QGIS Planet

Installing PostGIS on Fedora 20

In order to explore all the new interfaces to PostGIS (from QGIS, GDAL, GRASS GIS 7 and others) I decided to install PostGIS 2.1 on my Fedora 20 Linux box. Eventually it is an easy job but I had to visit a series of blogs to refresh my dark memories from past PostGIS installations done some years ago… So, here the few steps:

# become root
su -
# grab the PostgreSQL 9.3 server and PostGIS 2.1
yum install postgresql-server postgresql-contrib postgis

Now the server is installed but yet inactive and not configured. The next step is to initialize, configure and start the PostgreSQL server:

# initialize DB:
postgresql-setup initdb
# start at boot time:
chkconfig postgresql on
# fire up the daemon:
service postgresql start

A test connection will show that we need to configure TCP/IP connections:

# this will fail
psql -l
psql: could not connect to server: No such file or directory
    Is the server running locally and accepting
    connections on Unix domain socket "/var/run/postgresql/.s.PGSQL.5432"?

So we enable TCP/IP connections listening on port 5432:

# edit "postgresql.conf" with editor of choice (nano, vim, ...),
# add line "listen_addresses = '*'":
vim /var/lib/pgsql/data/postgresql.conf
...
listen_addresses = '*'
#listen_addresses = 'localhost'         # what IP address(es) to listen on;
...

Now restart the PostgreSQL daemon:

# restart to re-read configuration
service postgresql restart

Check if the server is now listening on TCP/IP:

# check network connections:
netstat -l | grep postgres
tcp        0      0 0.0.0.0:postgres        0.0.0.0:*               LISTEN     
tcp6       0      0 [::]:postgres           [::]:*                  LISTEN     
unix  2      [ ACC ]     STREAM     LISTENING     2236495  /var/run/postgresql/.s.PGSQL.543

So far so nice. Still PostGIS is not yet active, and we need a database user “gisuser” with password:

# switch from root user to postgres user:
su - postgres
# create new DB user with password (will prompt you for it, choose a strong one):
createuser --pwprompt --encrypted gisuser

Finally we create a first database “gis”:

# create new DB
createdb --encoding=UTF8 --owner=gisuser gis

We enable it for PostGIS 2.1:

# insert PostGIS SQL magic (it should finish with a "COMMIT"):
psql -d gis -f /usr/share/pgsql/contrib/postgis-64.sql

That’s it! Now exit from the “postgres” user account a the “root” account:

# exit from PG user account (back to "root" account level):
exit

In case you want to reach the PostgreSQL/PostGIS server from outside your machine (i.e. from the network), you need to enable PostgreSQL for that:

# enable the network in pg_hba.conf (replace host line; perhaps comment IP6 line):
vim /var/lib/pgsql/data/pg_hba.conf

...
host    all             all             all                     md5
...

# save and restart the daemon:
service postgresql restart

Time for another connection test:

# we try our new DB user account on the new database (hostname is the 
# name of the server in the network):
psql --user gisuser -h hostname -l
Password for user gisuser: xxxxxx

Wonderful, we are connected!

# exit from root account:
exit
[neteler@oboe ] $

Now have our PostGIS database ready!

What’s left? Get some spatial data in as a normal user:

# nice tool
shp2pgsql-gui
shp2pgsql-gui

Using the shp2pgsql-gui

Next pick a SHAPE file and upload it to PostGIS with “Import”.

Now connect to your PostGIS database with QGIS or GRASS GIS and enjoy!

See also: https://fedoraproject.org/wiki/PostgreSQL

GDAL/OGR 1.11.0 released

The new version 1.11.0  of GDAL/OGR (http://www.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 http://trac.osgeo.org/gdal/wiki/Release/1.11.0-News

The new release can be downloaded from:

Workshop at FOSS4G 2014: Spatio-temporal data handling and visualization in GRASS GIS 7

Drowning in too many maps? Have some fun exploring fascinating geometries of changing landscapes in Space Time Cube and creating 2D and 3D animations from time series of geospatial data. Learn about the new capabilities for spatio-temporal data handling in GRASS GIS 7 (http://grass.osgeo.org/grass7/) and explore various techniques for dynamic visualizations.

First, we will introduce you to GRASS GIS 7, including its spatio-temporal capabilities and you will learn how to manage and analyze geospatial data time series. Then, we will explore new tools for visualization of spatio-temporal data. You will create both 2D and 3D dynamic visualizations directly in GRASS GIS 7. Additionally, we will explain the Space Time Cube concept using various applications based on raster and vector data time series. You will learn to manage and visualize data in space time cubes (voxel models). No prior knowledge of GRASS GIS is necessary, we will cover the basics needed for the workshop. All relevant material including an overview of the tools and hands-on practical instructions along with the sample data sets will be available on-line. And, by the way, GRASS GIS is a free and open source geographic information system (GIS) used for geospatial data management, analysis, modeling, image processing, and visualization which runs on Linux, MS Windows, Mac OS X and other systems.

Presenters: Vaclav Petras, Anna Petrasova, Helena Mitasova, Markus Neteler

When:  FOSS4G 2014, Sept 8th-13th 2014, Portland, OR, USA

Register at: https://2014.foss4g.org/schedule/workshops/#wshop-526

OSGeo-Live 7.9 Released

OSGeo today announced that the OSGeo-Live GIS software collection version 7.9 has been released, featuring more than fifty open source, standards compliant geospatial desktop applications, web applications and frameworks.

Release Highlights:
This release is a modernization update to last year’s 7.0 release including new versions of the software but preserving much of the core build and operating system. In addition we’ve added a number of small fixes and updated document translations.

OSGeo-Live Lightning Presentation:
The OSGeo-Live Lightning Presentation which explains the breadth of OSGeo software is now bundled with OSGeo-Live. It is often presented by conference organisors, or keynote speakers. The presentation may be given as is, or modified to align with time constraints, presenter’s interest, or conference focus. http://live.osgeo.org/livedvd/docs/en/presentation/

Applications:
Twenty two geospatial programs have been updated to newer versions. The core geospatial stack has also been upgraded from UbuntuGIS, and the base operating system has been updated to Xubuntu 12.04.4 LTS, including all the latest security and bug fixes, and web browser updates.

About OSGeo-Live:
OSGeo-Live is a self-contained bootable DVD, USB flash drive and Virtual Machine based upon Ubuntu Linux. OSGeo-Live is pre-configured with a wide variety of robust open source geospatial software. All applications can be trialled without installing anything on your computer, simply by booting the computer from a DVD or USB drive, or running in a Virtual Machine environment. Each featured package is accompanied by both a publication quality one page descriptive summary and a short tutorial on how to get started using it. http://live.osgeo.org

OSGeo-Live includes:

  • Over sixty quality geospatial Open Source applications installed and pre-configured
  • Free world maps and geodata
  • One page overview and quick start guide for every application
  • Overviews of key OGC standards
  • Translations to multiple languages

