The development team is happy to announce that a new bugfix version of GRASS GIS has been released today. This release fixes a number of bugs discovered in the 6.2.2 source code. It is primarily for stability purposes and adds minimal new features. Besides bug fixes it also includes a number of new message translations and updates for the help pages and projection database. Highlights include further maturation of the GRASS 6 GUI, vector, and database code. Some improvements have been backported from the GRASS 6.3 development branch where new development continues at a strong pace of approximately one code commit every hour, including major work on an all new cross-platform wxPython GUI and a native MS Windows port. The Geographic Resources Analysis Support System, commonly referred to as GRASS, is a Geographic Information System (GIS) combining powerful raster, vector, and geospatial processing engines into a single integrated software suite. GRASS includes tools for spatial modeling, visualization of raster and vector data, management and analysis of geospatial data, and the processing of satellite and aerial imagery. It also provides the capability to produce sophisticated 4D presentation graphics and hardcopy maps. GRASS is currently used around the world in academic and commercial settings as well as by many governmental agencies and environmental consulting companies. It runs on a variety of popular hardware platforms and is Free open-source software released under the terms of the GNU General Public License. GRASS is a proposed founding project of the new Open Source Geospatial Foundation. In support of the movement towards consolidation in the open source geospatial software world, GRASS is tightly integrated with the latest GDAL/OGR libraries. This enables access to an extensive range of raster and vector formats, including OGC-conformal Simple Features. GRASS also makes use of the highly regarded PROJ.4 software library with support for most known map projections and the easy definition of new and rare map projections via custom parameterization. Strong links are maintained with the QuantumGIS and R Statistics projects with integrated GRASS toolkits available for both. Software download at Source.