The GRASS GIS Development team has announced the release of the new major version GRASS GIS 7.0.0. This version provides many new functionalities including spatio-temporal database support, image segmentation, estimation of evapotranspiration and emissivity from satellite imagery, automatic line vertex densification during reprojection, more LIDAR support and a strongly improved graphical user interface experience. GRASS GIS 7.0.0 also offers significantly improved performance for many raster and vector modules: “Many processes that would take hours now take less than a minute, even on my small laptop!” explains Markus Neteler, the coordinator of the development team composed of academics and GIS professionals from around the world. The software is available for Linux, MS-Windows, Mac OSX and other operating systems.
About GRASS GIS
The Geographic Resources Analysis Support System https://grass.osgeo.org/, commonly referred to as GRASS GIS, is an open source Geographic Information System providing powerful raster, vector and geospatial processing capabilities in a single integrated software suite. GRASS GIS 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 presentation graphics and hardcopy maps. GRASS GIS has been translated into about twenty languages and supports a huge array of data formats. It can be used either as a stand-alone application or as backend for other software packages such as QGIS and R geostatistics. It is distributed freely under the terms of the GNU General Public License (GPL). GRASS GIS is a founding member of the Open Source Geospatial Foundation (OSGeo).
Most comand line options for GDAL/OGR tools that accept a coordinate system will allow you to give the name of a file containing WKT. And if you prefix the filename with ESRI:: the library will interprete the WKT as being ESRI WKT and convert to “standard” format accordingly. The -s_srs switch is assigning a source coordinate system to your input data (in case it didn’t have this properly defined already), and the -t_srs is defining a target coordinate system to reproject to.
TIGER files in OGR
# linear features:
ogr2ogr tiger_lines.shp tgr46081.rt1 CompleteChain
# area features:
tigerpoly.py tgr46081.rt1 tiger_area.shp
OGR CSV driver: easily indicate column types
You can now write a little csv help file to indicate the columns types to OGR. It works as follows. Suppose you have a foobar.csv file that looks like this:
After getting mad with Lidar points colorizing which till now required a DB table with GRASSRGB attributes, I have modified d.vect to support colors directly from z height (geometry). Works for 3D points, lines (eg, 3D contours) and 3D polygons (eg delaunay triangles):
# Spearfish: g.region rast=elevation.10m r.random elevation.10m n=5000 vector=random3d -d d.mon x0 # display as black points d.vect random3d # display 3D points colorized according to z height d.vect -z random3d zcol=gyr