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Vehicle-based photogrammetry system for avalanche detection
Traditionally, field observers collect images in avalanche-affected or -prone regions, and these images are returned to SLF for semi-automated or manual processing. In prior work, an automatic car-mounted camera system was developed at SLF that would allow a user to specify locations for taking imag
In Switzerland, snow avalanches cause more casualties than any other natural hazard. The main source of information on avalanche hazard in Switzerland for authorities, safety personnel of ski resorts and traffic lines, as well as the public, is the avalanche bulletin of the WSL Institute for Snow and Avalanche Research SLF. The avalanche bulletin is compiled by experienced avalanche forecasters based on data gathered from automated weather stations and observers in the field. Traditionally, field observers collect images in avalanche-affected or -prone regions, and these images are returned to SLF for semi-automated or manual processing. In prior work, an automatic car-mounted camera system was developed at SLF that would allow a user to specify locations for taking images during one pass through an area, and then automatically capture images at the same locations and camera orientations (using a custom built-in pan-tilt system and GNSS) during repeat visits. The goal of this project is to extend the existing system to allow for higher-frequency image-gathering with highly-accurate location tags that would allow for photogrammetric reconstruction. Such a reconstruction would generate a 3D mesh of the terrain as well as geo-referenced orthomosaics, and would allow for more automated processing (such as snow depth estimation and avalanche detection).
In Switzerland, snow avalanches cause more casualties than any other natural hazard. The main source of information on avalanche hazard in Switzerland for authorities, safety personnel of ski resorts and traffic lines, as well as the public, is the avalanche bulletin of the WSL Institute for Snow and Avalanche Research SLF. The avalanche bulletin is compiled by experienced avalanche forecasters based on data gathered from automated weather stations and observers in the field. Traditionally, field observers collect images in avalanche-affected or -prone regions, and these images are returned to SLF for semi-automated or manual processing. In prior work, an automatic car-mounted camera system was developed at SLF that would allow a user to specify locations for taking images during one pass through an area, and then automatically capture images at the same locations and camera orientations (using a custom built-in pan-tilt system and GNSS) during repeat visits. The goal of this project is to extend the existing system to allow for higher-frequency image-gathering with highly-accurate location tags that would allow for photogrammetric reconstruction. Such a reconstruction would generate a 3D mesh of the terrain as well as geo-referenced orthomosaics, and would allow for more automated processing (such as snow depth estimation and avalanche detection).
- Determination of the timing and spatial localisation accuracy required for ground-based photogrammetric reconstruction using commercial software such as Pix4D or Agisoft
- Development of a time-synchronised localisation system that would allow for high-accuracy post-processed kinematic (PPK) GNSS position estimation, and accurate triggering of a camera
- Software development for selecting suitable camera poses (position and orientation) to take photos, potentially from a moving vehicle, for accurate photogrammetry
- Data collection and demonstration of the final system
- Determination of the timing and spatial localisation accuracy required for ground-based photogrammetric reconstruction using commercial software such as Pix4D or Agisoft - Development of a time-synchronised localisation system that would allow for high-accuracy post-processed kinematic (PPK) GNSS position estimation, and accurate triggering of a camera - Software development for selecting suitable camera poses (position and orientation) to take photos, potentially from a moving vehicle, for accurate photogrammetry - Data collection and demonstration of the final system
- Physical prototyping skills for building up the system (3D printing, servos, etc.)
- Basic electronics experience (experience with Arduino, Pixhawk, GNSS, etc. would be beneficial)
- Programming experience (C/C++, Python)
Interest in snow research
- Physical prototyping skills for building up the system (3D printing, servos, etc.) - Basic electronics experience (experience with Arduino, Pixhawk, GNSS, etc. would be beneficial) - Programming experience (C/C++, Python) Interest in snow research