Introduction

Free and Open Source Software (FOSS)

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Fig. 1 FOSS software overview (source).

Free and open-source software (FOSS) is a computer software that can be classified as both free software and open-source software. That is, anyone is freely licensed to

  • use,
  • copy,
  • study, and
  • change

the software in any way. The source code is openly shared so that people are encouraged to voluntarily improve the design of the software. This is in contrast to proprietary software, where the software is under restrictive copyright and the source code is usually hidden from the users. See Free and open-source software article on Wikipedia for more information.

FOSS for Geospatial

In 2006 was founded OSGeo Foundation to support the collaborative development of open source geospatial software, and promote its widespread use.

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Fig. 2 OSGeo logo (source)

The foundation has adopted principles to ensure that projects under OSGeo umbrella will satisfy basic quality requirements, namely:

  • Projects should manage themselves, striving for consensus and encouraging participation from all contributors - from beginning users to advanced developers.
  • Contributors are the scarce resource and successful projects court and encourage them.
  • Projects are encouraged to adopt open standards and collaborate with other OSGeo projects.
  • Projects are responsible for reviewing and controlling their code bases to insure the integrity of the open source baselines.

This principles ensure that OSGeo projects are well established, stable, mature and sustainable.

Software used in this training materials

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  • GRASS GIS (recommended version 7.8) for geospatial raster, imagery, and vector data processing and providing spatial analysis.
  • QGIS desktop (recommended version 3.4) for geospatial visualization, creating hardcopy outputs, and data publishing.
  • GDAL library for reading and writing various geospatial data.
  • sentinelsat library utility to search and download Copernicus Sentinel satellite images.
  • pyModis Python based library to work with MODIS data.
  • pyWPS implementation of the Web Processing Service standard from the Open Geospatial Consortium written in Python.

Virtual machine

The simplest way how to follow this training. VirtualBox must be installed on your PC, enable also virtualization support in BIOS. See Virtualization Quickstart for details.

A customized virtual machine (VM) below is based on OSGeoLive version 13. This VM contains all software dependecies including sample dataset. See GRASS Jena Workshop folder on the desktop.

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Fig. 3 Customized OSGeoLive VM

Download tailored virtual machine including sample dataset as 7z archive (10.2GB, 20GB uncompressed). Note that VM size can grow up to 40GB!

Note

RAM 4GB minimum, at least 2 CPU cores

Sample dataset

For purpose of this training materials a sample dataset has been created based on Open Data covering Germany and Jena region specifically. See detailed description below.

Sample dataset can be also download as 7z archive (6.1GB, 6.5GB uncompressed).

Units

See a timetable

Lecturer

  • Martin Landa, GeoForAll Lab, Czech Technical University in Prague, Czech Republic

Materials proudly provided by GISMentors training and mentoring group.

License

Creative Commons Attribution-ShareAlike 4.0 International License.

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Source code available on GitHub. Feel free to open issues or pull requests to improve the materials :-)

Document version: 2.0 (built Feb 13, 2020)