Credits
Over 180 people have directly helped with OSGeo-Live packaging, documenting and translating, and thousands have been involved in building the packaged software. Developers, packagers, documenters and translators include:
Activity Workshop, Agustín Dí­ez, Aikaterini Kapsampeli, Alan Beccati, Alan Boudreault, Alessandro Furieri, Alexander Bruy, Alexander Kleshnin, Alexander Muriy, Alexandre Dube, Alexey Ardyakov, Alex Mandel, Amy Gao, Andrea Antonello, Andrea Yanza, Andrey Syrokomskiy, Andry Rustanto, Angelos Tzotsos, Anna Muñoz, Antonio Falciano, Anton Novichikhin, Anton Patrushev, Argyros Argyridis, Ariel Núñez, Assumpció Termens, Astrid Emde, Barry Rowlingson, Benjamin Pross, Brian Hamlin, Bruno Binet, Bu Kun, Cameron Shorter, Christophe Tufféry, Christos Iossifidis, Cristhian Pin, Damian Wojsław, Dane Springmeyer, Daniel Kastl, Daria Svidzinska, David Mateos, Denis Rykov, Diego González, Diego Migliavacca, Dimitar Misev, Dmitry Baryshnikov, Dominik Helle, Edgar Soldin, Eike Hinderk Jürrens, Elena Mezzini, Eric Lemoine, Erika Pillu, Estela Llorente, Etienne Delay, Etienne Dube, Evgeny Nikulin, Fran Boon, François Prunayre, Frank Gasdorf, Frank Warmerdam, Friedjoff Trautwein, Gavin Treadgold, Giuseppe Calamita, Grald Fenoy, Grigory Rozhentsov, Guy Griffiths, Hamish Bowman, Haruyuki Seki, Henry Addo, Hernan Olivera, Howard Butler, Hyeyeong Choe, Ian Edwards, Ian Turton, Ilya Filippov, Jackie Ng, Jan Drewnak, Jane Lewis, Javier Rodrigo, Javier Sánchez, Jesús Gómez, Jim Klassen, Jing Wang, Jinsongdi Yu, Jody Garnett, Johan Van de Wauw, John Bryant, Jorge Arévalo, Jorge Sanz, José Antonio Canalejo, José Vicente Higón, Judit Mays, Klokan Petr Pridal, Kristof Lange, kuzkok, Lance McKee, Lars Lingner, Luca Delucchi, Lucía Sanjaime, Mage Whopper, Manuel Grizonnet, Marc-André Barbeau, Marco Curreli, Marco Puppin, Marc Torres, Margherita Di Leo, Maria Vakalopoulou, Mario Andino, Mark Leslie, Massimo Di Stefano, Matthias Streulens, Mauricio Miranda, Mauricio Pazos, Maxim Dubinin, Michaël Michaud, Michael Owonibi, Micha Silver, Mike Adair, Milena Nowotarska, M Iqnaul Haq Siregar, Nacho Varela, Nadiia Gorash, Nathaniel V. Kelso, Ned Horning, Nobusuke Iwasaki, Oliver Tonnhofer, Òscar Fonts, Otto Dassau, Pasquale Di Donato, Patric Hafner, Paul Meems, Pavel, Pedro-Juan Ferrer, Pirmin Kalberer, Raf Roset, Regina Obe, Ricardo Pinho, Roald de Wit, Roberta Fagandini, Roberto Antolin, Roberto Antolí­n, Roger Veciana, Ruth Schoenbuchner, Samuel Mesa, Scott Penrose, Sergey Grachev, Sergio Baños, Simon Cropper, Simon Pigot, Stefan A. Tzeggai, Stefan Hansen, Stefan Steiniger, Stephan Meissl, Steve Lime, Takayuki Nuimura, Thierry Badard, Thomas Baschetti, Thomas Gratier, Tom Kralidis, Toshikazu Seto, Trevor Wekel, Valenty González, Vera, Xianfeng Song, Yoichi Kayama, Zhengfan Lin

Sponsoring organisations

  • The Open Source Geospatial Foundation OSGeo provides the primary development and hosting infrastructure and personnel for the OSGeo-Live project, and infrastructure for many of the software projects themselves. http://osgeo.org
  • LISAsoft provides sustaining resources and staff toward the management and packaging of software onto the Live DVD. http://www.lisasoft.com
  • Information Center for the Environment (ICE) at the University of California, Davis provides hardware resources and development support to the OSGeo Live project. http://ice.ucdavis.edu
  • Remote Sensing Laboratory at the National Technical University of Athens, provides hardware resources and development support to the OSGeo-Live project. http://www.ntua.gr
  • The DebianGIS and UbuntuGIS teams provide and quality-assure many of the core packages. http://wiki.debian.org/DebianGis and https://wiki.ubuntu.com/UbuntuGIS

Will the sun shine on us?

Recently, in order to nicely plan ahead for a birthday lunch at the agritur Malga Brigolina (a farm-restaurant near Sopramonte di Trento, Italy, at 1,000m a.s.l. in the Southern Alps), friends of mine asked me the day before:

Will the place be sunny at lunch time for a nice walk?

[well, the weather was close to clear sky conditions but mountains are high here and casting long shadows in the winter time].

paganella_rotaliana

A rather easy task I thought, so I got my tools ready since that was an occasion to verify the predictions with some photos! Thanks to the new EU-DEM at 25m I was able to perform the computations right away in a metric system rather than dealing with degree in LatLong.

Direct sunlight can be assessed from the beam radiation map of GRASS GIS’ r.sun when running it for a specific day and time. But even easier, there is a new Addon for GRASS GIS 7 which calculates right away time series of insolation maps given start/stop timestamps and a time step: r.sun.hourly. This shrinks the overall effort to almost nothing.

1. Creating the direct sunlight maps

The first step is to calculate where direct sunlight reaches the ground. Here the input elevation map is the European “eu_dem_25″, while the output is the beam radiation for a certain day (15 Dec 2013 is DOY 349).

Important hint: the computational region must be large enough to east/south/west to capure the cast shadow effects of all relevant surrounding mountains.

I let calculations start at 8am and finish at 5pm which an hourly time step. The authors have kindly parallelized r.sun.hourly, so I let it run on four processors simultaneously to speed up:

# calculate DOY (day-of-year) from given date:
date -d 2013-12-15 +%j
349

# calculate beam radiation maps for a given time period
# (note: minutes are to be given in decimal time: 30min = 0.5)
r.sun.hourly elev_in=eu_dem_25 beam_rad=trento_beam_doy349 \
      start_time=8 end_time=17 time_step=1 day=349 year=2013 \
      nprocs=4

The ten resulting maps contain the beam radiation for each pixel considering the cast shadow effects of the pixel-surrounding mountains. However, the question was not to calculate irradiance raster maps in Wh/m^2 but simply “sun-yes” or “sun-no”. So a subsequent filtering had to be applied. Each beam radiation map was filtered: if pixel value equal to 0 then “sun-no”, otherwise “sun-yes” (what my friends wanted to achieve; effectively a conversion into a binary map).
Best done in a simple shell script loop:

[Edit 30 Dec 2013: thanks to Anna you can simplify below loop to the r.colors call thanks to the new -b flag for binary output in r.sun.hourly!]

for map in `g.mlist rast pattern="trento_beam_doy349*"` ; do
    # rename current map to tmp
    g.rename rast=$map,$map.tmp
    # filter and save with original name
    r.mapcalc "$map = if($map.tmp == 0, null(), 1)"
    # colorize the binary map
    echo "1 yellow" | r.colors $map rules=-
    # remove cruft
    g.remove rast=$map.tmp
done

As a result we got ten binary maps, ideal for using them as overlay with shaded DEMs or OpenStreetMap layers. The areas exposed to direct sunlight are shown in yellow.

Trento direct sunlight 15 Dec 2013 Animation

Trento, direct sunlight, 15 Dec 2013 between 10am and 5pm (See here for creating an animated GIF). Quality reduced for this blog.

2. Time to look at some details: So, is Malga Brigolina in sunlight at lunch time?

Situation at 12pm (noon): predicted that the restaurant is still in shadow – confirmed in the photo:

malga_brigolina_direct_sunlight_15dec2013_12pm_foto

(click to enlarge)

Situation at 1:30/2:00pm: sun is getting closer to the Malga, as confirmed in photo (note that the left photo is 20min ahead of the map). The small street in the right photo is still in the shadow as predicted in the map):

malga_brigolina_direct_sunlight_15dec2013_14pm_foto(click to enlarge)

Situation at 3:00pm: sun here and there at Malga Brigolina:

malga_brigolina_direct_sunlight_15dec2013_15pm_3DSunlight map blended with OpenStreetmap layer (r.blend + r.composite) and draped over DEM in wxNVIZ of GRASS GIS 7 (click to enlarge). The sunday walk path around Malga Brigolina is the blue/red vector line shown in the view center.

