Geographic Information System software can get expensive quickly. Licences, extensions, specialist modules and server components can turn a simple mapping project into a sizeable IT expense.
That is one reason free and open source GIS software continues to attract students, researchers, engineers, planners and businesses. The software is not simply “free GIS” in the sense of a stripped-down trial version.
Several open source projects are mature enough to handle serious spatial analysis, remote sensing, database work and web mapping.
The bigger question is which one fits the work.
A person creating property maps does not need the same software as a researcher analysing satellite imagery. A web developer publishing thousands of map features has a different requirement again. The 10 applications below cover those different situations.
1. QGIS
QGIS is probably the first name that comes up when discussing free GIS software, and there is a practical reason for that. It manages an unusually broad range of GIS work without forcing users to assemble a collection of separate applications.
Maps can be created, vector layers edited, raster datasets processed and spatial relationships analysed from the same desktop environment. QGIS also connects with PostgreSQL/PostGIS databases, web map services and numerous file formats. The project supports Windows, macOS and Linux.
Its plugin system is another major attraction. Need a particular tool that is not included in a standard installation? There is a good chance an existing plugin covers it.
QGIS is also useful as the centre of a larger open source GIS setup. GRASS GIS, SAGA and other processing frameworks can be accessed through its processing environment.
Best suited for: General GIS, cartography, spatial analysis, education and professional mapping.
2. GRASS GIS
GRASS GIS is not the flashy option. It is the workhorse.
The project has a long history in scientific and environmental GIS, and its strength lies in processing rather than presentation. Raster analysis, terrain modelling, hydrology, land-cover work, vector processing and spatial modelling are all areas where GRASS has plenty to offer.
There is a learning curve. GRASS has a large collection of modules, and new users may need time to understand how its processing model works. Once that hurdle is crossed, however, the software becomes useful for repeatable and technically demanding analysis.
It can also be used from the command line and Python environments. That matters when a GIS operation needs to be repeated across hundreds or thousands of datasets.
GRASS can also work inside QGIS, so using it does not necessarily mean abandoning a familiar desktop mapping interface.
Best suited for: Environmental analysis, terrain modelling, hydrology, research and advanced spatial processing.
3. SAGA GIS
SAGA GIS stands for System for Automated Geoscientific Analyses. The name is a little academic, and so is much of the software.
That is not a criticism.
SAGA is particularly useful when geographic data needs to be analysed rather than simply displayed. Its toolset covers terrain analysis, raster processing, interpolation, image processing and various geoscientific operations.
Digital elevation models are a good example. A DEM can be turned into slope, aspect, hillshade and other terrain-related datasets, providing information that would be difficult to extract from a plain map.
SAGA also fits into broader GIS workflows. Data can be moved between SAGA, QGIS and other applications rather than keeping every operation inside one program.
For someone working in environmental science, geography or terrain analysis, that flexibility can save considerable time.
Best suited for: DEM processing, terrain analysis, environmental research and scientific GIS.
4. gvSIG Desktop
gvSIG Desktop is sometimes overlooked in discussions about open source GIS, but it has been around long enough to prove that it is more than an experimental project.
The software provides tools for editing, analysing and presenting geographic information. It works with vector and raster data, databases and remote services, including OGC-based services.
One of its interesting areas is interoperability. GIS departments rarely work with one data source or one application. Files arrive in different formats, databases sit on separate systems and map services come from external organisations. Software that can communicate with those sources has a practical advantage.
gvSIG also includes tools for topology, networks, layouts and 3D visualisation.
It may not have the same mindshare as QGIS, but that does not make it irrelevant. It remains a useful choice for organisations looking for an open source desktop GIS.
Best suited for: Desktop GIS, database-connected mapping, editing and organisations using OGC services.
5. Whitebox
Whitebox is an interesting case because it is less focused on being a traditional all-purpose GIS application.
Its main attraction is geospatial analysis. The software is particularly strong around terrain, hydrology, LiDAR, raster and vector processing. Whitebox also provides tools that can be used through programming environments such as Python and R.
That makes it appealing to analysts who want to automate their work.
Consider a project involving hundreds of raster files. Running the same operation manually in a desktop GIS can become tedious very quickly. A scripted workflow can handle the repetitive part and leave the analyst to concentrate on the results.
