Category Archives: Blog

The EuroLST seamless and gap-free daily European maps of land surface temperatures

The EuroLST dataset is seamless and gap-free with a temporal resolution of four records per day and enhanced spatial resolution of 250 m. This newly developed reconstruction method (Metz et al, 2014) has been applied to Europe and neighbouring countries, resulting in complete daily coverage from 2001 onwards. To our knowledge, this new reconstructed LST time series exceeds the level of detail of comparable reconstructed LST datasets by several orders of magnitude. Studies on emerging diseases, parasite risk assessment and temperature anomalies can now be performed on the continental scale, maintaining high spatial and temporal detail. In their paper, the authors provide examples for implications and applications of the new LST dataset, such as disease risk assessment, epidemiology, environmental monitoring, and temperature anomalies.

Reconstructed MODIS Land Surface Temperature Dataset, at 250m pixel resolution (click figure to enlarge):
MODIS lst time series reconstructed

Section 1. Article and data citation:

EuroLST has been produced by the former PGIS group at Fondazione Edmund Mach, DBEM based on daily MODIS LST (Product of NASA) maps.

Metz, M.; Rocchini, D.; Neteler, M. 2014: Surface temperatures at the continental scale: Tracking changes with remote sensing at unprecedented detail. Remote Sensing. 2014, 6(5): 3822-3840 (DOI | HTML | PDF)

Section 2. Used software

Open Source commands used in processing (GRASS GIS 7):
links to the related manual pages involved in the data preparation

  • i.pca: Principal Components Analysis (PCA) for image processing.
  • r.regression.multi: it calculates multiple linear regression from raster maps
  • v.surf.bspline: it performs bicubic or bilinear spline interpolation with Tykhonov regularization.

Furthermore:

  • r.bioclim: calculates various bioclimatic indices from monthly temperature and optional precipitation time series (install in GRASS GIS 7 with “g.extention r.bioclim”)
  • pyModis: Free and Open Source Python based library to work with MODIS data

Section 3. Metadata

Map projection: EPSG 3035, prj file
PROJCS["Lambert Azimuthal Equal Area",
    GEOGCS["grs80",
        DATUM["European_Terrestrial_Reference_System_1989",
            SPHEROID["Geodetic_Reference_System_1980",6378137,298.257222101]],
        PRIMEM["Greenwich",0],
        UNIT["degree",0.0174532925199433]],
    PROJECTION["Lambert_Azimuthal_Equal_Area"],
    PARAMETER["latitude_of_center",52],
    PARAMETER["longitude_of_center",10],
    PARAMETER["false_easting",4321000],
    PARAMETER["false_northing",3210000],
    UNIT["Meter",1]]

1. Selected open data derived from EuroLST

Section 1. BIOCLIM derived from reconstructed MODIS LST at 250m pixel resolution

BIO1: Annual mean temperature (°C*10) BIO2: Mean diurnal range (Mean monthly (max - min tem)) BIO3: Isothermality ((bio2/bio7)*100) BIO4: Temperature seasonality (standard deviation * 100) BIO5: Maximum temperature of the warmest month (°C*10) BIO6: Minimum temperature of the coldest month (°C*10) BIO7: Temperature annual range (bio5 - bio6) (°C*10) BIO10: Mean temperature of the warmest quarter (°C*10) BIO11: Mean temperature of the coldest quarter (°C*10)

BIOCLIM-like European LST maps following the “Bioclim” definition (Hutchinson et al., 2009) – derived from 10 years of reconstructed MODIS LST (download to be completed) as GeoTIFF files, 250m pixel resolution, in EU LAEA projection:

Each ZIP file contains the respective GeoTIFF file (for cell value units, see below), the color table as separate ASCII file and a README.txt with details.

Section 2. WMS/WCS Server

Using this URL, you can read the EuroLST BIOCLIM data directly via OGC WMS and WCS protocol:

http://geodati.fmach.it/production/ows_europe_lst

Section 3. OpenData License

The data published in this page are open data and released under the ODbL (Open Database License).

The full EuroLST dataset is not released online as open data (size: 18TB), please ask Luca Delucchi or Roberto Zorer for more info


2. Acknowledgments

The MOD11A1.005, MYD11A1.005 were retrieved from the online web site, courtesy of the NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, http://e4ftl01.cr.usgs.gov/

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:

  http://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 (http://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

QGIS 2.10 RPMs for Fedora 21, Centos 7, Scientific Linux 7

qgis-icon_smallThanks 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.

Repo: https://copr.fedoraproject.org/coprs/neteler/QGIS-2.10-Pisa/

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

  • qgis 2.10.1
  • qgis-debuginfo 2.10.1
  • qgis-devel 2.10.1
  • qgis-grass 2.10.1
  • qgis-python 2.10.1
  • qgis-server 2.10.1

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

su

# EPEL7:
yum install epel-release
yum update
wget -O /etc/yum.repos.d/qgis-2-10-epel-7.repo https://copr.fedoraproject.org/coprs/neteler/QGIS-2.10-Pisa/repo/epel-7/neteler-QGIS-2.10-Pisa-epel-7.repo
yum update
yum install qgis qgis-grass qgis-python

# Fedora 21:
dnf copr enable neteler/QGIS-2.10-Pisa
dnf update
dnf install qgis qgis-grass qgis-python

Enjoy!

