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Department of Geography Remote Sensing Spectroscopy

TIRLab - Thermal Infrared Remote Sensing

The TIRLab of the Department of Geography at the University of Zurich is engaged in research and teaching in the field of thermal infrared (TIR) remote sensing. Our research is tailored to different spheres and scales, and is based on a diverse approach of experimental, field, and modelling studies using a wide range of tools and datasets. Our teaching ranges from the physical fundamentals to applications of pressing environmental and societal issues arising from global atmospheric change. In addition to lectures, we promote understanding of TIR data through hands-on exercises and student projects, and are open to theses that exploit the potential of TIR remote sensing across scales and spheres.

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News

  • New paper published!

    Jennifer Susan Adams and Kathrin Naegeli's paper on "Across-scale thermal infrared anisotropy in forests: Insights from a multi-angular laboratory-based approach" was just published in Remote Sensing of Environment. The study investigated thermal infrared angular effects in forests using a novel method of contructing mini-canopies in the footprint of a laboratory goniometer. The publication is available at this link

  • New paper published!

    Nils Rietze's second PhD paper "Pre-Fire Vegetation Conditions and Topography Shape Burn Mosaics of Siberian Tundra Fire Scars" was recently published in JGR Biogeosciences. Using a combination of very high-resolution (PlanetScope) and medium resolution (Landsat) imagery, the study revealed heterogeneous burn patterns and how pre-fire vegetation conditions influenced the heterogeneity of the burning. You can find the study here: link

  • New paper published!

    Jennifer Susan Adams co-authored a paper entitled "Predictions of failed satellite retrieval of air quality using machine learning" where they apply machine learning methods to forecast trace-gas retrieval failures using only raw satellite radiances, including thermal infrared, thereby streamlining the generation of high-quality data. The publication is available at this link.