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(credits)= | ||
# Credits and background | ||
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```{toctree} | ||
:maxdepth: 2 | ||
history | ||
mission | ||
authors | ||
funding | ||
license | ||
``` |
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(funding)= | ||
## Funding acknowledgments | ||
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Members of the lead development team acknowledge funding from: | ||
- SNSF grant no. 184634, a MeteoSwiss [GCOS](https://gcos.wmo.int/en/home) project on elevation data analysis for glaciology, | ||
- NASA award 80NSSC22K1094, an [STV](https://science.nasa.gov/earth-science/decadal-surveys/decadal-stv/) project on the fusion of elevation data, | ||
- NASA award 80NSSC23K0192, an [ICESat-2](https://icesat-2.gsfc.nasa.gov/) project on the processing of elevation data in the cloud, | ||
- CNES (French Space Agency) award on merging [demcompare](https://github.com/CNES/demcompare) and xDEM while further developing related 3D tools. | ||
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::::{grid} | ||
:reverse: | ||
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:::{grid-item} | ||
:columns: 4 | ||
:child-align: center | ||
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```{image} ./_static/nasa_logo.svg | ||
:width: 200px | ||
:class: dark-light | ||
``` | ||
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::: | ||
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:::{grid-item} | ||
:columns: 4 | ||
:child-align: center | ||
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```{image} ./_static/snsf_logo.svg | ||
:width: 220px | ||
:class: only-light | ||
``` | ||
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```{image} ./_static/snsf_logo_dark.svg | ||
:width: 220px | ||
:class: only-dark | ||
``` | ||
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::: | ||
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:::{grid-item} | ||
:columns: 4 | ||
:child-align: center | ||
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```{image} ./_static/cnes_logo.svg | ||
:width: 200px | ||
:class: only-light | ||
``` | ||
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```{image} ./_static/cnes_logo_dark.svg | ||
:width: 200px | ||
:class: only-dark | ||
``` | ||
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::: | ||
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:::: |
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(history)= | ||
# History | ||
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Below, some more information on the history behind the package. | ||
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## Creation | ||
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```{margin} | ||
<sup>1</sup>More on our GlacioHack founder at [adehecq.github.io](https://adehecq.github.io/). | ||
``` | ||
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xDEM was created during the **[GlacioHack](https://github.com/GlacioHack) hackathon**, that was initiated by | ||
Amaury Dehecq<sup>1</sup> and took place online on November 8, 2020. | ||
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```{margin} | ||
<sup>2</sup>Check-out [glaciology.ch](https://glaciology.ch) on our founding group of VAW glaciology! | ||
``` | ||
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The initial core development of xDEM was performed by members of the Glaciology group of the Laboratory of Hydraulics, Hydrology and | ||
Glaciology (VAW) at ETH Zürich<sup>2</sup>, with contributions by members of the University of Oslo, the University of Washington, and University | ||
Grenoble Alpes. | ||
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## Joining effort with **demcompare** | ||
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In 2024, xDEM and [demcompare](https://github.com/CNES/demcompare) joined efforts in the perspective of | ||
merging the best of both packages into one, and to jointly continue the development of new features for | ||
analyzing elevation data with a larger expertise pool. | ||
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[demcompare](https://github.com/CNES/demcompare) is a tool developed by the CNES (French Space Agency) to | ||
support its 3D satellite missions in analyzing elevation data, for instance from stereophotogrammetric DEMs | ||
that can be generated with [CARS](https://github.com/CNES/cars). | ||
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## Current team | ||
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```{margin} | ||
<sup>3</sup>More on CNES's 3D missions on the [CO3D constellation page](https://cnes.fr/en/projects/co3d). | ||
``` | ||
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The current lead development team includes **researchers in Earth observation and engineers from | ||
[CNES](https://cnes.fr/en)** (French Space Agency). We specialize in elevation data analysis, for application in Earth | ||
science or for operational use for 3D satellite missions<sup>3</sup>. | ||
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Other volunteer contributors span diverse scientific backgrounds in industry or research. We welcome | ||
any new contributors! See how to contribute on [the dedicated page of our repository](https://github.com/GlacioHack/xdem/blob/main/CONTRIBUTING.md). |
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:maxdepth: 2 | ||
publis | ||
background | ||
authors | ||
license | ||
credits | ||
``` | ||
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# Indices and tables | ||
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(mission)= | ||
## Mission | ||
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```{epigraph} | ||
The core mission of xDEM is to be **easy-of-use**, **modular** and **robust**. | ||
It also attempts to be as **efficient**, **scalable** and **state-of-the-art** as possible. | ||
Finally, as an open source package, it aspires to foster **reproducibility** and **open science**. | ||
``` | ||
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In details, those mean: | ||
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- **Ease-of-use:** all basic operations or methods from published works should only require a few lines of code to be performed; | ||
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- **Modularity:** all methods should be fully customizable, to allow both flexibility and inter-comparison; | ||
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- **Robustness:** all methods should be tested within our continuous integration test-suite, to enforce that they always perform as expected; | ||
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```{note} | ||
:class: margin | ||
**Scalability** is currently being improved towards a first major release ``v1.0``. | ||
``` | ||
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And, additionally: | ||
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- **Efficiency**: all methods should be optimized at the lower-level, to function with the highest performance offered by Python packages; | ||
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- **Scalability**: all methods should support both lazy processing and distributed parallelized processing, to work with high-resolution data on local machines as well as on HPCs; | ||
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- **State-of-the-art**: all methods should be at the cutting edge of remote sensing science, to provide users with the most reliable and up-to-date tools. | ||
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And finally: | ||
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- **Reproducibility:** all code should be version-controlled and release-based, to ensure consistency of dependent | ||
packages and works; | ||
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- **Open-source:** all code should be accessible and reusable to anyone in the community, for transparency and open governance. |