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Mon Mar 18 12:35:11 2019

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QGIS Planet

Using QGIS in local government

Something that I always find interesting is how people are using different open source tools to get their work done.  This post attempts to outline how I/we are using QGIS at work for different projects.

Kerb mapping, condition, and defect pickup

This project is currently being done by a 67 year old foreman who has worked for the council for a very long time and has great knowledge of the town.   QGIS, with the main working layers stored in PostGIS, was setup so that he can:

  • Digitize kerb lines from aerial photos.
  • Split the existing kerb lines into segments depending on different asset rules.
  • Give each segment an overall condition rating.
  • Add defect points along the each kerb segment e.g. broken, lifted, etc,

Each defect point is snapped to the underlying  kerb line and chainages (distance along line) is generated using a update statement at the end of the project (could be done using a insert trigger if needed) using ST_line_locate_point(line, point).

Defect points coloured by risk captured against the kerb line

Overall QGIS has been great for this project.  The built in data entry forms have been a great help to allow fast and correct data entry. Each form has four drop downs all with present values and descriptions to aid in data entry.

Flood damaged claim maps

We recently suffered, like the rest of Queensland, some really major flooding which caused large amounts of damage to our road infrastructure. We got off pretty light compared to some places, nevertheless we still had a lot of damaged assets.  And so began the process of collecting data that could be used for state government funding claims.

Anyway, onto the QGIS bit.  QGIS was installed on one of the main engineers computers in order for him to make maps for each claim.  Having the ability for him to have one map window but multiple frames in the composer helped him to create multiple  views of the same data with ease.

In total there are 42 QGIS project files with a main project file which served the base layers to the other projects, using the cool Embed Layers and Groups feature.  This means any change in main base project was reflected up(down?) to the other projects next time they are opened.  The main project file has things like, property layer; normal road layers, with labels; road layer with roads for claims.   The other 42 projects have a filtered, and styled, road layer to only show roads in that batch, and its composers (print layouts).

Normally we would use MapInfo for this kind of thing but consider this: There are at least 3 print layouts per claim, each layout could have more then one map frame.  Now with MapInfo only being able to have a 1:1 ratio between the map window and the map frame in the layout you would need at least 3 map windows per claim.  Quick calc:

42 * 3 =  126+n map windows + 126 print layouts (n = extra map frames in layouts)

Each map window has its own copy of every layer, making change once apply every where changes hard.  This of course doesn’t apply to styles as they are stored in the .map (tab) file, but does for labels, style overrides, etc.   I’ll pass.

QGIS is no means perfect for printing or print layouts but the 1:N map window to map frame ratio worked really well for this project.  The styling options in QGIS also helped to change the display of the map depending on what was needed to be shown quickly, one even used the rule-based rendering.

You get the point.
Moving on.

Processing GPS photos with road chainages

This one I am quite proud of.  It’s nothing fancy but still saves a lot of time.  While not really QGIS only but a combination of QGIS+Spatialite it process GPS photos and assigns them a road name and chainage.

The issue: A large influx of GPS photos for the different flood damage projects and the need to process them quickly so that they got assigned to the correct road and chainage.  Now you can map GPS photos easy enough but then you still have to go to each one and assign a road name, chainage, and move it into the correct folder.  To hell with doing that by hand, this is why we invented GIS.

The result is a little (140 line) python script that:

  1. extracts the coordinates from each photos,
  2. finds the closest (within tolerance) road distance node (distance nodes are generated at 5m intervals along the road, around 800,000 in total for the whole shire),
  3. gets the road name, locality, and chainage for that node,
  4. creates a folder with that road name,
  5. renames the photo with {name} @ {chainage},
  6. moves it into the road name folder it is assign to.
  7. inserts a record for that photo into the spatialite database that can be viewed in QGIS.
The Spatialite database has a spatial index on the road distance nodes and with that in place it can process 148 photos in 8 seconds.  Not too bad at all. Now all we have to do to process the photos is stick them into a special folder and run process.bat.

Porting our planning scheme maps

I have been involved in creating, and maintaining, our planning scheme maps for the council.  It’s been a pretty fun project, apart from the constant moving target that is the state planning specifications, but I digress.

Planning scheme in QGIS

This project was done, and still is, in MapInfo. While there is nothing technically wrong with that, it has become a bit more of a pain to maintain then one would hope.  The planning scheme is not just one map but rather a series of different maps all with different scales and requirements.  I’m sure by now you can start to see the issues that can arise:

