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Staff

Dr. rer. nat. Marlon Nuske

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Publications

PREDICTING CROP YIELD WITH MACHINE LEARNING: AN EXTENSIVE ANALYSIS OF INPUT MODALITIES AND MODELS ON A FIELD AND SUB-FIELD LEVEL

Deepak Kumar Pathak; Miro Miranda Lorenz; Francisco Mena; Cristhian Sanchez; Patrick Helber; Benjamin Bischke; Peter Habelitz; Hiba Najjar; Jayanth Siddamsetty; Diego Arenas; Michaela Vollmer; Marcela Charfuelan Oliva; Marlon Nuske; Andreas Dengel

In: 2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE International Geoscience and Remote Sensing Symposium (IGARSS-2023), WE4.R8: Agricultural Yield Estimation and Prediction I, July 16-21, Pasadena, California, USA, IEEE, 10/2023.

To the publication

INFLUENCE OF DATA CLEANING TECHNIQUES ON SUB-FIELD YIELD PREDICTIONS

Cristhian Sanchez; Deepak Kumar Pathak; Miro Miranda Lorenz; Marcela Charfuelan Oliva; Patrick Helber; Marlon Nuske; Benjamin Bischke; Peter Habelitz; Nafisur Rahman; Francisco Mena; Hiba Najjar; Jayanth Siddamsetty; Diego Arenas; Michaela Vollmer; Andreas Dengel

In: 2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE International Geoscience and Remote Sensing Symposium (IGARSS-2023), TU3.R3: Spatio-temporal Data Harmonization I, July 16-21, Pasadena, California, USA, IEEE, 10/2023.

To the publication

Crop Yield Prediction: an Operational Approach to Crop Yield Modeling on Field and Sub-Field Level with Machine Learning Models

Patrick Helber; Benjamin Bischke; Peter Habelitz; Cristhian Sanchez; Deepak Kumar Pathak; Miro Miranda Lorenz; Hiba Najjar; Francisco Mena; Jayanth Siddamsetty; Diego Arenas; Michaela Vollmer; Marcela Charfuelan Oliva; Marlon Nuske; Andreas Dengel

In: 2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE International Geoscience and Remote Sensing Symposium (IGARSS-2023), July 16-21, Pasadena, CA, USA, IEEE, 10/2023.

To the publication
All publications

Profile

  • Rwanda_Weather_events

    Rwanda Extreme Weather Events

    In close collaboration with the Rwanda Space Agency, we develop machine learning tools to understand and monitor extreme weather events. We specifically focus on the use of remote sensing data for…

  • ML4Sim

    Machine Learning for Simulation Intelligence in Composite Process Design

    Fiber-reinforced polymers are composite materials made of fibers and a surrounding matrix. Due to their outstanding lightweight potential, they are applied in numerous areas of everyday life, from…

  • AI4DTE

    Artificial Intelligence (AI) Enhanced Earth Observation (EO) for on Digital Twin Earth (DTE)

    A digital twin of the earth will allow science and policy users alike to gain insights of our earth system and will help with decision support. We analyze the potential of artificial intelligence…

  • AI4EO Solution Factory

    Artificial Intelligence for Earth Observation Solution Factory

    Within the AI4EO Solution Factory we combine our AI expertise with EO data to develop customized state-of-the-art solutions for business cases as diverse as agriculture, urban planning disaster…

    AI4EO Solution Factory

  • ML4SCA

    Machine Learning for Satellite Collision Avoidance

    With an increasing number of satellites and debris objects in earth orbit it becomes increasingly important to automate and improve procedures for collision avoidance. We develop machine learning…