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 (http://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
http://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

Fun with docker and GRASS GIS software

GRASS GIS and dockerSometimes, 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

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.

Enjoy.

GRASS GIS 6.4.5RC1 released

GRASS GIS logoAfter months of development a first release candidate of GRASS GIS 6.4.5 is now available. This is a stability release of the GRASS GIS 6 line.

Source code download:
http://grass.osgeo.org/grass64/source/
http://grass.osgeo.org/grass64/source/grass-6.4.5RC1.tar.gz

Binaries download:
http://grass.osgeo.org/download/software/#g64x

To get the GRASS GIS 6.4.5RC1 source code directly from SVN:
svn checkout http://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.

See also our detailed announcement:
http://trac.osgeo.org/grass/wiki/Release/6.4.5RC1-News

First time users should explore the first steps tutorial after installation:
http://grasswiki.osgeo.org/wiki/Quick_wxGUI_tutorial

Release candidate management at
http://trac.osgeo.org/grass/wiki/Grass6Planning

Please join us in testing this release candidate for the final release.

Consider to donate pizza or beer for the next GRASS GIS Community Sprint (following the FOSS4G Europe 2015 in Como):
http://grass.osgeo.org/donations/

Thanks to all contributors!

About GRASS GIS

The Geographic Resources Analysis Support System (http://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, April 2015

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.fedoraproject.org/coprs/neteler/python-OWSLib/
wget -O /etc/yum.repos.d/neteler-python-OWSLib-epel-7.repo https://copr.fedoraproject.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.fedoraproject.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.fedoraproject.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.fedoraproject.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

Compiling OTB Orfeo ToolBox software on Centos/Scientific Linux

The Orfeo ToolBox (OTB), an open-source C++ library for remote sensing images processing, is offering a wealth of algorithms to perform Image manipulation, Data pre-processing, Features extraction, Image Segmentation and Classification, Change detection, Hyperspectral processing, and SAR processing.

Since there is no (fresh) RPM package available for Centos or Scientific Linux, here some quick hints (no full tutorial, though) how to get OTB easily locally compiled. We are following the Installation Chapter.

Importantly, you need to have some libraries installed including GDAL. Be sure that it has been compiled with the “–with-rename-internal-libtiff-symbols” and ” –with-rename-internal-libgeotiff-symbols” flags to avoid namespace collision a.k.a segmentation fault of OTB as per “2.2.4 Building your own qualified Gdal“. We’ll configure and build with the GDAL-internal Tiff and Geotiff libraries that supports BigTiff files

# configure GDAL
./configure \
 --without-libtool \
 --with-geotiff=internal --with-libtiff=internal \
 --with-rename-internal-libtiff-symbols=yes \
 --with-rename-internal-libgeotiff-symbols=yes \
...
make
make install

The compilation of the OTB source code requires “cmake” and some other requirements which you can install via “yum install …”. Be sure to have the following structure for compiling OTB, i.e. store the source code in a subdirectory. The binaries will then be compiled in a “build” directory parallel to the OTB-SRC directory:

OTB-4.4.0/
|-- build/
`-- OTB-SRC/
    |-- Applications/
    |-- CMake/
    |-- CMakeFiles/
    |-- Code/
    |-- Copyright/
    |-- Examples/
    |-- Testing/
    `-- Utilities/

Now it is time to configure everything for OTB. Since I didn’t want to bother with “ccmake”, below the magic lines to compile and install OTB into its own subdirectory within /usr/local/. We’ll use as many internal libraries as possible according to the table in the installation guide. The best way is to save the following lines as a text script “cmake_otb.sh” for easier (re-)use, then run it:

#!/bin/sh

OTBVER=4.4.0
(
mkdir -p build
cd build

cmake -DCMAKE_INSTALL_PREFIX:PATH=/usr/local/otb-$OTBVER \
      -DOTB_USE_EXTERNAL_ITK=OFF -DOTB_USE_EXTERNAL_OSSIM=OFF \
      -DOTB_USE_EXTERNAL_EXPAT=OFF -DOTB_USE_EXTERNAL_BOOST=OFF \
      -DOTB_USE_EXTERNAL_TINYXML=OFF -DOTB_USE_EXTERNAL_LIBKML=OFF \
      -DOTB_USE_EXTERNAL_MUPARSER=OFF \
       ../OTB-SRC/

make -j4
# note: we assume to have write permission in /usr/local/otb-$OTBVER
make install
)

That’s it!

In order to use the freshly compiled OTB, be sure to add the new directories for the binaries and the libraries to your PATH and LD_LIBRARY_PATH variables, e.g. in $HOME/.bashrc:

export PATH=$PATH:/usr/local/bin:/usr/local/otb-4.4.0/bin
export LD_LIBRARY_PATH=/usr/local/lib:/usr/local/lib64/:/usr/local/otb-4.4.0/lib/otb/

Enjoy OTB! And thanks to the OTB developers for making it available.

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:
http://grass.osgeo.org/news/42/15/GRASS-GIS-7-0-0/

About GRASS GIS
The Geographic Resources Analysis Support System (http://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).

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: