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GRASS GIS 7.0.2 released

What’s new in a nutshell

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.

Source code download:

Binaries download:

More details:

See also our detailed announcement:

  https://trac.osgeo.org/grass/wiki/Grass7/NewFeatures (overview of new 7.0 stable release series)First time users may explore the first steps tutorial after installation.

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).

The GRASS Development Team, November 2015

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GRASS GIS 7.0.1 released – 32 years of GRASS GIS

What’s new in a nutshellgrass7_logo_500px

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.

Source code download:

Binaries download:

More details:

See also our detailed announcement:

  https://trac.osgeo.org/grass/wiki/Grass7/NewFeatures (overview of new stable release series)First time users may explore the first steps tutorial after installation.

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).

The GRASS Development Team, July 2015

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Sol Katz Award – Call for Nominations

The Open Source Geospatial Foundation would like to open nominations for the 2015 Sol Katz Award for Geospatial Free and Open Source Software.

The Sol Katz Award for Geospatial Free and Open Source Software (GFOSS) will be given to individuals who have demonstrated leadership in the GFOSS community. Recipients of the award will have contributed significantly through their activities to advance open source ideals in the geospatial realm.

Sol Katz was an early pioneer of GFOSS and left behind a large body of work in the form of applications, format specifications, and utilities while at the U.S. Bureau of Land Management. This early GFOSS archive provided both source code and applications freely available to the community. Sol was also a frequent contributor to many geospatial list servers, providing much guidance to the geospatial community at large.

Sol unfortunately passed away in 1999 from Non-Hodgkin’s Lymphoma, but his legacy lives on in the open source world. Those interested in making a donation to the American Cancer Society, as per Sol’s family’s request, can do so at https://donate.cancer.org/index.

Nominations for the Sol Katz Award should be sent to SolKatzAward@osgeo.org with a description of the reasons for this nomination. Nominations will be accepted until 23:59 UTC on August 21st (https://www.timeanddate.com/worldclock/fixedtime.html?month=8&day=21&year=2015&hour=23&min=59&sec=59).
A recipient will be decided from the nomination list by the OSGeo selection committee.

The winner of the Sol Katz Award for Geospatial Free and Open Source Software will be announced at the FOSS4G-Seoul event in September. The hope is that the award will both acknowledge the work of community members, and pay tribute to one of its founders, for years to come.

It should be noted that past awardees and selection committee members are not eligible.

More info at the Sol Katz Award wiki page
https://wiki.osgeo.org/wiki/Sol_Katz_Award

Past Awardees:

2014: Gary Sherman
2013: Arnulf Christl
2012: Venkatesh Raghavan
2011: Martin Davis
2010: Helena Mitasova
2009: Daniel Morissette
2008: Paul Ramsey
2007: Steve Lime
2006: Markus Neteler
2005: Frank Warmerdam

Selection Committee 2015:

Jeff McKenna (chair)
Frank Warmerdam
Markus Neteler
Steve Lime
Paul Ramsey
Sophia Parafina
Daniel Morissette
Helena Mitasova
Martin Davis
Venkatesh Raghavan
Arnulf Christl
Gary Sherman

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Inofficial QGIS 2.8 RPMs for EPEL 7: Fedora 20, Fedora 21, Centos 7, Scientific Linux 7

qgis-icon_smallThanks to the work of Devrim Gündüz, Volker Fröhlich, Dave Johansen, Rex Dieter and other Fedora/EPEL packagers I had an easy going to prepare RPM packages of QGIS 2.8 Wien for Fedora 20 and 21, Centos 7, and Scientific Linux 7.

The base SRPM package I copied from Fedora’s koji server, modified the SPEC file in order to remove the now outdated PyQwt bindings (see bugzilla) and compiled QGIS 2.8 via the great COPR platform.

Repo: https://copr.fedoraproject.org/coprs/neteler/QGIS-2.8-Wien/

The following packages can now be installed and tested on epel-7-x86_64 (Centos 7, Scientific Linux 7, etc.), Fedora-20-x86_64, and Fedora-21-x86_64:

  • qgis 2.8.1
  • qgis-debuginfo 2.8.1
  • qgis-devel 2.8.1
  • qgis-grass 2.8.1
  • qgis-python 2.8.1
  • qgis-server 2.8.1

Installation instructions (run as “root” user or use “sudo”):

# EPEL7:
yum -y install epel-release
yum -y install wget
# https://copr.fedorainfracloud.org/coprs/neteler/python-OWSLib/
wget -O /etc/yum.repos.d/neteler-python-OWSLib-epel-7.repo https://copr.fedorainfracloud.org/coprs/neteler/python-OWSLib/repo/epel-7/neteler-python-OWSLib-epel-7.repo
yum -y update
yum -y install python-OWSLib
wget -O /etc/yum.repos.d/qgis-epel-7.repo https://copr.fedorainfracloud.org/coprs/neteler/QGIS-2.8-Wien/repo/epel-7/neteler-QGIS-2.8-Wien-epel-7.repo
yum update
yum install qgis qgis-grass qgis-python qgis-server

# Fedora 20:
wget -O /etc/yum.repos.d/qgis-epel-7.repo https://copr.fedorainfracloud.org/coprs/neteler/QGIS-2.8-Wien/repo/fedora-20/neteler-QGIS-2.8-Wien-fedora-20.repo
yum update
yum install qgis qgis-grass qgis-python qgis-server

# Fedora 21:
wget -O /etc/yum.repos.d/qgis-epel-7.repo https://copr.fedorainfracloud.org/coprs/neteler/QGIS-2.8-Wien/repo/fedora-21/neteler-QGIS-2.8-Wien-fedora-21.repo
yum update
yum install qgis qgis-grass qgis-python qgis-server

The other packages are optional (well, also qgis-grass, qgis-python, and qgis-server…).