Situation at 4:00pm: we are close to sunset in Trentino… view towards the Rotaliana (Mezzocorona, S. Michele all’Adige), last sunlit summits also seen in photo:

rotaliana_direct_sunlight_15dec2013_16pm_foto(click to enlarge)

3. Outcome

The resulting sunlight/shadow map appear to match nicely realty. Perhaps r.sun.hourly should get an additional flag to generate the binary “sun-yes” – “sun-no” maps directly.

trento_direct_sunlight_15dec2013_15pm_3DDirect sunlight zones (yellow, 15 Dec 2013, 3pm): Trento with Monte Bondone, Paganella, Marzolan, Lago di Caldonazzo, Lago di Levico and surroundings (click to enlarge)

4. GRASS GIS usage note

The wxGUI settings were as simple as this (note the transparency values for the various layers):

trento_direct_sunlight_wxGUI

Data sources:

Video: GRASS GIS development visualization from 1999 to 2013

Watch how the community based GRASS GIS 6.4 software development evolved! You can see how the individual contributors modify and expand the source code:

  • Dec 29, 1999: GRASS GIS 5.0 is being stored in an online source code repository in December 1999…
  • Dec 02, 2000: The developers work on all parts of the code…
  • Jan 15, 2002: Working on the future GRASS GIS 5.1 release
  • Nov 25, 2002: Starting GRASS 5.1 development with code restructuring
  • Jun 14, 2004: GRASS GIS 5.7 released in June 2004
  • Nov 09, 2004: Source code restructuring to get a better directory layout (all other developers waiting…)
  • Nov 09, 2004: … thousands of files are modified in this operation …
  • Nov 10, 2004: All developers resume their activities after the restructuring
  • Jan 10, 2005: Preparing the GRASS GIS 6.0.0 release…
  • Apr 09, 2005: GRASS GIS 6.0.0 published, release branch being split off from trunk for easier maintenance
  • Feb 22, 2006: Release of GRASS GIS 6.0.2 and new source code refactoring startedApr 05, 2006: Heavy development activity in trunk (development branch) …
  • Oct 25, 2006: GRASS GIS 6.2.0 released in October 2006
  • Apr 10, 2007: Preparing the GRASS GIS 6.2.2 release…
  • Jun 16, 2007: GRASS GIS 6.2.2 released in June 2007
  • Nov 01, 2007: Raster and vector modules being actively maintained…
  • Apr 02, 2007: New graphical user interface development speeding up (wxGUI)
  • Feb 20, 2008: Copyright statements prettified in many files
  • May 31, 2008: New GRASS 6 development branch being split off from trunk (which becomes GRASS 7)
  • Jun 10, 2008: Developers moving over to new branch
  • Feb 23, 2009: GRASS 6.4 release branch split off from GRASS 6 development branch
  • Apr 03, 2009: GRASS GIS 6.4 preparations starting…
  • Feb 24, 2010: Intense maintenance in GRASS 6.4 release branch
  • Sep 15, 2010: GRASS GIS 6.4.0 released in September 2010
  • Apr 12, 2011: GRASS GIS 6.4.1 released in April 2011
  • Jun 27, 2011: GRASS GIS 6.4.svn matures for the upcoming 6.4.2 release
  • Aug 16, 2011: Intense maintenance in GRASS 6.4 release branch (GRASS GIS 7 development not shown here)…
  • Feb 19, 2012: GRASS GIS 6.4.2 released in February 2012
  • Nov 13, 2012: Backporting graphical user interface bugfixes from GRASS GIS 7 to GRASS GIS 6.4
  • Apr 17, 2013: Further maintenance in GRASS 6.4 release branch
  • Jul 10, 2013: Fixing odds ‘n ends for the new stable release
  • Jul 27, 2013: GRASS GIS 6.4.3 released in July 2013

The corresponding timeline is also available at
http://grass.osgeo.org/home/history/releases/

THANKS TO ALL CONTRIBUTORS!
http://grass.osgeo.org/development/

Rendering: Markus Neteler
Audio track editing: Duccio Rocchini & Antonio Galea

Music:
Le bruit peut rendre sourd – Track 6/18 Album “Sensation electronique” by Saelynh (CC-BY-NC-ND) http://www.jamendo.com/en/track/1236/le-bruit-peut-rendre-sourd

Software used:
Gource software: http://code.google.com/p/gource/ (GPL)
OpenShot video editor: http://www.openshotvideo.com/ (GPL

Using the 25m EU-DEM for shading OpenStreetMap layers

Inspired by Václav Petráš posting about “Did you know that you can see streets of downtown Raleigh in elevation data from NC sample dataset?” I wanted to try the new GRASS GIS 7 Addon r.shaded.pca which creates shades from various directions and combines then into RGB composites just to see what happens when using the new EU-DEM at 25m.

To warm up, I registered the “normally” shaded DEM (previously generated with gdaldem) with r.external in a GRASS GIS 7 location (EPSG 3035, LAEA) and overlayed the OpenStreetMap layer using WMS with GRASS 7′s r.in.wms. An easy task thanks to University of Heidelberg’s www.osm-wms.de. Indeed, they offer a similar shading via WMS, however, in the screenshot below you see the new EU data being used for controlling the light on our own:

OpenStreetMap shaded with EU DEM 25m

OpenStreetMap shaded with EU DEM 25m (click to enlarge)

Next item: trying r.shaded.pca… It supports multi-core calculation and the possibility to strengthen the effects through z-rescaling. In my example, I used:

r.shaded.pca input=eu_dem_25 output=eu_dem_25_shaded_pca nproc=3 zmult=50

The leads to a colorized hillshading map, again with the OSM data on top (50% transparency):

eu_dem_25m_PCA_shaded_OSM_trento_rovereto_garda_lake

OpenStreetMap shaded with r.shaded.pca using EU DEM 25m (click to enlarge)

Yes, fun – I like it :-)

Data sources:

EU-DEM: new Digital Surface Model at 25m

eu_dem_upper_garda_lake_riva_arco_italy

EU DEM 25m upper Garda Lake area with Riva del Garda and Arco (Italy). 3D view in wxNVIZ – GRASS GIS 7

The 25m European Digital Elevation Model (EU-DEM, Version 1) is a Digital Surface Model (DSM) representing the first surface as illuminated by the sensors:

eu_dem_s_michele_rotaliana_italy

EU DEM Rotaliana with Mezzocorona and S. Michele (Italy). Produced using Copernicus data and information funded by the European Union – EU-DEM layers.

Its elevations were captured at 1 arc second postings (2.78E-4 degrees). The tiles are provided at 25m resolution in EU-LAEA (EPSG. 3035) projection, temporal coverage: 2000, published in Oct 2013. It is a realisation of the Copernicus programme, managed by the European Commission, DG Enterprise and Industry. Metadata are provided here. According to their “Methodology” page it is a hybrid product based on SRTM and ASTER GDEM data fused by a weighted averaging approach and it has been generated as a contiguous dataset divided into 1 degree by 1 degree tiles, corresponding to the SRTM naming convention. In addition to the DEM data, a colour shaded relief image over Europe is provided.

From the metadata page: “The EU-DEM data are provided as is, i.e. without a formal validation yet. An independent statistical validation is scheduled as part of the GIO land monitoring service activities, and will be made available in the course of 2014.

