Today’s post: More print composer overview magic!

Inverted Map Overviews

Thanks to the “Invert overview” option, we can now chose between highlighting the detail area (left example in the image) or blocking out the surrounding area (right example).

The “Lock layers for map item” option can come in very handy if you want to reduce the number of layers in the overview map while still keeping all layers of interest in the main map.

The city of Vienna provides both subdistrict geometries and population statistics. Mapping the city’s population density should be straightforward, right? Let’s see …

We should be able to join on ZBEZ and SUB_DISTRICT_CODE, check! But what about the actual population counts? Unfortunately, there is no file which simply lists population per subdistrict. The file I found contains four lines for each subdistrict: females 2011, males 2011, females 2012 and males 2012. That’s not the perfect format for mapping general population density.

A quick way to prepare our input data is applying pivot tables, eg. in Open Office: The goal is to have one row per subdistrict and columns for population in 2011 and 2012:

Export as CSV, add CSVT and load into QGIS. Finally, we can join geometries and CSV table:

A quick look at the joined data confirms that each subdistrict now has a population value. But visualizing absolute values results in misleading maps. Big subdistricts with only average density will overrule smaller but much denser subdistricts:

That’s why we need to calculate population density. This is easy to do using Field Calculator. The subdistrict file already contains area values but even if they were missing, we could calculate it using the $area operator: "pop2012" / ($area / 10000). The resulting population density in population per ha finally shows which subdistricts are the most densely populated:

One could argue that this is still no accurate representation of population density: Big parts of some subdistricts are actually covered by water – especially along the Danube – and therefore uninhabited. There are also big parks which could be excluded from the subdistrict area. But that’s going to be the topic of another post.

If you want to use my results so far, you can download the GeoJSON file from Github.

This is an update to my previous post “WFS to PostGIS in 3 Steps”. Thanks to Even Rouault’s comments and improvements to GDAL, it is now possible to load Latin1-encoded WFS (like the one by data.wien.gv.at) into PostGIS in just one simple step.

To use the following instructions, you’ll have to get the latest GDAL (release-1600-gdal-mapserver.zip)

You only need to run SDKShell.bat to set up the environment and ogr2ogr is ready for action:

C:\Users\Anita>cd C:\release-1600-gdal-mapserver
C:\release-1600-gdal-mapserver>SDKShell.bat
C:\release-1600-gdal-mapserver>ogr2ogr -overwrite -f PostgreSQL PG:"user=myuser password=mypassword dbname=wien_ogd" "WFS:http://data.wien.gv.at/daten/geoserver/ows?service=WFS&request=GetFeature&version=1.1.0&typeName=ogdwien:BEZIRKSGRENZEOGD&srsName=EPSG:4326"

Thanks everyone for your comments and help!

After my successful experiment with QGIS Server on Ubuntu, I took a shot at Windows7. These are my notes on installing QGIS Server following the instructions on the wiki.

Installation

Using OSGeo4W installer it is easy to install QGIS Server: Just mark qgis-server for installation from “Web” category (in the “Advanced” installation).

All other necessary packages will be selected automatically.

As mentioned on the wiki, the next step is to tell Apache which port number to use. Apache (2.2.14-4 from OSGeo4W) does not have any default IP/port set and it fails to start. To fix this, we need to edit the file

c:/osgeo4w/apache/conf/httpd.conf

and change

Listen @apache_port_number@

to our needs, e.g. to listen on port 80

Listen 80

The last thing I had to do to get QGIS Server working was to copy two files
libeay32.dll and ssleay32.dll
from C:\OSGeo4W\apache\bin
to C:\OSGeo4W\apps\qgis\bin.

The GetCapabilities request should work now

http://localhost/qgis/qgis_mapserv.fcgi.exe?SERVICE=WMS&VERSION=1.3.0&REQUEST=GetCapabilities

Adding a QGIS project file

To add a project file to the server, we stay in C:\OSGeo4W\apps\qgis\bin. If we put a project file in this directory, it will be served by default (without having to pass the optional map parameter).

