xDEM: robust analysis of DEMs in Python.

xDEM is an open source project to develop a core Python package for the analysis of digital elevation models (DEMs).

It aims at providing modular and robust tools for the most common analyses needed with DEMs, including both geospatial operations specific to DEMs and a wide range of 3D alignment and correction methods from published, peer-reviewed studies. The core manipulation of DEMs (e.g., vertical alignment, terrain analysis) are conveniently centered around a DEM class (that, notably, re-implements all tools of gdalDEM). More complex pipelines (e.g., 3D rigid coregistration, bias corrections, filtering) are built around modular Coreg, BiasCorr classes that easily interface between themselves. Finally, xDEM includes advanced uncertainty analysis tools based on spatial statistics of SciKit-GStat.

Additionally, xDEM inherits many convenient functionalities from GeoUtils such as implicit loading, numerical interfacing and convenient object-based geospatial methods to easily perform the most common higher-level tasks needed by geospatial users (e.g., reprojection, cropping, vector masking). Through GeoUtils, xDEM relies on Rasterio, GeoPandas and Pyproj for georeferenced calculations, and on NumPy and Xarray for numerical analysis. It allows easy access to the functionalities of these packages through interfacing or composition, and quick inter-operability through object conversion.

If you are looking for an accessible Python package to write the Python equivalent of your GDAL command lines, or of your QGIS analysis pipeline without a steep learning curve on Python GIS syntax, xDEM is perfect for you! For more advanced users, xDEM also aims at being efficient and scalable by supporting lazy loading and parallel computing (ongoing).

Documentation

For a quick start, full feature description or search through the API, see xDEM's documentation at: https://xdem.readthedocs.io.

Installation

With mamba

mamba install -c conda-forge xdem

See mamba's documentation to install mamba, which will solve your environment much faster than conda.

With pip

pip install xdem

Citing methods implemented in the package

When using a method implemented in xDEM, please cite both the package and the related study:

Citing xDEM:

Citing the related study:

• Coregistration:
  • Horizontal shift from aspect/slope relationship of Nuth and Kääb (2011),
  • Iterative closest point (ICP) of Besl and McKay (1992),
• Bias correction:
  • Along-track multi-sinusoidal noise by basin-hopping of Girod et al. (2017),
• Uncertainty analysis:
  • Heteroscedasticity and multi-range correlations from stable terrain of Hugonnet et al. (2022),
• Terrain attributes:
  • Slope, aspect and hillshade of either Horn (1981) or Zevenbergen and Thorne (1987),
  • Profile, plan and maximum curvature of Zevenbergen and Thorne (1987),
  • Topographic position index of Weiss (2001),
  • Terrain ruggedness index of either Riley et al. (1999) or Wilson et al. (2007),
  • Roughness of Dartnell (2000),
  • Rugosity of Jenness (2004),
  • Fractal roughness of Taud et Parrot (2005).

Contributing

We welcome new contributions, and will happily help you integrate your own DEM routines into xDEM!

After discussing a new feature or bug fix in an issue, you can open a PR to xDEM with the following steps:

1. Fork the repository, make a feature branch and push changes.
2. When ready, submit a pull request from the feature branch of your fork to GlacioHack/xdem:main.
3. The PR will be reviewed by at least one maintainer, discussed, then merged.

More details on our contributing page.