  1. No dynamic scale bar for layouts (not even a scale bar object rather just text and boxes made to look like a scale bar. With no group items feature moving these around is a pain).
  2. 1:1 map window to map frame means excessive map windows when the data is all the same with just different views.
  3. Legends don’t support ordering, adding items, or groups.
  4. With no embedding base maps feature like in QGIS it’s hard to change one thing and apply it to all the map windows/workspaces.
The specifications also ask for lines with symbols along them to show things like bikeways, footpaths etc, something that can’t be done in MapInfo, well it can by using the line style editor but I would rather stab myself in the eye.
The one thing I haven’t fully worked out how to do in QGIS yet is fully automate the printing process. Currently I open MapInfo using a batch file and pass it a workspace and MBX which prints the layouts and exits. I do this for each map type.    In QGIS I have a few options:
  1. Create a plugin that runs though each project and prints off its composers.
  2. Create a python script that runs from a batch file using qgis.core and qgis.gui QGIS python bindings.
  3. add a –code option to the command line of QGIS so that you could run: qgis.exe –noplugins –code “”, which would open QGIS and run the python code and exit.
I’m yet to explore what option is the best for this project but I’ll get back to you on that.  Once I have the above issue sorted I plan on creating the maps in QGIS to see how it would turn out (time permitting)

Custom asset data collection program

This one would have to be my favourite.  I really love programming (most days), and being able to create our own data collection program using QGIS and MS SQL 2008 has been great.

While it is only very very young I’m already seeing some great potential.  Using an open source base (apart from MS SQL) has given us a lot of power, power to change stuff that we don’t like (which so far has been one minor bug), and the power to get exactly what we need.

I can’t talk about this project a lot as it is only very new and still only in design/testing/prototyping stage.

The main things for me are:

  • Ease of use. If I get asked how to do something over and over I have failed the users. And no 100 page training manuals.
  • Fast
  • No menus, or right-click menus! I’m a power user and even I hate navigating menus on a tablet.
  • Easy to build custom forms
  • Online/Offline syncing
  • Ease of use. Oh did I say this already!? Well it’s important.
  • Easy to configure by admins.
  • Limited use of dialogs. It’s NOT ok for an app to ask users to confirm 100 dialogs to do one thing.

Overall I think using QGIS and PyQt I can hit all the targets listed above quite well. In fact I know I can because I have already hit most of the them in the last couple of weeks.


So that is my list of QGIS uses in my local government situation, hopefully it wasn’t TL;DR and you found it interesting.  I’m sure there will be plenty more to add at the end of 2012.

Filed under: Open Source, qgis Tagged: case study, FOSSGIS, gis, local gov, Local government, mapinfo, Open Source, osgeo, qgis, Quantum GIS

QGIS and GRASS in Local Government Bushfire Hazard Mapping – A Case Study

QGIS and GRASS in Local Government Bushfire Hazard MappingIntroduction

The Southern Downs Regional Council (SDRC) is a small-to-medium sized local government in south east Queensland, Australia. The council region, mainly the southern part, suffers from major bushfires.  Bushfire is a real and present concern for the residents and landowners in the Southern Downs Region, and has resulted in the loss of life and property.

This project will allow the council and the people of the region to be more aware of the risk and to allow for better decision making in the future.

The Project
As bushfire is not only a problem for SDRC but also for the whole of Queensland, the state government requires that each local government identifies the bushfire hazard in their area via the State Planning Policy 1/03 Mitigating the Adverse Impacts of Flood, Bushfire and Landslide [1].  This kind of job would normally be done using consultants but was instead done by the council itself using a combination of QGIS and GRASS.

The GIS side of the project project was broken down into 6 main steps

  1. Slope assessment and mapping
  2. Aspect assessment and mapping
  3. Vegetation assessment and mapping
  4. Combining scores to identify the severity of bushfire hazard
  5. Field verification and qualitative assessment
  6. Final Maps

The use of QGIS and GRASS
QGIS, using the GRASS plugin, was selected as it provided the tools needed to complete the job and the interaction between QGIS and GRASS made it easy to process the raster maps and present them in a meaningful way to users.  SDRC uses MapInfo for its main GIS system, however MapInfo’s addons were not as powerful as GRASS GIS for raster processing.

The QGIS GRASS plugin was used to import 5 meter contours of the whole region into GRASS which were then converted into a contour raster map using  A slope and aspect map were then generated using r.slope.aspect from the raster contour map.  Categories groups were assigned to different slope and aspect ranges and given a risk sore.  Vegetation areas were also given different risk scores.  All the resulting raster maps were then combined using mapcalc and given a final risk hazard score.  The risk scores are then divided into three main categories: high; medium; and low.  

The final part of the process was field verification via the rural fire service. After the review process, QGIS was used to print the final maps for presentation.

As all GRASS commands can be run from the command line, all the commands that were needed to generate the bushfire hazard maps were recorded, for documentation purposes and for if the maps needed to be regenerated some time in the future.

Overall QGIS, together with the GRASS plugin, provided a great experience and a great final outcome for the council doing their own bushfire hazard mapping.  The GRASS plugin provides a very easy to use interface to GRASS through QGIS.  As QGIS is able to open the GRASS raster format natively, integration is very seamless and maps can be made with ease.

The project won an encouragement award at the Queensland Planning Institute of Australia state planning awards in 2010 [2]


Filed under: Open Source, qgis Tagged: bushfire, case study, GRASS GIS, Open Source, qgis, Quantum GIS

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