As of 24 May 2016, a new stable release branch was created for the upcoming GRASS GIS 7.2 release. This new branch includes all the many improvements which have been implemented in the former development version 7.1.svn.
What is a branch? In simple words, it is a kind of directory in the software development server (SVN in our case) in which no more development but only bugfixing happens. From a release branch, new stable releases are created and published.
The actual branches in the GRASS GIS project are:
very old stable: releasebranch_6_4 (used for bugfixing and to publish stable GRASS GIS 6.4.x releases) – very low release frequency (started in revision r34936)
old stable releasebranch_7_0 (used for bugfixing and to publish stable GRASS GIS 7.0.x releases) – perhaps one last release upcoming (branch started in revision r59487 but development already started in Apr 2008 in r31142)
new stable releasebranch_7_2 (used for bugfixing and to publish stable GRASS GIS 7.2.x releases) – upcoming series of stable releases (branch started in revision r68500)
trunk (used for development, with pseudo-name 7.3.svn) – under heavy development
Note to SVN users
The trunk branch with pseudo-name 7.1.svn has become 7.3.svn due to the creation of the new 7.2.svn release branch. You can simply continue to update from SVN, the version will be automatically updated.
If you used to work with the 7.0.svn release branch, consider to download the new 7.2.svn release branch, either from the weekly source code snapshot (here) or from the SVN server directly (here).
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).
From March 2016 onwards, Dr. Markus Neteler, a prominent head of the Open Source GIS scene, will join the management board of mundialis GmbH & Co. KG in Bonn, Germany. Founded in 2015, mundialis combines remote sensing and satellite data analysis in the field of Big Data with Open Source WebGIS solutions.
Since 2008, Dr. Neteler was the head of the GIS and remote sensing unit at the Edmund Mach Foundation in Trento (Italy) and worked in this capacity on numerous projects related to biodiversity, environmental and agricultural research. He is also a founding member of the Open Source Geospatial Foundation (OSGeo), a nonprofit organization with headquarters in Delaware (USA), that promotes the development and use of free and open source geographic information systems (GIS). Since 1998 he coordinated the development of the well known GRASS GIS software project, a powerful Open Source GIS that supports processing of time series of several thousand raster, 3D raster or vector maps in a short time.
Markus will keep his role as “Mr. GRASS” at mundialis, especially because the company also sees itself as a research and development enterprise that puts its focus on the open source interfaces between geoinformation and remote sensing. Although a new company, mundialis offers more than 50 years of experience in GIS, due to the background of its management. Besides Neteler, there are Till Adams and Hinrich Paulsen, both at the same time the founders and CEOs of terrestris in Bonn, a company that develops Open Source GIS solutions since 2002. These many years of experience in the construction of WebGIS and Geoportal architectures using free software as well as in the application of common OGC standards – are now combined with mundialis’ expertise in the processing of big data with spatial reference and remote sensing data.
https://neteler.org/wp-content/uploads/2024/01/wg_neteler_logo.png00Markushttps://neteler.org/wp-content/uploads/2024/01/wg_neteler_logo.pngMarkus2016-01-25 18:06:482023-11-03 23:12:00Markus Neteler joins the management of mundialis in Bonn
The new GRASS GIS 7.0.2 release provides 190 stability fixes and manual improvements.
About GRASS GIS 7: Its graphical user interface supports the user to make complex GIS operations as simple as possible. The updated Python interface to the C library permits users to create new GRASS GIS-Python modules in a simple way while yet obtaining powerful and fast modules. Furthermore, the libraries were significantly improved for speed and efficiency, along with support for huge files. A lot of effort has been invested to standardize parameter and flag names. Finally, GRASS GIS 7 comes with a series of new modules to analyse raster and vector data, along with a full temporal framework. For a detailed overview, see the list of new features. As a stable release series, 7.0.x enjoys long-term support.
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).
This release addresses some minor issues found in the first GRASS GIS 7.0.0 release published earlier this year. The new release provides a series of stability fixes in the core system and the graphical user interface, PyGRASS improvements, some manual enhancements, and a few language translations.
This release is the 32nd birthday release of GRASS GIS.
New in GRASS GIS 7: Its new graphical user interface supports the user in making complex GIS operations as simple as possible. A new Python interface to the C library permits users to create new GRASS GIS-Python modules in a simple way while yet obtaining powerful and fast modules. Furthermore, the libraries were significantly improved for speed and efficiency, along with support for huge files. A lot of effort has been invested to standardize parameter and flag names. Finally, GRASS GIS 7 comes with a series of new modules to analyse raster and vector data, along with a full temporal framework. For a detailed overview, see the list of new features. As a stable release 7.0 enjoys long-term support.
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).
https://neteler.org/wp-content/uploads/2024/01/wg_neteler_logo.png00Markushttps://neteler.org/wp-content/uploads/2024/01/wg_neteler_logo.pngMarkus2015-07-31 20:20:162023-10-22 18:58:12GRASS GIS 7.0.1 released – 32 years of GRASS GIS
Thanks to the work of Volker Fröhlich and other Fedora/EPEL packagers I was able to create RPM packages of QGIS 2.10 Pisa for Fedora 21, Centos 7, and Scientific Linux 7 using the great COPR platform.
Sometimes, we developers get reports via mailing list that this & that would not work on whatever operating system. Now what? Should we be so kind and install the operating system in question in order to reproduce the problem? Too much work… but nowadays it has become much easier to perform such tests without having the need to install a full virtual machine – thanks to docker.
Disclaimer: I don’t know much about docker yet, so take the code below with a grain of salt!
