Contents

Geospatial Libraries

This page lists open-source packages for geospatial file manipulation with Python. The necessary packages are already installed if you use the provided `hypy <hypy_install.html#create-and -install-conda-environments>`__ environment. The following sections provide explanations of relevant and optional packages for this course and how those can be installed.

ArcGIS and arcpy

The proprietary license-requiring arcpy package is described on the Commercial software page.

gdal (including ogr and osr)

`gdal <https://gdal.org/>`__ and ogr of the OSGeo Project stem from the GDAL project, which is part of the Open Source Geospatial Foundation (OSGeo) - the developers of QGIS. gdal provides many methods to convert geospatial data (file types, projections, derive geometries), where gdal itself hand els raster data and its ogr module hand les vector data. The tutorials on this website depend on gdal and ogr (including osr for spatial referencing); so it is important to get the installation of gdal right.

To install gdal for Python, open Anaconda Prompt and type:

conda install -c conda-forge gdal

Tip

Conda users may experience that installing gdal results in conflicts. Wait for Anaconda Prompt resolving the conflicts, then type conda update conda, conda update anaconda, and restart Anaconda Prompt. Now re-install gdal with conda install -c conda-forge gdal (a similar procedure may be required for other geospatial package installations).

Note

None-conda users, if you cannot ``import gdal``, for some apparently arbitrary reasons (e.g., Error: Arbitrary-like stuff is missing.), the problem probably lies in the definition of environmental variables. The problem can be trouble-shot in PyCharm with the following solution

  1. Go to File > Settings … > Build, Execution, Deployment > Console > Python Console > Environment variables

  2. Set the following environment_variables

    setx GDAL_DATA 'C:\Program Files\GDAL\gdal-data'setx GDAL_DRIVER_PATH 'C:\Program Files\GDAL\gdalplugins'setx PROJ_LIB 'C:\Program Files\GDAL\projlib'setx PYTHONPATH 'C:\Program Files\GDAL\'Wait a couple of moments until PyCharm adapted (building skeleton …) the new environment_variables and import gdal - should work now.

Linux

In general, the installation of gdal in only an environment can be tricky. Therefore, Linux users may want to make a global installation with:

  1. sudo apt install -y build-essentiallibxml2-dev libxslt1-dev (install build and XML tools)

  2. sudo apt install libgdal-dev (install gdal development files)

  3. sudo apt install python-gdal (install gdal itself)

  4. Enable gdal in a virtual environment:

    • run virtual wrapper: toggleglobalsitepackages

    • activate environment with conda activate ENVIRONMENT

    • activate global site packages for the current environment: toggleglobalsitepackages enable global site-packages

geojson

`geojson <https://pypi.org/project/geojson/>`__ is the most direct option for handling GeoJSON data. To install geojson for Python, open Anaconda Prompt and type:

conda install -c conda-forge geojson

descartes

Even though of proprietary origin, the `descartes <https://docs.descarteslabs.com/api.html>`__ package (developed and maintained by Descartes Labs) comes with many open-sourced functions. Moreover, Decartes Labs hosts the showcase platform GeoVisual Search with juicy illustrations of aritificial intelligence (AI) applications in geoscience. To install descartes for Python, open Anaconda Prompt and type:

conda install -c conda-forge descartes

Python Imaging Library (PIL) / pillow

Processing images with Python is enabled with the Python Imaging Library (PIL). PIL supports many image file formats, and has efficient graphics processing capabilities. The pillow library is a user-friendly PIL fork and provides Image* modules (e.g., Image, ImageDraw, ImageMath, and many more).

The comprehensive pillow documentation is available at readthedocs.io. To install pillow in a conda environment open Anaconda Prompt and type:

conda install -c anaconda pillow

shapely

A preferable and very well documented package for shapefile handling is `shapely <https://shapely.readthedocs.io/>`__. To install shapely for Python, open Anaconda Prompt and type:

conda install -c conda-forge shapely

shapely is also used in the `geo_utils package <https://geo-utils.readthedocs.io/>`__, which contains tailored functions for this course.

pyshp

Another shapfile handling package `pyshp <https://pypi.org/project/pyshp/>`__, which provides pure Python code (rather than wrappers), which simplifies direct dealing with shapefiles in Python. To install pyshp for Python, open Anaconda Prompt and type:

conda install -c conda-forge pyshp

Other packages

Besides the above mentioned packages there are other useful libraries for geospatial analyses in Python . Packages in bold font are used in the `geo_utils package <https://geo-utils.readthedocs.io/>`__, which contains tailored functions for this course.

Geodata About Exercises