Implications for Impact and Risk Assessment, pp. 243 - 256 (Eds. Sillmann, J.; Sippel, S.; Russo, S.). Elsevier, Amsterdam (2019)

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)

Lange, H.; Boese, S.: Recurrence quantification and recurrence network analysis of global photosynthetic activity. In: Recurrence Quantification Analysis: Theory and Best Practices, pp. 349 - 374 (Eds. Webber, C. L.; Marwan, N.). Springer, Cham [u.a.] (2014)

Silva, R. P.; Souza, C. A. S.; Amaral, M. R. M.; Carneiro, V. M.; Barros, P. C.; Marra, D. M.; Santos, J.; Higuchi, N.: Árvore: crescimento, desenvolvimento e sua identificação. In: A floresta amazônica e suas múltiplas dimensões: uma proposta de educação ambiental. 2ed. (Eds. Higuchi, M. I. G.; Higuchi, N.). Manaus, Brasil (2012)

Benson, V.; Robin, C.; Requena Mesa, C.; Alonso, L.; Carvalhais, N.; Cortés, J.; Gao, Z.; Linscheid, N.; Weynants, M.; Reichstein, M.: Multi-modal learning for geospatial vegetation forecasting. In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle , June 17, 2024 - June 21, 2024. (2024)

Heinze, B.; Schwab, V. F.; Küsel, K.; Schloemer, S.; Roskam, A.; Xu, X.; Trumbore, S. E.: Microbial methane oxidation in groundwater ecosystems. In: Conference: International Symposium of CRC 1076 AquaDiva. Conference: International Symposium of CRC 1076 AquaDiva, Jena, Germany, June 06, 2024 - June 07, 2024. (2024)

Hellwig, F. M.; Jagdhuber, T.; Fluhrer, A.; Dubois, C.; Chaparro, D.; Schellenberg, K.; Piles, M.; Schmullius, C.; Entekhabi, D.: Multi-frequency radiometry for multi-year monitoring of relative water content in a temperate forest. In: IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, pp. 2739 - 2742. IGARSS 2023, Pasadena, CA, USA , July 16, 2023 - July 21, 2023. (2023)

Jagdhuber, T.; Fluhrer, A.; Chaparro, D.; Dubois, C.; Hellwig, F. M.; Bayat, B.; Montzka, C.; Baur, M. J.; Ramati, M.; Kübert, A. et al.; Mueller, M. M.; Schellenberg, K.; Boehm, M.; Jonard, F.; Steele-Dunne, S.; Piles, M.; Entekhabi, D.: On the potential of active and passive microwave remote sensing for tracking seasonal dynamics of evapotranspiration. In: IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, pp. 2610 - 2613. IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, July 16, 2023 - July 21, 2023. IEEE (2023)

Urban, M.; Hirner, A.; Ziemer, J.; Mueller, M. M.; Gessner, U.; Baade, J.; Mogonong, B.; Morgenthal, T.; Feig, G.; Ramoelo, A. et al.; Heckel, K.; Nghiyalwa, H. S.; Schmullius, C.: Sentinel-1 and Sentinel-2 time series breakpoint detection as part of the south African land degradation monitor (SALDI). In: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, pp. 1997 - 2000. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium , July 11, 2021 - July 16, 2021. IEEE, Brüssel, Belgien (2021)

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 , June 19, 2021 - June 25, 2021. IEEE, Nashville, TN, USA (2021)

Adsuara, J. E.; Perez-Suay, A.; Moreno-Martınez, A.; Camps-Valls, G.; Kraemer, G.; Reichstein, M.; Mahecha, M. D.: Discovering differential equations from earth observation data. In: IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, pp. 3999 - 4002. IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, September 26, 2020 - October 02, 2020. IEEE (2021)

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)

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)

Guanche Garcia, Y.; Rodner, E.; Flach, M.; Sippel, S.; Mahecha, M. D.; Denzler, J.: Detecting multivariate biosphere extremes. In: Proceedings of the 6th International Workshop on Climate Informatics: CI2016: NCAR Technical Note NCAR/TN-529+PROC, pp. 9 - 12 (Eds. Banerjee, A.; Ding, W.; Dy, V.). Climate Informatics Workshop 2016, Colorado (USA), September 22, 2016 - September 23, 2016. National Center for Atmospheric Research, Boulder (2016)