In my case I usually work on Fedora or Scientific Linux based systems. In order to quickly (i.e. roughly 10 min of automated installation on my slow laptop) try out issues of GRASS GIS 7 on e.g., Ubuntu, I can run all my tests in docker installed on my Fedora box:
# we need to run stuff as root user
su
# Fedora 21: install docker
yum -y docker-io
# Fedora 22: install docker
dnf -y install docker
# enable service
systemctl start docker
systemctl enable docker
Now we have a running docker environment. Since we want to exchange data (e.g. GIS data) with the docker container later, we prepare a shared directory beforehand:
# we'll later map /home/neteler/data/docker_tmp to /tmp within the docker container
mkdir /home/neteler/data/docker_tmp
Now we can start to install a Ubuntu docker image (may be “any” image, here we use “Ubuntu trusty” in our example). We will share the X11 display in order to be able to use the GUI as well:
# enable X11 forwarding
xhost +local:docker
# search for available docker images
docker search trusty
# fetch docker image from internet, establish shared directory and display redirect
# and launch the container along with a shell
docker run -v /data/docker_tmp:/tmp:rw -v /tmp/.X11-unix:/tmp/.X11-unix \
-e uid=$(id -u) -e gid=$(id -g) -e DISPLAY=unix$DISPLAY \
--name grass70trusty -i -t corbinu/docker-trusty /bin/bash
In almost no time we reach the command line of this minimalistic Ubuntu container which will carry the name “grass70trusty” in our case (btw: read more about Working with Docker Images):
root@8e0f233c3d68:/#
# now we register the Ubuntu-GIS repos and get GRASS GIS 7.0
add-apt-repository ppa:ubuntugis/ubuntugis-unstable
add-apt-repository ppa:grass/grass-stable
apt-get update
apt-get install grass7
This will take a while (the remaining 9 minutes or so of the overall 10 minutes).
Since I like cursor support on the command line, I launch (again?) the bash in the container session:
root@8e0f233c3d68:/# bash
# yes, we are in Ubuntu here
root@8e0f233c3d68:/# cat /etc/issue
Now we can start to use GRASS GIS 7, even with its graphical user interface from inside the docker container:
# create a directory for our data, it is mapped to /home/neteler/data/docker_tmp/
# on the host machine
root@8e0f233c3d68:/# mkdir /tmp/grassdata
# create a new LatLong location from EPSG code
# (or copy a location into /home/neteler/data/docker_tmp/)
root@8e0f233c3d68:/# grass70 -c epsg:4326 ~/grassdata/latlong_wgs84
# generate some data to play with
root@8e0f233c3d68:/# v.random n=30 output=random30
# start the GUI manually (since we didn't start GRASS GIS right away with it before)
root@8e0f233c3d68:/# g.gui
Indeed, the GUI comes up as expected!
GRASS GIS 7 GUI in docker container
You may now perform all tests, bugfixes, whatever you like and leave the GRASS GIS session as usual.
To get out of the docker session:
root@8e0f233c3d68:/# exit # leave the extra bash shell
root@8e0f233c3d68:/# exit # leave docker session
# disable docker connections to the X server
[root@oboe neteler]# xhost -local:docker
To restart this session later again, you will call it with the name which we have earlier assigned:
[root@oboe neteler]# docker ps -a
# ... you should see "grass70trusty" in the output in the right column
# we are lazy and automate the start a bit
[root@oboe neteler]# GRASSDOCKER_ID=`docker ps -a | grep grass70trusty | cut -d' ' -f1`
[root@oboe neteler]# echo $GRASSDOCKER_ID
[root@oboe neteler]# xhost +local:docker
[root@oboe neteler]# docker start -a -i $GRASSDOCKER_ID
### ... and so on as described above.
https://neteler.org/wp-content/uploads/2024/01/wg_neteler_logo.png00Markushttps://neteler.org/wp-content/uploads/2024/01/wg_neteler_logo.pngMarkus2015-04-12 00:30:102023-11-11 19:07:57Fun with docker and GRASS GIS software
To get the GRASS GIS 6.4.5RC1 source code directly from SVN:
svn checkout https://svn.osgeo.org/grass/grass/tags/release_20150406_grass_6_4_5RC1/
Key improvements:
Key improvements of the GRASS GIS 6.4.5RC1 release include stability fixes (esp. vector library), some fixes for wxPython3 support, some module fixes, and more message translations.
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).
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).
GRASS GIS 7 just got better: When reprojecting vector data, now automated vertex densification is applied. This reduces the reprojection error for long lines (or polygon boundaries). The needed improvement has been kindly added in v.proj by Markus Metz.
Example
As an (extreme?) example, we generate a box in LatLong/WGS84 (EPSG: 4326) which is of 10 degree side length (see below for screenshot and at bottom for SHAPE file download of this “box” map):
[neteler@oboe ~]$ grass70 ~/grassdata/latlong/grass7/
# for the ease of generating the box, set computational region:
g.region n=60 s=40 w=0 e=30 res=10 -p
projection: 3 (Latitude-Longitude)
zone: 0
datum: wgs84
ellipsoid: wgs84
north: 60N
south: 40N
west: 0
east: 30E
nsres: 10
ewres: 10
rows: 2
cols: 3
cells: 6
# generate the box according to current computational region:
v.in.region box_latlong_10deg
exit
Next we start GRASS GIS in a metric projection, here the EU LAEA:
Then we do a second reprojection with new automated vertex densification (here we use the default values for smax which is a 10km vertex distance in the reprojected map by default):
Comparison of the reprojection of a 10 degree large LatLong box to the metric EU LAEA (EPSG 3035): before in red and new in green. The grid is based on WGS84 at 5 degree spacing.
The result shows how nicely the projection is now performed in GRASS GIS 7: the red line output is old, the green color line is the new output (its area filling is not shown).
Consider to benchmark this with other GIS… the reprojected map should not become a simple trapezoid.