geoextent
Python library for extracting geospatial extent of files and directories with multiple data formats. Read a notebook-based article about the library published at EarthCube 2021.
This project is developed as part of the DFG-funded research project Opening Reproducible Research (o2r, https://o2r.info).
Installation
System requirements
Python: 3.x
The package relies on common system libraries for reading geospatial datasets, such as GDAL and NetCDF. On Debian systems, the UbuntuGIS project offers easy installation of up to date versions of those libraries.
See the packages
list in travis.yml
for a full list of dependencies on Linux.
Install from PyPI
You must install a suitable version of pygdal
manually first, see instructions and this related SO thread with different helpful answers.
We use pygdal
for better compatibility with virtual environments.
pip install pygdal=="`gdal-config --version`.*"
pip install geoextent
Source installation
git clone https://github.com/o2r-project/geoextent
cd geoextent
pip install -r requirements.txt
pip install -e .
Use
Run
geoextent --help
to see usage instructions.
Showcases
To run the showcase notebooks, install JupyterLab or the classic Jupyter Notebook and then start a local server as shown below.
If your IDE has support for the Jupyter format, installing ipykernel
might be enough.
We recommend running the below commands in a virtual environment as described here.
The notebook must be trusted and python-markdown extension must be installed so that variables within Markdown text can be shown.
cd showcase
pip install -r requirements.txt
pip install -r showcase/requirements.txt
pip install -e .
jupyter trust showcase/SG_01_Exploring_Research_Data_Repositories_with_geoextent.ipynb
jupyter lab
Then open the local Jupyter Notebook server using the displayed link and open the notebook (*.ipynb
files) in the showcase/
directory.
Consult the documentation on paired notebooks based on Jupytext before editing selected notebooks.
Supported data formats
- GeoJSON (.geojson)
- Tabular data (.csv)
- Shapefile (.shp)
- GeoTIFF (.geotiff, .tif)
Contribute
All help is welcome: asking questions, providing documentation, testing, or even development.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
See CONTRIBUTING.md for details.
How to cite
Nüst, Daniel; Garzón, Sebastian and Qamaz, Yousef. (2021, May 14). o2r-project/geoextent (Version v0.7.1). Zenodo. https://zenodo.org/record/4762205
See also the CITATION.cff
and codemeta.json
files in this repository, which can possibly be imported in the reference manager of your choice.
License
geoextent
is licensed under MIT license, see file LICENSE.
Copyright (C) 2020 - o2r project.