1. Data download

Note that the GeoTIFF files are of major size, up to 5 GB:

Hint for GRASS GIS users: instead of importing the data, you can use r.external to simply register the GeoTIFF file within a EU LAEA projected location.

eu_dem_trento_adige_s_michele_italy

News in GRASS GIS 7

GRASS GIS, commonly referred to as GRASS (Geographic Resources Analysis Support System), is the free Geographic Information System (GIS) software with the longest record of development as FOSS4G community project. The increasing demand for a robust and modern analytical free GIS led to the start of GRASS GIS 7 development in April 2008. Since GRASS 6 more than 10,000 changes have been implemented with a series of new modules for vector network analysis, image processing, voxel analysis, time series management and improved graphical user interface. The core system offers a new Python API and large file support for massive data analysis. Many modules have been undergone major optimization also in terms of speed. The presentation will highlight the advantages for users to migrate to the upcoming GRASS GIS 7 release.

50th ICA-OSGeo Lab established at Fondazione Edmund Mach (FEM)

We are pleased to announce that the 50th ICA-OSGeo Lab has been established at the GIS and Remote Sensing Unit (Piattaforma GIS & Remote Sensing, PGIS), Research and Innovation Centre (CRI), Fondazione Edmund Mach (FEM), Italy. CRI is a multifaceted research organization established in 2008 under the umbrella of FEM, a private research foundation funded by the government of Autonomous Province of Trento. CRI focuses on studies and innovations in the fields of agriculture, nutrition, and environment, with the aim to generate new sharing knowledge and to contribute to economic growth, social development and the overall improvement of quality of life.

The mission of the PGIS unit is to develop and provide multi-scale approaches for the description of 2-, 3- and 4-dimensional biological systems and processes. Core activities of the unit include acquisition, processing and validation of geo-physical, ecological and spatial datasets collected within various research projects and monitoring activities, along with advanced scientific analysis and data management. These studies involve multi-decadal change analysis of various ecological and physical parameters from continental to landscape level using satellite imagery and other climatic layers. The lab focuses on the geostatistical analysis of such information layers, the creation and processing of indicators, and the production of ecological, landscape genetics, eco-epidemiological and physiological models. The team pursues actively the development of innovative methods and their implementation in a GIS framework including the time series analysis of proximal and remote sensing data.

The GIS and Remote Sensing Unit (PGIS) members strongly support the peer reviewed approach of Free and Open Source software development which is perfectly in line with academic research. PGIS contributes extensively to the open source software development in geospatial (main contributors to GRASS GIS), often collaborating with various other developers and researchers around the globe. In the new ICA-OSGeo lab at FEM international PhD students, university students and trainees are present.

PGIS is focused on knowledge dissemination of open source tools through a series of courses designed for specific user requirement (schools, universities, research institutes), blogs, workshops and conferences. Their recent publication in Trends in Ecology and Evolution underlines the need on using Free and Open Source Software (FOSS) for completely open science. Dr. Markus Neteler, who is leading the group since its formation, has two decades of experience in developing and promoting open source GIS software. Being founding member of the Open Source Geospatial Foundation (OSGeo.org, USA), he served on its board of directors from 2006-2011. Luca Delucchi, focal point and responsible person for the new ICA-OSGeo Lab is member of the board of directors of the Associazione Italiana per l’Informazione Geografica Libera (GFOSS.it, the Italian Local Chapter of OSGeo). He contributes to several Free and Open Source software and open data projects as developer and trainer.

Details about the GIS and Remote Sensing Unit at http://gis.cri.fmach.it/

Open Source Geospatial Foundation (OSGeo) is a not-for-profit organisation founded in 2006 whose mission is to support and promote the collaborative development of open source geospatial technologies and data.

International Cartographic Association (ICA) is the world authoritative body for cartography and GIScience. See also the new ICA-OSGeo Labs website.

Processing Landsat 8 data in GRASS GIS 7: RGB composites and pan sharpening

banner_pansharpening

In our first posting (“Processing Landsat 8 data in GRASS GIS 7: Import and visualization“) we imported a Landsat 8 scene (covering Raleigh, NC, USA). In this exercise we use Landsat data converted to reflectance with i.landsat.toar as shown in the first posting.

Here we will try color balancing and pan-sharpening, i.e. applying the higher resolution panchromatic channel to the color channels, using i.landsat.rgb.

1. Landsat 8 – RGB color balancing: natural color composites

After import, the RGB (bands 4,3,2 for Landsat 8) may look initially less exciting than expected.This is easy to fix by a histogram based auto-balancing of the RGB color tables.

landsat8_rgb_composite_unbalanced

To brighten up the RGB composite, we can use the color balancing tool of GRASS GIS 7:

grass7_landsat_rgb0

As input, we specify the bands 4, 3, and 2:

grass7_landsat_rgb1

Using a “Cropping intensity (upper brightness level)” of 99 (percent), the result look as follows:

landsat10_rgb_composite_autobalance_99percent_crop

For special purposes or under certain atmospheric/ground conditions it may be useful to make use of the functions “Preserve relative colors, adjust brightness only” or “Extend colors to full range of data on each channel” in the “Optional” tab of i.landsat.rgb.

landsat9_rgb_composite_preserve_relative_colors

You will need to experiment since the results depend directly on the image data.

2. Landsat 8 pansharpening

Pansharpening is a technique to merge the higher geometrical pixel resolution of the panchromatic band (Band 8) with the lower resolution color bands (Bands 4, 3, 2).

GRASS GIS 7 offers several methods through the command i.pansharpen.

1) Brovey transform:

landsat8_pansharpen_brovey1

This module runs in multi-core mode parallelized. The management of the resolution (i.e., apply the higher resolution of the panchromatic band) is performed automatically.

landsat8_pansharpen_brovey2

2. IHS transform

Here we select as above the bands in the i.pansharpen interface but use the “ihs” method.

landsat8_pansharpen_ihs1

HINT: If the colors should look odd, then apply i.landsat.rgb to the pan-sharpened bands (see above).

Color-adjusted IHS pansharpening (with “Cropping intensity: strength=99″):

landsat8_pansharpen_ihs_color_adjusted

Comparison of Landsat 8 RGB composite (39m) and IHS pansharpened RGB composite (15m):

landsat8_rgb432_color_adjusted_zoom landsat8_rgb432_pansharpen_ihs_color_adjusted_zoom

3. PCA transform

Here we select as above the bands in the i.pansharpen interface but use the “pca” method.

landsat8_pansharpen_pca1

Likewise other channels may be merged with i.pansharpen, even when originating from different sensors.

3. Conclusions

Overall, the IHS pansharpening method along with auto-balancing of colors appears to perform very well with Landsat 8.

Processing Landsat 8 data in GRASS GIS 7: Import and visualization

banner_landsat_rgb

For our analysis example, we’ll obtain (freely – thanks, NASA and USGS!) a Landsat 8 scene from http://earthexplorer.usgs.gov/

First of all, you should register.

1. Landsat 8 download procedure

1. Enter Search Criteria:

  • path/row tab, enter Type WRS2: Path: 16, Row: 35
  • Date range: 01/01/2013 – today
  • Click on the “Data sets >>” button

2. Select Your Data Set(s):

  • Expand the entry + Landsat Archive
        [x] L8 OLI/TIRS
  • Click on the “Results >>” button

(We jump over the additional criteria)

4. Search Results

From the resulting list, we pick the data set:

earthexplorer_selection_lsat8Entity ID: LC80160352013134LGN03
Coordinates: 36.04321,-79.28696
Acquisition Date: 14-MAY-13

Using the “Download options”, you can download the data set (requires login). Select the choice:
[x] Level 1 GeoTIFF Data Product (842.4 MB)

You will receive the file “LC80160352013134LGN03.tar.gz”.