Whitebox therefore fits neatly into modern data-analysis workflows. It does not have to replace QGIS. In many cases, the two make more sense together.
Best suited for: Terrain analysis, LiDAR, hydrology, raster processing and automated GIS workflows.
6. Orfeo ToolBox
Satellite imagery creates a different set of problems from ordinary GIS mapping. Huge raster files, multiple spectral bands and image classification require specialised processing tools.
Orfeo ToolBox, commonly called OTB, is built for that job.
OTB is an open source remote-sensing library designed for processing high-resolution optical and radar imagery. Its tools cover image classification, segmentation, orthorectification, pansharpening, change detection and other remote-sensing operations.
The project can be accessed through QGIS, Python and command-line workflows. That makes it useful for both researchers and automated processing pipelines.
One point often missed in older software lists: OTB is no longer centred around its own traditional desktop graphical interface. Its processing framework and integrations are the important part.
Best suited for: Satellite imagery, remote sensing, image classification and large raster datasets.
7. GeoServer
GeoServer is where the discussion moves from desktop GIS to the web.
Instead of opening a GIS application to inspect a dataset, GeoServer can publish spatial information so that other applications and users can access it over a network. It supports widely used OGC standards such as WMS, WFS and WCS.
That makes it useful behind web mapping applications, spatial data portals and internal geographic-information systems.
A common setup might look something like this: QGIS is used by GIS staff to prepare and edit data, PostGIS stores the spatial database, and GeoServer publishes selected layers to a web application.
GeoServer is therefore not really competing with QGIS. They solve different problems.
For an organisation planning to put geographic data online, GeoServer deserves serious consideration.
Best suited for: Web GIS, spatial data portals, OGC services and publishing geographic datasets.
8. MapServer
MapServer takes a similar web-oriented approach but comes from a different technical tradition.
It is an open source platform for publishing spatial data and creating map services. The project can be used with different data sources and integrated into web applications.
MapServer is particularly relevant to developers who need a map-serving backend rather than a full desktop GIS.
The distinction matters. Installing MapServer will not suddenly provide the editing and cartography experience associated with QGIS. Its job is to make geographic information available to applications and users.
For organisations with existing web infrastructure, MapServer can provide a lightweight route to serving spatial data without committing to a proprietary server product.
Best suited for: Web mapping, spatial data services and developer-focused GIS applications.
9. OpenJUMP
OpenJUMP is a desktop GIS written in Java and has a particularly practical focus on vector data.
It supports geographic data editing, spatial operations and connections to several common GIS data sources and services. The project also includes tools for topology and geometry processing.
It is not trying to be everything to everyone. That can actually be an advantage.
For a project centred on vector layers, geometry editing and spatial analysis, OpenJUMP provides a relatively straightforward environment. It is also extensible through plugins.
QGIS will usually come up first for users looking for a broad desktop GIS, but OpenJUMP remains a useful alternative for particular vector-processing workflows.
Best suited for: Vector editing, geometry operations, topology and desktop GIS work.
10. uDig
uDig, short for User-friendly Desktop Internet GIS, is another open source Java-based GIS project. Its focus includes desktop mapping, spatial data editing and access to internet-based geographic services.
The software can work with services such as WMS and WFS and has been designed as an extensible GIS framework rather than simply a finished desktop application.
That framework approach is important for developers. uDig can be extended through plugins and used as part of applications that require embedded GIS functionality.
It is a more specialised choice than QGIS and does not have the same level of mainstream adoption. Still, for Java-based projects where extensibility matters, it can be worth examining.
Best suited for: Java-based GIS development, desktop mapping and extensible GIS applications.
Final Thoughts
The strongest part of the open source GIS ecosystem is not any single application. It is the fact that different tools can be connected.
A GIS team might edit data in QGIS, store it in PostGIS, process terrain with GRASS or Whitebox, analyse imagery with Orfeo ToolBox and publish selected layers through GeoServer. None of those jobs needs to be forced into one product.
That is where free and open source GIS software becomes particularly interesting for professional use. The cost advantage is obvious, but the bigger benefit is flexibility.
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