This description of Quantum GIS is taken from WIKIPEDIA and will lead you to into the Quantum GIS world with all of its resources.
Gary Sherman began development of Quantum GIS in early 2002, and it became an incubator project of the Open Source Geospatial Foundation in 2007. Version 1.0 was released in January 2009.
Written in C++, Quantum GIS makes extensive use of the Qt library. Quantum GIS allows integration of plugins developed using either C++ or Python. In addition to Qt, required dependencies of Quantum GIS include GEOS and SQLite. GDAL, GRASS GIS, PostGIS, and PostgreSQL are also recommended, as they provide access to additional data formats.
Quantum GIS runs on multiple operating systems including Mac OS X, Linux, UNIX, and Microsoft Windows. For Mac users, the advantage of Quantum GIS over GRASS GIS is that it does not require the X11 windowing system in order to run, and the interface is much cleaner and faster. Quantum GIS can also be used as a graphical user interface to GRASS. Quantum GIS has a small file size compared to commercial GIS's and requires less RAM and processing power; hence it can be used on older hardware or running simultaneously with other applications where CPU power may be limited.
Quantum GIS is maintained by an active group of volunteer developers who regularly release updates and bug fixes. As of 2012 developers have translated Quantum GIS into 48 languages and the application is used internationally in academic and professional environments.
As a free software application under the GNU GPL, Quantum GIS can be freely modified to perform different or more specialized tasks. Two examples are the QGIS Browser and QGIS Server applications, which use the same code for data access and rendering, but present different front-end interfaces. There are also numerous plug-ins available which expand the software's core functionality.
Quantum GIS allows use of shapefiles, coverages, and personal geodatabases. MapInfo, PostGIS, and a number of other formats are supported in Quantum GIS. Web services, including Web Map Service and Web Feature Service, are also supported to allow use of data from external sources.
Plugins, written in Python, extend the capabilities of QGIS. There are plug-ins to geocode using the Google Geocoding API, perform geoprocessing (fTools) similar to the standard tools found in ArcGIS, interface with PostgreSQL and MySQL databases, and use Mapnik as a map renderer.
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