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Overview of the QGIS interface view: in red, the important features discussed in this tutorial, some side buttons in orange. QGIS is a Geographic Information System (GIS) . This means that unlike Inkscape, QGIS can manage data files geolocation and geotag raw (often in the format TIFF and shp ) which can be found on the internet (mostly).
Shapefile file extensions – Esri Webhelp docs for ArcGIS 10.0 (2010) Esri – Understanding Topology and Shapefiles; shapelib.maptools.org – Free c library for reading/writing shapefiles; Python Shapefile Library – Open Source (MIT License) Python library for reading/writing shapefiles
QGIS also makes it simple to share and publish geospatial data as maps, online services, or print maps in a variety of file formats, such as shapefiles, GeoTIFFs, and KML files. Screenshot of Print Composer. In order to prepare printed map with QGIS, Print Layout is used. It can be used for adding multiple map views, labels, legends, etc.
Thematic mapping. Creates image pictures from shapefiles and creates Google Maps websites with the data linked to the shapefile - Freeware: QGIS: yes Linux, MAC OS, Windows: QGIS Development Team qgis.org: Visualization Easy to use, ability to expand functionality with Python plugins. Geo-processing functions included. C++ GPL: GRASS: yes
QGis (full name: Quantum GIS) is a GPL license, cross-platform (Windows, Linux, Mac), and rather friendly cartographic software application. It is a Geographic Information System (GIS) program you can use to create, view, and analyze maps.
The Geospatial Data Abstraction Library (GDAL) is a computer software library for reading and writing raster and vector geospatial data formats (e.g. shapefile), and is released under the permissive X/MIT style free software license by the Open Source Geospatial Foundation.
Shapefiles : are a data exchange format created by ESRI and one of the most widely used GIS/geodata formats. One "shapefile" usually include four different files : .shp, .shx, .dbf, .prj.
Vector data is simpler to update and maintain, whereas a raster image will have to be completely reproduced. (Example: a new road is added). Vector data allows much more analysis capability, especially for "networks" such as roads, power, rail, telecommunications, etc. (Examples: Best route, largest port, airfields connected to two-lane highways).