For this test, I added my vienna.qgs project file. This is how my QGIS bin folder looks like (notice the .dll files we copied from Apache/bin and the project file):

Next, we have to restart Apache to force QGIS Server to load the project file. The OSGeo4W installation provides a handy “Apache-Monitor” GUI to restart Apache. If it fails, try to reboot ;)

Let’s test the setup using “Add WMS Layer” in QGIS by adding the service URL and ticking “Ignore GetMap URI …” and “Ignore GetFeature URI …”.

The project layers are now available through WMS and can be loaded into your client.

QGIS "Add WMS Layer" dialog with my newly created WMS

Conclusion

That wasn’t bad. The wiki page was very helpful and I didn’t encounter any real problems. Editing a config file and copying a few .dlls is easy enough.

Since linking files is not one of Windows’ strengths, I’d expect a server with multiple projects to get quite messy. But it certainly works for home use and experiments.

This year we are celebrating Gerardus Mercator’s 500th birthday. We have all grown very accustomed to his Mercator projection but I want to take the chance to explore some alternatives:

Radical Cartography features an extensive projection reference compiled by Bill Rankin. One of the more exotic projections is “Van der Grinten I” by Alphons J. van der Grinten, 1898. It has a “pleasant balance of shape and scale distortion”. The “boundary is a circle” and “all parallels and meridians are circular arcs (spacing of parallels is arbitrary)”.

Using the name, we can try to find the projection definition on Spatialreference.org. One of the definitions that works well in QGIS is “ESRI:53029 Sphere Van der Grinten I” with the following proj4 string:

+proj=vandg +lon_0=0 +x_0=0 +y_0=0 +R_A +a=6371000 +b=6371000 +units=m +no_defs

In QGIS Settings – Custom CRS, we can add this projection to the list of available CRS:

1. Press the “Star” button to add a new empty entry”
2. Add the Name and proj4 string
3. Press the “Save” button to make the changes permanent

Custom projection dialog

Once this is done, “Van der Grinten I” can be selected for on-the-fly reprojection. I’ve been using NaturalEarth’s land and ocean dataset. The result might not be a perfect circle (due to the coarseness of the dataset) but I find it very appealing:

Van der Grinten projection

This week Sourcepole released a new addition to the Raster Terrain Analysis plugin: a sophisticated Relief tool. (More info in their announcement) This plugin is shipped with QGIS (developer version, not in 1.7.3 release) by default but you might have to activate it in Plugin Manager:

The plugin dialog is quite self-explanatory. You can chose the elevation file, output path and any of the numerous raster formats. The z factor is a bit more mysterious. We will have a look at that in a second. The rest of the dialog is the relief color editor. Pressing Create automatically will give you a color gradient to start with.

Relief tool dialog

But what’s the z factor good for?

I’ve tried a few different settings using free NASA SRTM data and it seems that higher values lead to a smoother relief (Please ignore the water areas):

Update:

As Marco noted in the comments: The z factor is used if the x/y units are different from the z unit.

• If everything is in meters, use z factor 1.0 (default).
• If x/y is in degree and z in meters, use z factor 111120.
• If x/y degree and z is feet, use z factor 370400.

In the example above SRTM rasters are in WGS84 with heights in meters. That’s why the result using a z factor of 100000 looks so good.

In my opinion the results look great even with the coarse SRTM dataset I used. Looking forward to all the great QGIS maps we will see in the future.

This is a follow-up to my post “Google Maps”-Style Road Maps in QGIS and an answer to @mattwigway’s comment about how to create styles for e.g. US interstates.

interstate example map

To create a style like this, you can use the “Marker line” feature. The marker can be built using a blank SVG shield and additional text markers to add the road number on top.

creation of the interstate shield marker

This marker line can be put “on central point” to only show up once along the road.

creation of the interstate style

You can find interstate and other shield style on e.g. Wikimedia Commons. With Inkscape, you can remove the number and thus create a blank marker template.

The idea behind this post was to create a video of twitter activity using Time Manager. You can watch the results of my first test run here:

And this is how it’s done:

First, you have to collect some tweets with location information. The following command will collect tweets within a certain geographic region from the Twitter Stream API using curl. You need a Twitter user account to use the API. (Curl comes readily available with OSGeo4W install.)

curl -k -d @locations.txt https://stream.twitter.com/1/statuses/filter.json -uuser:password > tweets.json

The contents of locations.txt is the geographic extent you are interested in, e.g. for Austria:

locations=9,45,17,50

After collecting some data, you can load the tweets into QGIS. Executing the following lines in Python Console will add an in-memory point layer to the map. (I am only extracting coordinates and time stamp from the tweets, but you can access more information through the JSON object.)

import simplejson
from PyQt4.QtCore import *
from datetime import *

f=open('C:/temp/tweets.json','r')

# create layer
vl = QgsVectorLayer("Point", "tweets", "memory")
vl.startEditing()
pr = vl.dataProvider()

# add fields
pr.addAttributes( [ QgsField("t", QVariant.String) ] )

# create features
for line in f:
   try:
      j=simplejson.loads(line)
      fet=QgsFeature()
      fet.setGeometry(QgsGeometry.fromPoint(QgsPoint(j['geo']['coordinates'][1],j['geo']['coordinates'][0])))
      fet.setAttributeMap({0:QVariant(str(datetime.strptime(j['created_at'],'%a %b %d %H:%M:%S +0000 %Y')))})
      pr.addFeatures([fet])
   except:
      pass

vl.commitChanges()
vl.updateExtents()

QgsMapLayerRegistry.instance().addMapLayer(vl)

To use the result in Time Manager, you have to export the layer to e.g. Shapefile because it’s not possible to add query strings to in-memory layers.

If you are interested in learning more about PyQGIS, you can find a lot of useful material in the PyQGIS Cookbook.

Today, I’ve been experimenting with data from OpenFlights.org. They offer airport, airline and route data for download. The first idea that came to mind was to connect airports on a shared route by lines. This kind of visualization just looks much nicer if the connections are curved instead of simple straight lines.

Luckily, that’s pretty easy to do using PostGIS. After loading airport positions and route data, we can create the connection lines like this (based on [postgis-users] Great circle as a linestring):

UPDATE experimental.airroutes
SET the_geom =
(SELECT ST_Transform(ST_Segmentize(ST_MakeLine(
       ST_Transform(a.the_geom, 953027),
       ST_Transform(b.the_geom, 953027)
     ), 100000 ), 4326 )
 FROM experimental.airports a, experimental.airports b
 WHERE a.id = airroutes.source_id
   AND b.id = airroutes.dest_id
);

The CRS used in the query is not available in PostGIS by default. You can add it like this (source: spatialreference.org):

INSERT into spatial_ref_sys (srid, auth_name, auth_srid, proj4text, srtext) values ( 953027, 'esri', 53027, '+proj=eqdc +lat_0=0 +lon_0=0 +lat_1=60 +lat_2=60 +x_0=0 +y_0=0 +a=6371000 +b=6371000 +units=m +no_defs ', 'PROJCS["Sphere_Equidistant_Conic",GEOGCS["GCS_Sphere",DATUM["Not_specified_based_on_Authalic_Sphere",SPHEROID["Sphere",6371000,0]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]],PROJECTION["Equidistant_Conic"],PARAMETER["False_Easting",0],PARAMETER["False_Northing",0],PARAMETER["Central_Meridian",0],PARAMETER["Standard_Parallel_1",60],PARAMETER["Standard_Parallel_2",60],PARAMETER["Latitude_Of_Origin",0],UNIT["Meter",1],AUTHORITY["EPSG","53027"]]');

This is an example visualization (done in QGIS) showing only flight routes starting from Vienna International Airport:

Flight routes from Vienna International

Connections crossing the date line are currently more problematic. Lines would have to be split, otherwise this is what you’ll get:

Date line trouble

Want to finally try QGIS Server on your Windows system? Thankfully, Till Adams has written a new HowTo for QGIS Server on Windows. Till shows how to install OSGeo4W version and how to get it running.

If you first want to see what QGIS Server and QGIS Webclient can do, check Webgis-Uster homepage by Andreas Neumann.

Vienna’s Open Government Data initiative is publishing an increasing amount of Geodata and the best thing is: They’re publishing it via open standardized services! Both WMS and WFS are available and ready to be used in QGIS.

Let’s see how we can use the data available through their WFS using the district information layer “Bezirksgrenzen” as an example. The page lists a GML and a GeoJSON version of WFS. For now, we’ll use GeoJSON.

In QGIS, the layer can be loaded using “Add vector layer” – “Protocol” and inserting the GeoJSON url there. The encoding should be changed to ISO8859-15 to account for “Umlaute”.

The loaded GeoJSON layer "Bezirksgrenzen"

Now, we have geodata. Let’s add some attribute data too! Attribute data is available in CSV format. After downloading e.g. some information on the district population, check the file content and remove excessive header lines so that there is only one header line containing attribute names left. Then, you can load the CSV file into QGIS too (“Add vector layer”).

Last step: Joining geodata and attribute data! Go to the vector layer’s properties – Join tab and add the following join relation:

Joining GeoJSON and attribute layer

Now, the attribute table of the vector layer contains the additional CSV attributes – ready for further analysis. If you want to classify based on numerical CSV attributes, you’ll have to create a .csvt file first otherwise all fields are interpreted as texts.

Works great. Thumbs up for this great initiative!

QGIS 1.7 has landed. After some delays due to a major infrastructure overhaul, a new version of QGIS is available for download. For a list of what’s new in 1.7 check the release announcement.

Ever wondered how to create multi-line labels in QGIS? The new labeling engine has a “Multiline labels” option but it’s not so obvious how to create a usable labeling attribute. Here is how it works (credits to @nhopton on QGIS forum):

1. Create a big enough text field (if the data doesn’t contain any yet).
2. In Layer Properties – Fields, chose a “Text edit” edit widget for the label field.
3. Enter the multi-line text into the label field. You can do this using Attribute Table or Feature Form.
   

   A feature form with "Text edit" widget

4. Activate labeling. You’ll have to tick “Multiline labels” option in Layer Labeling Settings – Advanced – Options. That’s it:
   

   Simple multi-line label example

A common use case is the wish to show multiple attribute values in a feature’s label. Using Field Calculator, you can combine them into multi-line labels. All you need is to combine the fields with the || operator and add ‘\n’ (newline) wherever there should be a line break:

Field1 || '\n' || Field2

Populating a multi-line label field using Field Calculator

And finally, the result:

Multi-line labels displaying city name and population

“-T”, this small appendix can be found after many popular GIS-related acronym. But of course, it always means something different. Take for example GIS-T (GIS for Transportation), WFS-T (Transactional WFS) and WMS-T (WMS with time support). The world of acronyms is a fun place!

Let’s see what a WMS-T can do for us. From the WMS standard:

Some geographic information may be available at multiple times (for example, an hourly weather map). A WMS
may announce available times in its service metadata, and the GetMap operation includes a parameter for
requesting a particular time. [...] Depending on the context, time
values may appear as a single value, a list of values, or an interval, …

Currently, only Mapserver supports WMS-T but the Geoserver team is working on it.

Mapserver

MapServer 4.4 and above provides support to interpret the TIME parameter and transform the resulting values into appropriate requests.

Time attributes are specified within the metadata section:

METADATA
"wms_title" "Earthquakes"
"wms_timeextent" "2011-06-01/2011-07-01"
"wms_timeitem" "TIME"
"wms_timedefault" "2011-06-10 12:10:00"
END

Mapserver supports temporal queries for single values, multiple values, single range values or even multiple range values:

...&TIME=2011-06-10&...
...&TIME=2011-06-10, 2004-10-13, 2011-06-19&...
...&TIME=2011-06-10/2011-06-13&...
...&TIME=2011-06-10/2011-06-15, 2011-06-20/2011-06-25&...

Geoserver

GeoSolutions has developed support for TIME and ELEVATION dimensions in WMS.
There are plans to backport this feature to the stable 2.1.x series after the 2.1.1 release.

Configuration of time-enabled layers can be done via the normal user interface:

The following video by GeoSolutions demonstrates the use of Geoserver’s WMS-T:

Both server solutions seem to support only one time attribute per layer. An optional second time attribute would be nice to support datasets with start and end time like Time Manager for QGIS does.

The gis.stackexchange community keeps on growing and it’s questions and answers span a wide spectrum of GIS-related topics. As of today, the page lists 2,700 questions and 6,400 answers.

As was to be expected, ‘arcgis’ (549 times) is the most used tag followed by ‘arcgis-10.0′ ;)

From an open source perspective, PostGIS gets most attention (rank 8), followed closely by OpenLayers (rank 9) and Geoserver (rank 10). QGIS is the highest-ranked desktop GIS (rank 13). Users of other open source desktop GIS like uDig or gvSIG don’t seem to be using this platform yet.

Here’s the full list of open source GIS tags with a count of more than 10:

postgis × 149
openlayers × 137
geoserver × 121
qgis × 97
open-source × 94
grass × 85
gdal × 68
postgresql × 32
pgrouting × 20
geodjango × 14
mapnik × 13

Recently, @simo has posted an elegant solution for defining custom styles for Google Maps layers in OpenLayers on gis.stackexchange. An example with source can be found at http://www.empreinte-urbaine.eu/mapping/styled_gmap.html. The idea seems to be to use a StyledMapType:

The StyledMapType allows you to customize the presentation of the standard Google base maps, changing the visual display of such elements as roads, parks, and built-up areas to reflect a different style than that used in the default map type.

How great would it be if it was possible to define such styles in QGIS OpenLayers plugin too!

The aim of QGIS Processing Framework developed by Polymeris is to provide a generic framework for accessing existing geo-processing functionality of e.g. SAGA, GRASS, Orfeo Toolbox, etc. This should enable users to script their geo-processing work in python console and allow development of a tool to graphically build workflows using VisTrails an “open-source scientific workflow and provenance management system”.

For a first impression, Polymeris has published some screenshots of QGIS with SAGA modules loaded: [1],[2]

This project is big and if it turns out well, QGIS will profit enormously from it. Both scriptable geoprocessing functionality and a graphic workflow builder can improve user experience a lot if they are implemented well. You can follow further development on the project homepage on GitHub.

On Wednesday, Allan Maungu – geoscripting.blogspot.com announced MXD2QGS, a converter that exports layers from an Arcmap 10 document into a Quantum GIS project file. The tool is built as an ArcToolbox and can be downloaded from the blog.

I’d be very interested to hear whether this tool works for you.

For everyone working with spatial databases in QGIS there comes a time when “Add PostGIS/SpatiaLite Layer” and “RT Sql Layer” start to be annoying. You always have to retype or copy-paste your SQL queries into the user interface if you need to change the tiniest thing in the layer’s definition.

This is where “Fast SQL Layer” can be a real time saver. Fast SQL Layer is a new plugin for QGIS by Pablo T. Carreira. It basically adds an SQL console for loading layers from PostGIS/SpatiaLite into QGIS. And it even comes with syntax highlighting!

Installation

Fast SQL Layer comes with one dependency: Pygments, which is used for syntax highlighting.

On Ubuntu, all you have to do is install it with apt-get:

sudo apt-get install python-pygments

For Windows with OSGeo4W, @Mike_Toews posted this on gis.stackexchange:

I downloaded and extracted Pygments-1.4.tar.gz, then in an OSGeo4W shell within the Pygments-1.4 directory, type python setup.py build then python setup.py install

Usage

When you activate the plugin in plugin manager, a dock widget will appear which contains the console and some fields for specifying the database connection that should be used. Then, you can simply write your SQL query and load the results with one click.

Fast SQL plugin

In this example, I renamed “gid” to “id”, but you can actually edit the values in the drop down boxes to adjust the column names for id and geometry:

A second layer loaded using Fast SQL plugin

It certainly needs some polishing on the user interface side but I really like it.

The city of Vienna has started their open data initiative. They’re offering data on a variety of topics, including: infrastructure, population, education, environment and traffic.

For use in GIS, they serve the data through WMS and WFS:

• WMS: http://data.wien.gv.at/daten/wms?service=WMS&request=GetCapabilities&version=1.1.1
• WFS 1.0: http://data.wien.gv.at/daten/wfs?service=WFS&request=GetCapabilities&version=1.0.0
•  WFS 1.1: http://data.wien.gv.at/daten/wfs?service=WFS&request=GetCapabilities&version=1.1.0

Both WMS and WFS work well with the developer version of QGIS.

Looking forward to new datasets. Announcements should be published via RSS feed.