Struggling to choose between GRASS GIS and Global Mapper? Both products offer unique advantages, making it a tough decision.
GRASS GIS is a Science & Engineering solution with tags like gis, geospatial, data-analysis, data-visualization, mapping.
It boasts features such as Raster and vector GIS data processing, Image processing, Map production, Spatial modeling and analysis, 3D visualization support and pros including Free and open source, Cross-platform compatibility, Powerful geospatial data processing and analysis, Active development community, Extensive documentation and tutorials.
On the other hand, Global Mapper is a Office & Productivity product tagged with geospatial, mapping, data-visualization.
Its standout features include View, edit and convert geospatial data, Support for a wide range of raster and vector formats, Terrain analysis and 3D visualization, Georeferencing and coordinate system transformations, Advanced digitizing and editing tools, Spatial analysis and modeling, Network analysis tools, Scripting and automation capabilities, and it shines with pros like Very versatile and supports many data formats, User-friendly and easy to use interface, Powerful analysis and data processing capabilities, Good value for money compared to other GIS software.
To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.
GRASS GIS is a free and open source geographic information system used for geospatial data management, analysis, graphics and maps production, spatial modeling, and visualization. It operates on various operating systems including Linux, Mac OSX, and Windows.
Global Mapper is a versatile GIS (Geographic Information System) software application used for viewing, editing, analyzing, and converting geospatial data. It supports a wide range of raster and vector data formats allowing easy integration of spatial data.