Continuing on from the previous tutorial:-

Return to QGIS. Add the westminster_const_region.shp file if necessary

1. Press the Add Delimitated Text file button, and select the .csv export of the cleansed electoral data
2. The two options I changed from the default settings are:-

• First record contains field names
• No geometry (attribute only table)

QGIS – Create layer from text file

Step 3 – Joining the data

Joining the polygons in westminster_const_region.shp to the data imported from the Results_Cleansed spreadsheet will allow the data to be presented in a spatial and visual format which will be much easier to interpret, allow for spatial analysis and also give the viewer an idea of the geographic spread. Using QGIS’ Join function will hopefully save a lot of copying and pasting!

Right click on westminster_const_region.shp and select Properties to open the Properties dialog

• Select the Joins button from the left panel

• Join Layer – the layer that you want to join to
• Join Field – the field that you want to join to

• Target Field – the field in this layer that contains the matching data

QGIS – Add vector layer

The join will now appear in the layer’s Joins list:-

QGIS layer properties

The attribute table will now show the combined  data for both layers:-

QGIS attribute table

This data can now be used to create a thematic map that colours each constituency according to party that won the seat in 2010.

I won’t go through all the steps of creating a thematic map as an earlier tutorial does this.

I’ve used the same colours that the different parties in the UK use:-

QGIS Layer properties

The thematic map shows the results across the entire UK. It is easy to identify patterns in the result, for example

• The Liberal Democrats mostly won seats in Scotland, the North East, Wales and South West.
• There is strong Labour support in South West Scotland, North West England, West Midlands, South Wales, London, Liverpool and Manchester.
• The Conservative support covers much of the rest of England, especially South East England, excluding London.

2010 election results map

Introduction

Topology rules define the permissible relationships of features within a given GIS layer or between features in two different GIS layers. An example is that features in a road dataset must be connected to other roads at both ends, unless the road is specified as a dead end street.

Advantage of topology over queries

A lot of the checks that topology rules carry out could be achieved using spatial queries. You may have to use queries if the GIS software you’re using doesn’t have a topology feature.

Topology rules have the advantage that they only need be created once and then they can check your work as you go.

Queries would need to be re-created each time they are run. They can be saved, depending on the GIS being used, but this is still more time consuming and it is a task that must be carried out separately at the end of a work session.

Rules

QGIS 2.2 topology tool has the following rules pre-defined:-

• End points must be covered by (e.g. a railway line usually begins and ends at a station)
• Must contain (e.g. a building polygon must contain at least one address point seed)
• Must not have dangles (a line must begin and end at another line)
• Must not have duplicates (each feature should be unique, e.g. postcode areas)
• Must not have gaps (e.g. administrative area polygons cannot have gaps)
• Must not have invalid geometries
• Must not have multi-part geometries (each feature should be a separate entry)
• Must not overlap (e.g. administrative area polygons cannot overlap each other)
• Must not overlap with (a feature from layer must not overlap with another layer)

Example 1 – Roads must not have dangles

The following example uses the “Must not have dangles” rule to identify polylines from a roads dataset that are not snapped to other lines. Roads usually begin and end at a junction with another road, so this is a useful rule to identify where lines were not correctly snapped together.

To create and validate a Topology Rule

• Open the Topology Panel, by selecting Vector menu, Topology Checker, Topology Checker
• The Topology Panel appears in the lower right corner of the QGIS desktop window

• Press the Configure button to open the Topology Rule Settings dialog
• The top of the box will have 2 or 3 pull down boxes depending on the layer and rule that is chosen. Use these to build the rule and then press the Add Rule button.

• Press OK when done, the dialog box closes and the window returns to the QGIS Desktop.
• Press either the Validate All or Validate extent, depending on whether you wish to validate the entire dataset or just the current view extent.
• The errors will be listed. Double click on a row will make the map window zoom and pan to the error.

Continuing from last week’s post, I will show you how to use terrain analysis to calculate:-

• slope,
• aspect
• hillshade
• ruggedness index

Slope

Slope is calculated by comparing the pixel value at a particular location relative to the surrounding 8 pixel values. This gives the steepness of the slope.

The Slope dialogue box is very simple:-

Calculate slope dialogue box

• Select the elevation layer (this will be the DTM raster)
• Select the output layer
• I have left the Ouput format and Z factor as default. If the ground is very flat, then exaggerating the z factor might make the slopes easier to visualise.

Aspect

The aspect shows the compass bearing of the slope

The raster has been given values from 0-360 depending on the slope aspect. The darker areas with the lower values are the north to north east facing slopes; the lightest areas with the highest values are the west to north west facing slopes.

Aspect shading

Hillshade

This calculates the amount of sun or shade for a 3D surface. The dialogue box is similar to the previous ones, however there are new options for the sun angle:-

DEM hillshade dialogue box

This analysis uses a fixed location of the sun to accurately simulate the effects of bare hillside and shaded valleys. I positioned the sun to the south west (200 degrees), the east facing slopes around the River Medina estuary in the north of the island are very shaded, in contrast to the brightly lit west facing slopes on the other side of the river.

A DEM with hillshading

This is the most visually appealing and easily understood result and so it is often used as a backdrop for maps with other layers added.

Ruggedness Index

The ruggedness index value is calculated for every location, by summarizing the change in elevation within the 3×3 pixel grid.  Ruggedness index values are grouped into categories to describe the different types of terrain.  The classifications are as follows:

The dialogue box for the ruggedness Index is the same as it is for the other types of analysis mentioned above. The IOW is all categorized as level or nearly level in the ruggedness index. This is despite it being quite hilly! I used the Stretch to MinMx contrast enhancement on the layer properties box:-

A DEM with ruggedness index displayed

The result is quite different to the relief and hill shade raster’s. This is because, it doesn’t attempt to show actual slopes, rather it shows the change in elevation categorised as shown in the ruggedness index table. It is still easy to see the line of hills that cross east to west across the island.

