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Determine real-time glacier mass changes from camera images
Glacier melt plays and important role in the hydrological budget, especially during the hot summer months. You will set up a framework to analyze real-time melt observed by on-ice cameras.
Keywords: Glaciology, image analysis, programming
In the CRAMPON project (Cryospheric Monitoring and Prediction Online) we develop an operational modeling tool to nowcast and predict mass balance and runoff of Swiss glaciers. As field data for calibration are sparse, we intend to assimilate observations from different sources into the workflow. This Master's thesis will help to tie the model ensemble closer to in situ conditions by analyzing glacier melt from camera images.
In the CRAMPON project (Cryospheric Monitoring and Prediction Online) we develop an operational modeling tool to nowcast and predict mass balance and runoff of Swiss glaciers. As field data for calibration are sparse, we intend to assimilate observations from different sources into the workflow. This Master's thesis will help to tie the model ensemble closer to in situ conditions by analyzing glacier melt from camera images.
The goal of this Master’s Thesis is to set up a framework that is able to operationally digest incoming images by turning the image information into a mass change information. The framework should also be able to assess the uncertainty of the automated reading. Validation of the results shall be done with expert-based readings and possibly other in-situ measurements. The entire processing line shall lead to an operationally applicable workflow.
The project shall be coded in the Open Source language Python. Ideally, the candidate has experiences in using optical remote sensing techniques, scientific programming and /or Git. Strong ambitions to establish the required skills are a must.
The goal of this Master’s Thesis is to set up a framework that is able to operationally digest incoming images by turning the image information into a mass change information. The framework should also be able to assess the uncertainty of the automated reading. Validation of the results shall be done with expert-based readings and possibly other in-situ measurements. The entire processing line shall lead to an operationally applicable workflow. The project shall be coded in the Open Source language Python. Ideally, the candidate has experiences in using optical remote sensing techniques, scientific programming and /or Git. Strong ambitions to establish the required skills are a must.
For further information please contact Prof. Daniel Farinotti (daniel.farinotti@ethz.ch) or Johannes Landmann (landmann@vaw.baug.ethz.ch)
For further information please contact Prof. Daniel Farinotti (daniel.farinotti@ethz.ch) or Johannes Landmann (landmann@vaw.baug.ethz.ch)