2. Unpacking the downloaded Landsat 8 dataset

To unpack the data, run (or use a graphical tool at your choice):

tar xvfz LC80160352013134LGN03.tar.gz

A series of GeoTIFF files will be extracted: LC80160352013134LGN03_B1.TIF, LC80160352013134LGN03_B2.TIF, LC80160352013134LGN03_B3.TIF, LC80160352013134LGN03_B4.TIF, LC80160352013134LGN03_B5.TIF, LC80160352013134LGN03_B6.TIF, LC80160352013134LGN03_B7.TIF, LC80160352013134LGN03_B8.TIF, LC80160352013134LGN03_B9.TIF, LC80160352013134LGN03_B10.TIF, LC80160352013134LGN03_B11.TIF, LC80160352013134LGN03_BQA.TIF

We may check the metadata with “gdalinfo“:

gdalinfo LC80160352013134LGN03_B1.TIF
Driver: GTiff/GeoTIFF
Files: LC80160352013134LGN03_B1.TIF
Size is 7531, 7331
Coordinate System is:
PROJCS["WGS 84 / UTM zone 17N",
    GEOGCS["WGS 84",
        DATUM["WGS_1984",
            SPHEROID["WGS 84",6378137,298.257223563,
...
Pixel Size = (30.000000000000000,-30.000000000000000)
...

3. Want to spatially subset the Landsat scene first?

If you prefer to cut out a smaller area (subregion), check here for gdal_translate usage examples.

4. Import into GRASS GIS 7

Note: While this Landsat 8 scene covers the area of the North Carolina (NC) sample dataset, it is delivered in UTM rather than the NC's state plane metric projection. Hence we preprocess the data first in its original UTM projection prior to the reprojection to NC SPM.

Using the Location Wizard, we can import the dataset easily into a new location (in case you don't have UTM17N not already created earlier):

grass70 -gui

grass7_loc_wizard1
grass7_loc_wizard2
grass7_loc_wizard3
grass7_loc_wizard4
grass7_loc_wizard5
grass7_loc_wizard6
grass7_loc_wizard7
grass7_loc_wizard8
grass7_loc_wizard9

 

 

 

Now start GRASS GIS 7 and you will find the first band already imported (the others will follow shortly!).

For the lazy folks among us, we can also create a new GRASS GIS Location right away from the dataset on command line:

grass70 -c LC80160352013134LGN03_B10.TIF ~/grassdata/utm17n

5. Importing the remaining Landsat 8 bands

The remaining bands can be easily imported with the raster import tool:

grass7_import1

The bands can now be selected easily for import:

grass7_import2

  • Select "Directory" and navigate to the right one
  • The available GeoTIFF files will be shown automatically
  • Select those you want to import
  • You may rename (double-click) the target name for each band
  • Extend the computation region accordingly automatically

Click on "Import" to get the data into the GRASS GIS location. This takes a few minutes. Close the dialog window then.

In the "Map layers" tab you can select the bands to be shown:

grass7_visualize1

6. The bands of Landsat 8

(cited from USGS)

Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) images consist of nine spectral bands with a spatial resolution of 30 meters for Bands 1 to 7 and 9. New band 1 (ultra-blue) is useful for coastal and aerosol studies. New band 9 is useful for cirrus cloud detection. The resolution for Band 8 (panchromatic) is 15 meters. Thermal bands 10 and 11 are useful in providing more accurate surface temperatures and are collected at 100 meters. Approximate scene size is 170 km north-south by 183 km east-west (106 mi by 114 mi).

Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS)Launched February 11, 2013 Bands Wavelength (micrometers) Resolution (meters)
Band 1 - Coastal aerosol 0.43 - 0.45 30
Band 2 - Blue 0.45 - 0.51 30
Band 3 - Green 0.53 - 0.59 30
Band 4 - Red 0.64 - 0.67 30
Band 5 - Near Infrared (NIR) 0.85 - 0.88 30
Band 6 - SWIR 1 1.57 - 1.65 30
Band 7 - SWIR 2 2.11 - 2.29 30
Band 8 - Panchromatic 0.50 - 0.68 15
Band 9 - Cirrus 1.36 - 1.38 30
Band 10 - Thermal Infrared (TIRS) 1 10.60 - 11.19 100
Band 11 - Thermal Infrared (TIRS) 2 11.50 - 12.51 100

* TIRS bands are acquired at 100 meter resolution, but are resampled to 30 meter in delivered data product.

7. Natural color view (RGB composite)

Due to the introduction of a new "Cirrus" band (#1), the BGR bands are now 2, 3, and 4, respectively. See also "Common band combinations in RGB" for Landsat 7 or Landsat 5, and Landsat 8.

From Digital Numer (DN) to reflectance:
Before creating an RGB composite, it is important to convert the digital number data (DN) to reflectance (or optionally radiance). Otherwise the colors of a "natural" RGB composite do not look convincing but rather hazy (see background in the next screenshot). This conversion is easily done using the metadata file which is included in the data set with i.landsat.toar:

grass7_landsat_toar0
grass7_landsat_toar1
grass7_landsat_toar2
grass7_landsat_toar3

Now we are ready to create a nice RGB composite:

grass7_landsat_rgb0

grass7_landsat_rgb1

Select the bands to be visually combined:

grass7_visualize2

... and voilà!

grass7_landsat_rgb2

8. Applying the Landsat 8 Quality Assessment (QA) Band

One of the bands of a Landsat 8 scene is named "BQA" which contains for each pixel a decimal value representing a bit-packed combination of surface, atmosphere, and sensor conditions found during the overpass.  It can be used to judge the overall usefulness of a given pixel.

We can use this information to easily eliminate e.g. cloud contaminated pixels. In short, the QA concept is (cited here from the USGS page):

Cited from http://landsat.usgs.gov/L8QualityAssessmentBand.php‎

For the single bits (0, 1, 2, and 3):
0 = No, this condition does not exist
1 = Yes, this condition exists.

The double bits (4-5, 6-7, 8-9, 10-11, 12-13, and 14-15) represent levels of confidence that a condition exists:
00 = Algorithm did not determine the status of this condition
01 = Algorithm has low confidence that this condition exists (0-33 percent confidence)
10 = Algorithm has medium confidence that this condition exists (34-66 percent confidence)
11 = Algorithm has high confidence that this condition exists (67-100 percent confidence).

Detailed bit patterns (d: double bits; s: single bits):
d  Bit 15 = 0 = cloudy
d  Bit 14 = 0 = cloudy
d  Bit 13 = 0 = not a cirrus cloud
d  Bit 12 = 0 = not a cirrus cloud
d  Bit 11 = 0 = not snow/ice
d  Bit 10 = 0 = not snow/ice
d  Bit 9 = 0 = not populated
d  Bit 8 = 0 = not populated
d  Bit 7 = 0 = not populated
d  Bit 6 = 0 = not populated
d  Bit 5 = 0 = not water
d  Bit 4 = 0 = not water
s  Bit 3 = 0 = not populated
s  Bit 2 = 0 = not terrain occluded
s  Bit 1 = 0 = not a dropped frame
s  Bit 0 = 0 = not fill

Usage example 1:  Creating a mask from a bitpattern

We can create a cloud mask (bit 15+14 are set) from this pattern:
cloud:   1100000000000000

Using the Python shell tab, we can easily convert this into the corresponding decimal number for r.mapcalc:

Cited from http://landsat.usgs.gov/L8QualityAssessmentBand.php‎

Welcome to wxGUI Interactive Python Shell 0.9.8

Type "help(grass)" for more GRASS scripting related information.
Type "AddLayer()" to add raster or vector to the layer tree.