In the previous tutorial, I showed you how to create a raster terrain model. This is useful by itself for visualising the relief of an area. However, it can be even more useful when used as the basis of further analysis.

Over the next few tutorials, I will show you how to carry out the following types of analysis:-

• Slope
• Aspect
• Hillshade
• Ruggedness Index

I am going to use srtm data for the UK, you can download the file for your area from here: http://srtm.csi.cgiar.org/

Displaying the raster, resolving display problems

• Add the image to the project using the Add Raster Layer button. At first the image opens completely grey, to stretch the black to white gradient to fit between the minimum and maximum values found in the image:-
• Press the Stretch Histogram to Full Data Set on the Raster toolbar
• Alternatively, right click on the layer in the Layer Panel, and
  • Select Properties.
  • Select the Style tab.

  At the bottom, change the Contrast Enhancement pull down to Stretch to Min Max.

• If a grid displays as a continuous grey box, check the Transparency for null cells setting
  • Open the Layer Properties
  • Select the Transparency tab
    

    QGIS Layer Properties

• Check that the correct band is selected in the Transparency Band pull down
• Check the No data value and Percent Transparent entries in the Transparent Pixel list

The DEM Models plugin should appear on the Raster Menu. If it isn’t installed, it can be downloaded by using the menu to select Plugins, fetch Python plugins.

Its operation is similar for all the types of analysis that can be undertaken

1. Select the input raster layer
2. Select the output raster layer that will contain the results
3. Use the pull down to select the analysis:

• Hillshade
• Slope
• Aspect
• Color Relief
• Terrain Ruggedness Index
• Topographic Position Index
• Roughness

DEM Terrain Module

Introduction

Rasters are created from gridded data. Each pixel is coloured according to an interpolated value, e.g. triangulation (TIN), nearest neighbour analysis.

A raster file is comprised of a pixels arranged in a grid formation. Each pixel contains a colour value that instructs the computer as to what colour to use when displaying it. Raster images tend to be used for grids as they are a more efficient method of showing large areas of coloured pixels than vector maps.

The following illustrates how a raster grid represents terrain, and how the information might be extracted:-

For simplicity’s sake, imagine that we’re back in the days of 256 colours with 1 being white and 255 being black. I tend to display relief with the highest ground as white or red, then to show lower ground as green or blue.

Let’s take a cross section through a hill:

A grid raster image of the terrain would appear similar to below (please note that I have drawn this in Inkscape using a gradient fill to keep the demonstration simple!):-

The numeric values of the raster grid that the computer would see would be similar to this:

Note the values are not the actual elevation, just the colour values of the pixels. The elevation that each pixel value corresponds to (the legend) is contained in the accompanying shape file along with image registration (the x, y coordinates).

By analysing the grid and determining the relationship between pixel values and the elevation that they represent the GIS software can accurately model the terrain. Once the terrain has been modelled, it is possible to undertake further analysis such as slope calculation, predicting hill shade or water runoff.

The Image toolbar

Firstly, let’s have a look at QGIS’ image tool bar:-

QGIS image bar

This can be added by right clicking on any toolbar and selecting Raster from the short cut menu. The buttons are from left to right:-

• Stretch Histogram to Full Data Set
• Local Histogram Stretch
• Geo-referencer
• Interpolation
• Zonal Statistics

In the previous post (Queries in QGIS pt 1 – Attribute Queries), I showed how to select features based on their attribute data, e.g. select shops which have the address entered as London. Now let’s imagine there isn’t an address attribute, or alternatively, we want to select features within flood plains for example, or identify areas of woodland that have high voltage power lines running through them.

Spatial selection selects features in one layer based on their spatial relationship to features in another layer

To begin a spatial query either:

• Use the menu to select Vector, Spatial Query
  
• Press the Spatial Query button
  

The spatial query dialogue box:

Select Source Features From – this is the table that the selection will be from.

Where the feature – the options will change depending on the exact combination of point, line or region features that are being used for the selection. They include contains (e.g. a region layer may contain points), crosses (e.g. a line layer may cross a region layer), Is Within (e.g. a point layer may be within a region layer), Touches (where one object may touch another but not actually be within it).

Reference Features Of – this is the second layer. It will be used to select features from the first layer, but its features won’t be part of the selection

The selected geometries only will only use features that have already been selected. For example if I wanted to select all the woodland within a particular county I could set up the query to read

• Select Source Features from Farmland
  
• Where the Feature is Within
  
• Reference features of County Boundaries (selected features only)
  

Click OK, the query will run. Once it has completed, the results will appear:-

It is possible to run a further query based on the selection

Press the Create Layer from Selected to add the selection to the map as a new layer:-

Combined Spatial and Attribute Query

Quite often GIS is used to select features that contain a certain attribute within a certain area (e.g. all the A roads and motorways within Greater London).

These queries are carried out by combining the above Spatial and attribute selections. They can be carried out either order depending on which is most logical.

In this example I would overlay the roads and OS Boundary Line features. I would then select all the London Boroughs by clicking on them with the Select Single Feature tool

• Select Source Features from Roads
  
• Where the Feature is Within
  
• Reference features of OS Boundaryline (selected features only)
  
• Press OK
  
• In the Results box, press the Create Layer from Selected to create a new layer
  
• Right click on the newly added Selection from Roads layer in the Layer Panel
  
• Select Query
  
• Use the Query Builder to enter the following SQL “Classification” = ‘A Road’ OR “Classification” = ‘Motorway’
  
• Press OK