PhD position: Multi-temporal forest canopy height reconstruction from satellite data

Process and analyse large archives of optical stereo satellite imagery. • Develop and improve photogrammetric workflows for DSM and CHM generation. • Generate and validate multi-temporal canopy height models. • Analyse long-term forest structural dynamics and disturbance processes. • Publish research results in peer-reviewed journals and present them at international conferences. • Contribute to teaching activities within the Department of Geography.

You hold a MSc degree in photogrammetry, remote sensing, geomatics, geodesy, physical geography, environmental sciences, computer science, geoinformatics, aero/astro engineering, or a related discipline. Experience or strong interest in at least one of the following: Satellite or airborne remote sensing data processing/analysis • Stereo photogrammetry and/or SfM software (open-source or commercial) • Very-high-resolution commercial satellite image processing and/or analysis • Airborne LiDAR, and/or spaceborne laser altimetry (GEDI, ICESat-2) analysis • Geospatial data processing • Scientific programming (Python, R, Julia, or Matlab) Other relevant, but optional experience (ideally one or more): Point cloud processing and/or analysis • Computer vision and/or machine learning involving geospatial data • Forest science • Linux, Git/Github, Jupyter, Cloud computing • Open-source geospatial stack (e.g., GDAL, PDAL, GeoPandas, xarray) • Excellent written and oral communication skills (publication or other technical writing, conference poster or talk) We offer A fully funded 4-year PhD position. • Access to unique international remote sensing datasets. • Project collaboration with leading forest and remote sensing researchers across Europe (such as WSL, TU Wien, NIBIO, and IGE Grenoble) and Canada (Canadian Forest Service). • Excellent research infrastructure and computational resources. • A stimulating and supportive research environment at the University of Zurich. • Opportunity to collaborate with both remote sensing and machine learning research groups at the University of Zurich.