xDEM - A python library for reproducible DEM analysis and geodetic volume change calculations

Crunching satellite imagery or Digital Elevation Models (DEMs) is part of your weekly routine?

You are desperate to calculate glacier volume changes despite gappy observations?

Your head blows up just trying to provide those errors bars for your mass balance estimates?

You think science should be fully reproducible?

Python is one of your favourite programming languages?

If you answered yes to any two of those questions, you should definitely attend this presentation!

 

Remote sensing is becoming increasingly important in our understanding of global glacier changes. Dozens of studies each year aim at estimating geodetic glacier mass balance from the regional to the global scale, providing factual numbers behind glacier retreat. But how reliable are those numbers? Current approaches raise several problems:

• External data, such as glacier outlines can be updated regularly, as is done e.g. with the RGI outlines, potentially making previous estimates obsolete.
• Data processing techniques, such as DEM coregistration or gap-filling, evolve over time in the community.
• Many results are not reproducible or cannot even be updated, because access to the data or code is not granted.

All these issues make the comparison and validation of older vs newer studies challenging and questions the reliability of glacier change estimates. Why not team-up and create the tools we all dream of?

 

Here we present xDEM, an open-source, community-built and easy-to-use set of tools for DEMs postprocessing and volume change calculation. The tool is designed as a set of Python modules, built on top of popular libraries (rasterio, geopandas, GDAL). It will ultimately provide all that is needed to turn individual raw DEMs into a geodetic volume change and its uncertainties: coregistration, bias correction, gap-filling, volume change calculation and spatial statistics (e.g. variograms). The concept behind xDEM is:

Ease of use: Python modules developed by glaciologists, (mostly) for glaciologists.

Flexibility and modularity: We offer a set of options, rather than favouring a single method and make it straightforward to combine them.

Reproducibility: Version-controlled; releases saved with DOI; test-based development ensures our code always performs as expected.

The progress of the project can be followed at https://github.com/GlacioHack/xdem.

 

We illustrate the use of xDEM for various test cases and on-going projects to post-process DEMs obtained from ~1930 terrestrial images of the Swiss Alps, American reconnaissance KH-9 satellite images, modern ASTER and Pleiades images or the recent RAGMAC intercomparison experiment.