Python 2.7.5 (default, Aug 22 2013, 09:31:58) 
[GCC 4.8.1 20130603 (Red Hat 4.8.1-1)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> int(0b1100000000000000)
49152

Using this decimal value of 49152, we can create a cloud mask:

# set NULL for cloudy pixels, 1 elsewhere:
r.mapcalc "cloudmask = if(LC80160352013134LGN03_BQA == 49152, null(), 1 )"

# apply this mask
r.mask cloudmask

In our sample scene, there are only tiny clouds in the north-east, so no much to be seen. Some spurious cloud pixels are scattered over the scene, too, which could be eliminated (in case of false positives) or kept.

Usage example 2:  Querying the Landsat 8 BQA map and retrieve the bitpattern

Perhaps you prefer to query the BQA map itself (overlay the previously created RGB composite and query the BSA map by selecting it in the Layer Manager). In our example, we query the BQA value of the cloud:

Using again the Python shell tab, we can easily convert the decimal number (used for r.mapcalc) into the corresponding binary representation to verify with the  table values above.

>>> x=61440
>>> print(bin(x & 0xffffffff))
0b1111000000000000

Hence, bits 15,14,13, and 12 are set: cloudy and not a cirrus cloud. Looking at the RGB composite we tend to agree :-) Time to mask out the cloud!

wxGUI menu >> Raster >> Mask [r.mask]

Or use the command line, as shown already above:

# remove existing mask (if active)
r.mask -r

# set NULL for cloudy pixels, 1 elsewhere:
r.mapcalc "cloudmask = if(LC80160352013134LGN03_BQA == 61440, null(), 1 )" --o

# apply the new mask
r.mask cloudmask

The visual effect in the RGB composite is minimal since the cloud is white anyway (as NULL cells, too). However, it is relevant for real calculations such as NDVI (vegetation index) or thermal maps.

We observe dark pixels around the cloud originating from thin clouds. In a subsequent identification/mask step we may eliminate also those pixels with a subsequent filter.

Compiling QGIS 2.0.1 for Fedora 19 in a few steps

Thanks to Volker Fröhlich’s efforts, a source code RPM package (SRPM) of QGIS 2.0.1 is now available for Fedora. If you are not yet F20 user (like me), you can just take the F20 package and compile it for F19 (or even F18) since there will be no backport of QGIS 2 to F19 (it comes with QGIS 1.8). But: we do want QGIS 2 on Fedora19!

Solution: compile it yourself.

1. 1. Preparations

The best way is  to use “mock” which is used to recompile SRPMS in a separate local environment (“chroot”) without cluttering the system with extra packages needed for the compilation (run as “root”):

su
yum install mock

2. 2. Get the source code

Next download the SRPM package from the Koji  server:
QGIS:  http://koji.fedoraproject.org/koji/buildinfo?buildID=467757 (–> src – download) or check here for more recent versions.

3. 3. Compile it locally as RPM package

The general compilation command (“mock”) would be:

mock -r my_fedora_version_config --rebuild my_source_rpm.src.rpm

So, check for Fedora version config name which is suitable for your system (“my_fedora_version_config“)

ls /etc/mock/

In my case of a 64bit machine, it is “fedora-19-x86_64″. Hence we can compile QGIS 2.0.1 directly from the SRPM file:

mock -r fedora-19-x86_64 --rebuild qgis-2.0.1-2.fc20.src.rpm

Note: the compilation takes 40min on my tiny core i3 laptop (ASUS X202). Use the time to donate some coins to the QGIS project :-)

4. 4. Install and enjoy

Once the compilation job is done, i.e. the binary RPM files are available for installation. To install the freshly compiled QGIS 2.0.1 RPMs, run:

cd /var/lib/mock/fedora-19-x86_64/result/

# an existing QGIS1.8 installation will be replaced: 
yum localinstall qgis-2.0.1-2.fc19.x86_64.rpm \
qgis-grass-2.0.1-2.fc19.x86_64.rpm qgis-python-2.0.1-2.fc19.x86_64.rpm

# consider to cleanup (or keep it for the next update, it is about 1.5GB):
rm -rf /var/lib/mock/fedora-19-x86_64/
# leave the "root" shell
exit

Now we can happily use QGIS 2.0.1 on Fedora 19!

qgis

qgis201_on_fedora19

GFOSS DAY 2013 a Bologna: 10-11 Ottobre 2013

Dal 10 al 11 Ottobre 2013 si terrà a Bologna presso i laboratori della Scuola di Ingegneria e Architettura (V.le del Risorgimento, 2), e le sale conferenze della Regione Emilia-Romagna (V.le della Fiera, 8), la sesta conferenza italiana sul software geografico e sui dati geografici liberi (GFOSS DAY 2013).

Lo scopo principale della conferenza è quello di coinvolgere imprese, enti pubblici, scuole, università, centri di ricerca, sviluppatori, cittadini, operatori del settore ed appassionati dei temi del software libero geografico e degli open data.

Sarà inoltre possibile seguire in diretta streaming il convegno.

Registrati:

http://www.gfoss.it/drupal/gfossday2013/registrazione

La partecipazione alla conferenza è libera e gratuita ma è richiesta una registrazione (meglio anticipata) per consentire una migliore organizzazione dell’evento e garantire la stampa di badge e attestati.

L’accesso ai workshop è garantito fino al raggiungimento numero massimo di partecipanti.

Section 1. Programma

http://www.gfoss.it/drupal/gfossday2013/programma

Section 2. Sede della conferenza

http://www.gfoss.it/drupal/gfossday2013/locations

Parteciperete a #gfoss13? Ditelo al mondo!

Allegato Dimensione
Locandina_GFOSSDAY13.pdf 3.13 MB

Call for Papers FOSSGIS 2014 in Berlin

(reposting from here, Note to English speakers below)FOSSGIS Konferenz 2014 Berlin 19. - 21. März 2014

Sie forschen, Sie entwickeln, Sie beschäftigen sich mit Open-Source-Geo-Software oder freien Geodaten? Sie haben neue Ideen in diesem Themenbereich oder sind bereits dabei, freie Software und freie Geodaten zu nutzen oder zu entwickeln? Dann sind Sie auf unserer Konferenz – der FOSSGIS-Konferenz 2014 - genau richtig.

WIR BIETEN: Eine Plattform für Ihre Idee, Ihr Projekt, Ihren Erfahrungsbericht auf der größten deutschsprachigen Anwenderkonferenz für freie Geoinformationssysteme und freie Geodaten. Im Jahr 2014 findet die FOSSGIS vom 19. bis 21. März auf dem Gelände der Beuth Hochschule für Technik in Berlin statt. Wir rechnen mit über 400 Teilnehmern. An der Konferenz 2013 in Rapperswil (Schweiz) nahmen über ca. 350 Besucher teil.

WIR SUCHEN: Ihre Idee. Ihr Projekt. Ihren Erfahrungsbericht. Ihr Thema. Genauer gesagt, suchen wir Vorträge für Einsteiger und Fortgeschrittene, um spannende Themen zu behandeln, Diskussionen zu entwickeln, praxisorientierte Workshops* runden unser Programm ab. Vorträge zum Thema freie Geodaten, zum Beispiel OpenStreetMap, Open Data sind ebenso möglich wie Beiträge zu beispielsweise Softwarelösungen aus dem Bereich WebGIS, Desktop GIS, Geodatenbanken oder Location-Based-Services. Bewerben Sie sich jetzt mit einem Vortrag, Lightning Talk oder Workshop* beim Call for Papers.