Enjoy!

PS: Of course I hope that QGIS 2.8 officially hits EPEL7 anytime soon! My COPR repo is just a temporary bridge towards that goal.

EDIT 30 April 2015:

  • updated EPEL7 installation for python-OWSLib dependency
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New stable release of GRASS GIS 7.0.0!

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.

Detailed announcement and software download:
https://grass.osgeo.org/news/42/15/GRASS-GIS-7-0-0/

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).

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Happy 9th Birthday, OSGeo!

Press release by Jeff McKenna, OSGeo Foundation President

9 years ago today was the first ever meeting of the OSGeo foundation, in Chicago U.S.A. (initial press release). Thanks to those passionately involved back then, and the thousands contributing since, now our community has expanded and has reached many countries all over world. Congratulations to everyone for continuing to share the passion for Open Source geospatial.

Here is a glimpse at some of the exciting events happening around the world this year:

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Landsat 8 captures Trentino in November 2014

The beautiful days in early November 2014 allowed to get some nice views of the Trentino (Northern Italy) – thanks to Landsat 8 and NASA’s open data policy:

Landsat 8: Northern Italy 1 Nov 2014
Landsat 8: Northern Italy 1 Nov 2014

Trento captured by Landsat8
Trento captured by Landsat8

Landsat 8: San Michele - 1 Nov 2014
Landsat 8: San Michele – 1 Nov 2014

The beauty of the landscape but also the human impact (landscape and condensation trails of airplanes) are clearly visible.

All data were processed in GRASS GIS 7 and pansharpened with i.fusion.hpf written by Nikos Alexandris.

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QGIS 2.6 ‘Brighton’ released

In the new release of QGIS 2.6.0 a series of new features have been added concerning

  • General: new features and bugfixes,
  • DXF export (improvements),
  • Map Composer (enhancements),
  • Processing (including a new modeler implementation),
  • QGIS Server (improvements),
  • Symbology (including user interface improvements),
  • User Interface with improvements.

A visual changelog is available for more details with lots of screenshots.

Congratulations to all QGIS developers! Looking forward to see the Fedora RPM available…

You can download QGIS 2.6 at https://qgis.org/en/site/forusers/download.html

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Selective data removal in an elevation map by means of floodfilling

Do you also sometimes get maps which contain zero (0) rather than NULL (no data) in some parts of the map? This can be easily solved with “floodfilling”, even in a GIS.

My original map looks like this (here, Trentino elevation model):

The light blue parts should be no data (NULL) rather than zero (0)...

Now what? In a paint software we would simply use bucket fill but what about GIS data? Well, we can do something similar using “clumping”. It requires a bit of computational time but works perfectly, even for large DEMs, e.g., all Italy at 20m resolution. Using the open source software GRASS GIS 7, we can compute all “clumps” (that are many for a floating point DEM!):

# first we set the computational region to the raster map:
g.region rast=pat_DTM_2008_derived_2m -p
r.clump pat_DTM_2008_derived_2m out=pat_DTM_2008_derived_2m_clump

The resulting clump map produced by r.clump is nicely colorized:

Clumped map derived from DEM (generated with r.clump)

As we can see, the area of interest (province) is now surrounded by three clumps. With a simple map algebra statement (r.mapcalc or GUI calculator) we can create a MASK by assigning these outer boundary clumps to NULL and the other “good” clumps to 1:

r.mapcalc "no_data_mask = if(pat_DTM_2008_derived_2m_clump == 264485050 || \
  pat_DTM_2008_derived_2m_clump == 197926480 || \
  pat_DTM_2008_derived_2m_clump == 3, null(), 1)"

This mask map looks like this:

Mask map from all clumps except for the large outer clumps

We now activate this MASK and generate a copy of the original map into a new map name by using map algebra again (this just keeps the data matched by the MASK). Eventually we remove the MASK and verify the result:

# apply the mask
r.mask no_data_mask
# generate a copy of the DEM, filter on the fly
r.mapcalc "pat_DTM_2008_derived_2m_fixed = pat_DTM_2008_derived_2m"
# assign a nice color table
r.colors pat_DTM_2008_derived_2m_fixed color=srtmplus
# remove the MASK
r.mask -r

And the final DEM is now properly cleaned up in terms of NULL values (no data):

DEM cleaned up for no data

Enjoy.

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GDAL/OGR 1.11.0 released

The new version 1.11.0 of GDAL/OGR https://gdal.org/ which offers major new features has been released. GDAL/OGR is a C++ geospatial data access library for raster and vector file formats, databases and web services.  It includes bindings for several languages, and a variety of command line tools.

Highlights:

More complete information on the new features and fixes in the 1.11.0 release can be found at https://trac.osgeo.org/gdal/wiki/Release/1.11.0-News

The new release can be downloaded from:

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