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this centre, we are opening a PhD position on remote sensing of mountain forest dynamics. The Technical University of Munich (TUM) is one of the leading universities globally. At the TUM School of Life Sciences
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are experience with Landsat-8 satellite data, bathymetry and other remote sensing data. Scope of responsibility: Integrate existing acoustic data collected by NOAA and CCOM/JHC, derived terrain variables and
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that are derived from novel ground-based atmospheric remote sensing profile observations. Heat risks to human health and mortality are exacerbated in urban areas, where heat waves are more intense and last longer
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such as case weighting, anomaly detection, and model-based prediction (e.g., geostatistics and machine learning), using auxiliary geospatial or remotely sensed data. Quantifying uncertainty and correcting
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species, and the emergence of previously unseen classes. Recent advances in remote sensing and machine learning provide new opportunities to address these challenges, but most current approaches
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processes, remote sensing observations, and prediction and valuation of forest functions, providing a holistic view on forests as complex systems. See the project website to find out more about the FORFUS
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geospatial or remotely sensed data. Quantifying uncertainty and correcting for spatial and sampling biases inherent in environmental observation systems. Target environmental properties such as above ground
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, remote sensing observations, and prediction and valuation of forest functions, providing a holistic view on forests as complex systems. See the project website to find out more about the FORFUS doctoral
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processes, remote sensing observations, and prediction and valuation of forest functions, providing a holistic view on forests as complex systems. See the project website to find out more about the FORFUS
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | 7 days ago
) approaches, off-the-shelf solutions cannot be employed given the vast diversity of microbial communities and the limitations in the number of observations from remote deep-sea sites. In this project, you will