ABSTRACT: Die Einreichung eines Abstracts für die FOSSGIS 2014 ist ab sofort bis zum 15. November 2013 über unsere Konferenzsoftware Pentabarf möglich. Beitrags-Einreichungen ohne Abstract müssen leider abgelehnt werden, da sich das Programm-Komitee anhand des Abstracts ein Bild von Inhalt und Relevanz des Beitrags macht. Der Abstract sollte ca. 1500 Zeichen umfassen. Ob die Einreichung angenommen wurde, wird im Dezember 2013 bekanntgegeben. Es besteht die Möglichkeit einen Lightning Talk einzureichen. Ein Lightning Talk ist eine kurze, knackige Auseinandersetzung mit einem Thema, welches in 5 Minuten, gern humorvoll, Anregung zur Diskussion bietet. Weiterhin können Poster eingereicht werden.

*Workshops: Bitte berücksichtigen Sie bei der Planung, dass für die Workshops nur 90 Minuten vorgesehen sind und die Teilnehmer ein Mix aus Theorie und vor allem Praxis erwarten. Die Beschreibung des Workshops soll erreichbare Lernziele und die notwendigen Vorkenntnisse der Teilnehmer enthalten. Ein Workshop findet ab einer Teilnehmerzahl von 5 statt.

WER WIR SIND: Veranstaltet wird die Konferenz vom FOSSGIS e.V., von der OSGeo Foundation und der Beuth Hochschule für Technik Berlin.

Unsere Konferenz lebt von Ihren Beiträgen und Ihrem Besuch. Werden Sie Teil der Konferenz – wir freuen uns auf Sie!

Noch Fragen? Wir haben versucht, in unseren FAQs alle wichtigen Fragen zu beantworten. Falls weitere Fragen bestehen, zögern Sie nicht uns eine E-Mail zu schreiben.

Note to English speakers

The FOSSGIS-conference is the largest German-language conference for Free and Open Source Software for GIS and Free Geodata hosting about 400 participants.

Today, the Conference Committee announced the “Call for papers” for 2014. Because the conference-language is German, the CfP is either.

The program committee will, however, also consider applications for talks or workshops held in English if they are deeemed to add to the quality of the conference. So if you don’t speak German, but are a FOSS/Open Data celebrity, or have a story that only you can tell, please do submit your talk. We are unlikely to be able to provide interpreters, but we’ll make sure you don’t get lost in Berlin. Please be aware that you can submit paper until November, 15. 2013. You can submit your abstract using our Conference Software.

We are looking forward to see you in Berlin March 19-21, 2014!

OSGeo Receives 501(c)(4) Tax Exempt Status

The Open Source Geospatial Foundation (OSGeo) is pleased to announce that the U.S. Internal Open Source Geospatial FoundationRevenue Service (IRS) has accepted their application (PDF) for non-profit status under section 501(c)(4) of the tax code. Our 501(c)(4) status declares that OSGeo is a Social Welfare Organization. This determination affirms OSGeo’s role in serving the public through their mission, focused around Open Source Geospatial software.

This determination helps ensure that the organization will not have to pay US federal taxes on money accumulated toward the fulfilment of their mission. Unfortunately, unlike a 501(c)(3) (Charitable) status, this does not allow financial contributors to OSGeo to treat the contributions as a charitable contribution which can have a tax benefit for US tax payers. There should still be no problem with commercial organizations treating contributions to OSGeo as a business expense.

OSGeo owes a special debt to past Executive Director Tyler Mitchell, and current Treasurer Daniel Morissette who have carried this process to a successful conclusion after several years of work. Current OSGeo President, Jeff McKenna, says “Both Daniel and Tyler should be thanked by the entire community for their dedication to such a challenging task. Our future foundation events, and OSGeo in general, will benefit from their hard work for years to come.”

About the Open Source Geospatial Foundation

The Open Source Geospatial Foundation, or OSGeo, is a not-for-profit organization founded in 2006 whose mission is to support and promote the collaborative development of open geospatial technologies and data.  The Foundation provides financial, organizational and legal support to the broader open source geospatial community. It also serves as an independent legal entity to which community members can contribute code, funding and other resources, secure in the knowledge that their contributions will be maintained for public benefit.

OSGeo Board Election 2013 Results

On 7th Sep 2013 the final results from the 2013 elections for the open seats of the OSGeo Board of Directors have been published. There were four seats open and they have been filled by (in no particular order):

Thanks to all candidates for going through the elections and exposing themselves. All six candidates received excellent support with more then 60 votes each. Overall voting participation was 72% (129 out of 180) and there were no tie scores to arbitrate. Thanks to all Charter Members who voted!

The complete resulting OSGeo Board is:

With the election results published the new board of directors becomes immediately effective.

OSGeo wishes to thank the outgoing directors for their continued support of OSGeo and for helping to run a fantastic organizations with a great membership and lots of energy. We thank all candidates who stood in this election and all OSGeo Charter Members for their contribution and votes.

OSGeo-Live 7.0 Released

The OSGeo-Live geospatial software collection version 7.0 has been released, featuring more than sixty open source, standards compliant geospatial desktop applications, web applications and frameworks. A complete installation kit and high-quality sample data in multiple industry standard formats are included. The OSGeo Live will be officially launched at FOSS4G 2013 in Nottingham, UK, 17-21 September, 2013.

Release Highlights

Projects new to this release include:

  • GeoNode — a web-based application and platform for developing geospatial information systems (GIS) and for deploying spatial data infrastructures (SDI)
  • Leaflet — a modern, open source JavaScript library for mobile-friendly interactive maps
  • ncWMS — a Web Map Service (WMS) for geospatial data stored in CF-compliant NetCDF files
  • netCDF dataset — daily maximum temperature and rainfall, worldwide

All geospatial applications on the disc have been updated to their latest stable releases.

About OSGeo-Live

OSGeo-Live is a self-contained bootable DVD, USB flash drive and Virtual Machine based upon Ubuntu Linux (version 12.04 LTS). OSGeo-Live is pre-configured with a wide variety of robust open source geospatial software. All applications can be trialled without installing anything on your computer, simply by booting the computer from a DVD or USB drive, or running in a Virtual Machine environment. Each featured package is accompanied by both a publication quality one page descriptive summary and a short tutorial on how to get started using it.

http://live.osgeo.org

OSGeo-Live includes:

  • Over sixty quality geospatial Open Source applications installed and pre-configured
  • Free world maps and geodata
  • One page overview and quick start guide for every application
  • Overviews of key OGC standards
  • Translations to multiple languages

Credits

Over 160 people have directly helped with OSGeo-Live packaging, documenting and translating, and thousands have been involved in building the packaged software.

Packagers, documenters and translators include:

