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https://github.com/GlacioHack/xdem

Analysis of digital elevation models (DEMs)
https://github.com/GlacioHack/xdem

coregistration dem digital-elevation-model error-analysis geostatistics gis python surface-elevation-data terrain-analysis uncertainty-quantification variogram

Last synced: 3 months ago
JSON representation

Analysis of digital elevation models (DEMs)

Host: GitHub
URL: https://github.com/GlacioHack/xdem
Owner: GlacioHack
License: mit
Created: 2020-11-11T22:43:21.000Z (over 4 years ago)
Default Branch: main
Last Pushed: 2024-11-15T23:19:44.000Z (3 months ago)
Last Synced: 2024-11-16T00:18:57.872Z (3 months ago)
Topics: coregistration, dem, digital-elevation-model, error-analysis, geostatistics, gis, python, surface-elevation-data, terrain-analysis, uncertainty-quantification, variogram
Language: Python
Homepage: https://xdem.readthedocs.io/
Size: 23.4 MB
Stars: 145
Watchers: 8
Forks: 41
Open Issues: 148
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE

Awesome Lists containing this project

cryosphere-links - xDEM - A Python module developed by glaciologists for handling DEMs: read/write, coregistration, volume change calculation etc. (Cryosphere - across all subspheres / Cryo Software)

README

        # xDEM: robust analysis of DEMs in Python.

[![Documentation Status](https://readthedocs.org/projects/xdem/badge/?version=latest)](https://xdem.readthedocs.io/en/latest/?badge=latest)

[![build](https://github.com/GlacioHack/xdem/actions/workflows/python-tests.yml/badge.svg)](https://github.com/GlacioHack/xdem/actions/workflows/python-tests.yml)

[![Conda Version](https://img.shields.io/conda/vn/conda-forge/xdem.svg)](https://anaconda.org/conda-forge/xdem)

[![Conda Platforms](https://img.shields.io/conda/pn/conda-forge/xdem.svg)](https://anaconda.org/conda-forge/xdem)

[![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/xdem.svg)](https://anaconda.org/conda-forge/xdem)

[![PyPI version](https://badge.fury.io/py/xdem.svg)](https://badge.fury.io/py/xdem)

[![Coverage Status](https://coveralls.io/repos/github/GlacioHack/xdem/badge.svg?branch=main)](https://coveralls.io/github/GlacioHack/xdem?branch=main)

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/GlacioHack/xdem/main)

[![Pre-Commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)

[![Formatted with black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/python/black)

[![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/)

[![Imports: isort](https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336)](https://pycqa.github.io/isort/)

**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](https://gdal.org/programs/gdaldem.html)). 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](https://scikit-gstat.readthedocs.io/en/latest/).

Additionally, xDEM inherits many convenient functionalities from [GeoUtils](https://github.com/GlacioHack/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](https://github.com/GlacioHack/geoutils), xDEM

relies on [Rasterio](https://github.com/rasterio/rasterio), [GeoPandas](https://github.com/geopandas/geopandas) and [Pyproj](https://github.com/pyproj4/pyproj)

for georeferenced calculations, and on [NumPy](https://github.com/numpy/numpy) and [Xarray](https://github.com/pydata/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](https://gdal.org/) command lines, or of your

[QGIS](https://www.qgis.org/en/site/) 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

```bash

mamba install -c conda-forge xdem

```

See [mamba's documentation](https://mamba.readthedocs.io/en/latest/) to install `mamba`, which will solve your environment much faster than `conda`.

## Citing methods implemented in the package

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

Citing xDEM: [![Zenodo](https://zenodo.org/badge/doi/10.5281/zenodo.4809697.svg)](https://zenodo.org/doi/10.5281/zenodo.4809697)

Citing the related study:

- **Coregistration**:

  - Horizontal shift from aspect/slope relationship of *[Nuth and Kääb (2011)](https://doi.org/10.5194/tc-5-271-2011)*,

  - Iterative closest point (ICP) of *[Besl and McKay (1992)](http://dx.doi.org/10.1109/34.121791)*,

- **Bias correction**:

  - Along-track multi-sinusoidal noise by basin-hopping of *[Girod et al. (2017)](https://doi.org/10.3390/rs9070704)*,

- **Uncertainty analysis**:

  - Heteroscedasticity and multi-range correlations from stable terrain of *[Hugonnet et al. (2022)](https://doi.org/10.1109/JSTARS.2022.3188922)*,

- **Terrain attributes**:

  - Slope, aspect and hillshade of either *[Horn (1981)](http://dx.doi.org/10.1109/PROC.1981.11918)* or *[Zevenbergen and Thorne (1987)](http://dx.doi.org/10.1002/esp.3290120107)*,

  - Profile, plan and maximum curvature of *[Zevenbergen and Thorne (1987)](http://dx.doi.org/10.1002/esp.3290120107)*,

  - Topographic position index of *[Weiss (2001)](http://www.jennessent.com/downloads/TPI-poster-TNC_18x22.pdf)*,

  - Terrain ruggedness index of either *[Riley et al. (1999)](http://download.osgeo.org/qgis/doc/reference-docs/Terrain_Ruggedness_Index.pdf)* or *[Wilson et al. (2007)](http://dx.doi.org/10.1080/01490410701295962)*,

  - Roughness of *[Dartnell (2000)](http://dx.doi.org/10.14358/PERS.70.9.1081)*,

  - Rugosity of *[Jenness (2004)](https://doi.org/10.2193/0091-7648(2004)032[0829:CLSAFD]2.0.CO;2)*,

  - Fractal roughness of *[Taud et Parrot (2005)](https://doi.org/10.4000/geomorphologie.622)*.

## 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](CONTRIBUTING.md).