Activity Workshop, Agustín Dí­ez, Aikaterini Kapsampeli, Alan Beccati, Alan Boudreault, Alessandro Furieri, Alexander Bruy, Alexander Kleshnin, Alexander Muriy, Alexandre Dube, Alexey Ardyakov, Alex Mandel, Amy Gao, Andrea Antonello, Andrea Yanza, Andrey Syrokomskiy, Andry Rustanto, Angelos Tzotsos, Anna Muñoz, Antonio Falciano, Anton Novichikhin, Anton Patrushev, Argyros Argyridis, Ariel Núñez, Assumpció Termens, Astrid Emde, Barry Rowlingson, Benjamin Pross, Brian Hamlin, Bruno Binet, Cameron Shorter, Christophe Tufféry, Christos Iossifidis, Cristhian Pin, Damian Wojsław, Dane Springmeyer, Daniel Kastl, Daria Svidzinska, David Mateos, Denis Rykov, Diego González, Diego Migliavacca, Dimitar Misev, Dmitry Baryshnikov, Dominik Helle, Edgar Soldin, Eike Hinderk Jürrens, Elena Mezzini, Eric Lemoine, Estela Llorente, Etienne Delay, Etienne Dube, Evgeny Nikulin, Fran Boon, François Prunayre, Frank Gasdorf, Frank Warmerdam, Friedjoff Trautwein, Gavin Treadgold, Giuseppe Calamita, Gerald Fenoy, Grigory Rozhentsov, Guy Griffiths, Hamish Bowman, Haruyuki Seki, Henry Addo, Hernan Olivera, Howard Butler, Hyeyeong Choe, Ian Edwards, Ian Turton, Ilya Filippov, Jackie Ng, Jan Drewnak, Jane Lewis, Javier Rodrigo, Javier Sánchez, Jesús Gómez, Jim Klassen, Jing Wang, Jinsongdi Yu, Jody Garnett, Johan Van de Wauw, John Bryant, Jorge Arévalo, Jorge Sanz, José Antonio Canalejo, José Vicente Higón, Judit Mays, Klokan Petr Pridal, Kristof Lange, kuzkok, Lance McKee, Lars Lingner, Luca Delucchi, Lucía Sanjaime, Mage Whopper, Manuel Grizonnet, Marc-André Barbeau, Marco Curreli, Marco Puppin, Marc Torres, Margherita Di Leo, Maria Vakalopoulou, Mario Andino, Mark Leslie, Massimo Di Stefano, Mauricio Miranda, Mauricio Pazos, Maxim Dubinin, Michaël Michaud, Michael Owonibi, Micha Silver, Mike Adair, Milena Nowotarska, M Iqnaul Haq Siregar, Nacho Varela, Nadiia Gorash, Nathaniel V. Kelso, Ned Horning, Nobusuke Iwasaki, Oliver Tonnhofer, Òscar Fonts, Otto Dassau, Pasquale Di Donato, Patric Hafner, Paul Meems, Pavel, Pedro-Juan Ferrer, Pirmin Kalberer, Raf Roset, Ricardo Pinho, Roald de Wit, Roberta Fagandini, Roberto Antolin, Roberto Antolí­n, Roger Veciana, Ruth Schoenbuchner, Samuel Mesa, Scott Penrose, Sergey Grachev, Sergio Baños, Simon Cropper, Simon Pigot, Stefan A. Tzeggai, Stefan Hansen, Stefan Steiniger, Stephan Meissl, Steve Lime, Thierry Badard, Thomas Baschetti, Thomas Gratier, Tom Kralidis, Toshikazu Seto, Trevor Wekel, Valenty González, Vera, Xianfeng Song, Yoichi Kayama, Zhengfan Lin

Sponsoring organisations

 

4th GRASS GIS Community Sprint: Exciting achievements

The GRASS GIS community is delighted to present the outcome of the 4th Community Sprint that took place in a warm and sunny Prague, Czech Republic, from July 12 to July 18, 2013. The event happened after the Geoinformatics conference at the Czech Technical University in Prague. The Community Sprint was once more a creative gathering of both long-term and new developers, as well as users.
This meeting was held in the light of 30 YEARS OF GRASS GIS!

30 YEARS OF GRASS GIS!
We wish to cordially thank the Department of Mapping and Cartography, Faculty of Civil Engineering, Czech Technical University in Prague for hosting and technical support. In particular, we gratefully acknowledge our association sponsors OSGeo  and FOSSGIS e.V., and many individual donors: Peter Löwe, Andrea Borruso, Massimo Di Stefano, Alessandro Sarretta, Joshua Campbell, Andreas Neumann, Jon Eiriksson, Luca Casagrande, Karyn O Newcomb, Holger Naumann, Anne Ghisla, Helena Mitasova and Lubos Mitas, Dimitris Tamp, Mark Seibel, Markus Metz, and Tawny Gapinski. These financial contributions were used to cover costs such as meals and to help reducing travelling and accommodation expenses for participants with far arrival who came on own expenses.

Developers and users who joined the event came from various countries like Italy, Czech Republic, Slovak Republic, Poland, Sri Lanka/France, USA and Germany.
The Community Sprint focused on:

  • testing/bugfixing of the upcoming GRASS 7 version,
  • backporting new functionalities to the stable GRASS 6.4 series,
  • testing/bugfixing related to Mac OS X, MS-Windows and Linux,
  • presenting and developing the new Temporal GIS Algebra in GRASS 7,
  • connecting GRASS 7 with the planetary science software ISIS,
  • discussing integration with rasdaman.org software, a powerful multidimensional raster processor,
  • creating 3D vector test data for 3D interpolation,
  • discussing vector conflation,
  • discussing Bundle Block Adjustments,
  • presenting the state of image processing in GRASS 7, and discussing its future,
  • improving documentation, with focus on image processing and Temporal GIS Algebra,
  • developing/refactoring and bugfixing several wxGUI’s components,
  • further developing customizable wxGUI Toolboxes concept,
  • improving translation in Polish and Romanian languages,
  • fixing v.krige in GRASS7 and proposing merge with the recently developed v.kriging module,
  • meeting between Google Summer of Code 2013 mentor and students.

A lot of topic oriented discussions happened among small groups of participants: for more detailed information, please visit the Wiki pages at http://grasswiki.osgeo.org/wiki/GRASS_Community_Sprint_Prague_2013 and the related discussion page at http://grasswiki.osgeo.org/wiki/Talk:GRASS_Community_Sprint_Prague_2013

About GRASS GIS
The Geographic Resources Analysis Support System, 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 is distributed freely under the terms of the GNU General Public License (GPL). GRASS GIS is an official project of the Open Source Geospatial Foundation (OSGeo).

GRASS GIS Development Team, July 2013

Stable GRASS GIS 6.4.3 released

GRASS GIS 6.4.3 released – Birthday release for 30 years of GRASS GIS
http://grass.osgeo.org

30 YEARS OF GRASS GIS!

We are pleased to announce the release of a new stable version of GRASS GIS. This release fixes bugs discovered in 6.4.2 version of the program and adds a number of new features. This release includes over
830 updates to the source code since 6.4.2. As a stable release series, the 6.4 line will enjoy long-term support and incremental enhancements while preserving backwards-compatibility with the entire GRASS 6 line.

Key improvements of this release include some new functionality (assistance for topologically unclean vector data), major speedup for some vector modules, fixes in the vector network modules, fixes for the wxPython based portable graphical interface (attribute table management, wxNVIZ, and Cartographic Composer). A number of new modules have been added for processing LANDSAT and MODIS satellite data, and a new vector statistics module is also introduced. Many new symbols and north arrows are available, and the user will find an improved and easier to use wizard for creating custom project locations with precise map projection and datum support. Community-contributed add-on modules are now more easily and robustly installed from an online archive. Other major developments include enhancements to the Python scripting library and numerous software-compatibility fixes and translation updates. Important is the enhanced portability for MS-Windows (native support, fixes in case of missing system DLLs). And we welcome Romanian as our twenty-fourth language!

Source code download:

Binaries download:

  • … further packages will follow shortly.

To get the GRASS GIS 6.4.3 source code directly from SVN:
svn checkout http://svn.osgeo.org/grass/grass/tags/release_20130727_grass_6_4_3

See also our detailed announcement:

  http://trac.osgeo.org/grass/wiki/Release/6.4.3-NewsFirst time users should explore the first steps tutorial after installation.

Video of GRASS GIS 6.4 development visualization from 1999 to 2013 (with soundtrack)
GRASS GIS 6.4 development visualization from 1999 to 2013 (with soundtrack)
About GRASS GIS

GRASS (Geographic Resources Analysis Support System) is a free and open source Geographic Information System (GIS) software suite used for geospatial data management and analysis, image processing, graphics and map production, spatial modeling, and 3D visualization. GRASS GIS is currently used in academic and commercial settings around the world, as well as by many governmental agencies and environmental consulting companies. GRASS GIS can be used either as a stand-alone application or as backend for other software packages such as QGIS and R geostatistics. It is a founding member of the Open Source Geospatial Foundation (OSGeo).

  • Page 1 of 2 ( 24 posts )
  • >>

Back to Top

Sponsors