Table of Contents for
QGIS: Becoming a GIS Power User

Version ebook / Retour

Cover image for bash Cookbook, 2nd Edition QGIS: Becoming a GIS Power User by Alexander Bruy Published by Packt Publishing, 2017
  1. Cover
  2. Table of Contents
  3. QGIS: Becoming a GIS Power User
  4. QGIS: Becoming a GIS Power User
  5. QGIS: Becoming a GIS Power User
  6. Credits
  7. Preface
  8. What you need for this learning path
  9. Who this learning path is for
  10. Reader feedback
  11. Customer support
  12. 1. Module 1
  13. 1. Getting Started with QGIS
  14. Running QGIS for the first time
  15. Introducing the QGIS user interface
  16. Finding help and reporting issues
  17. Summary
  18. 2. Viewing Spatial Data
  19. Dealing with coordinate reference systems
  20. Loading raster files
  21. Loading data from databases
  22. Loading data from OGC web services
  23. Styling raster layers
  24. Styling vector layers
  25. Loading background maps
  26. Dealing with project files
  27. Summary
  28. 3. Data Creation and Editing
  29. Working with feature selection tools
  30. Editing vector geometries
  31. Using measuring tools
  32. Editing attributes
  33. Reprojecting and converting vector and raster data
  34. Joining tabular data
  35. Using temporary scratch layers
  36. Checking for topological errors and fixing them
  37. Adding data to spatial databases
  38. Summary
  39. 4. Spatial Analysis
  40. Combining raster and vector data
  41. Vector and raster analysis with Processing
  42. Leveraging the power of spatial databases
  43. Summary
  44. 5. Creating Great Maps
  45. Labeling
  46. Designing print maps
  47. Presenting your maps online
  48. Summary
  49. 6. Extending QGIS with Python
  50. Getting to know the Python Console
  51. Creating custom geoprocessing scripts using Python
  52. Developing your first plugin
  53. Summary
  54. 2. Module 2
  55. 1. Exploring Places – from Concept to Interface
  56. Acquiring data for geospatial applications
  57. Visualizing GIS data
  58. The basemap
  59. Summary
  60. 2. Identifying the Best Places
  61. Raster analysis
  62. Publishing the results as a web application
  63. Summary
  64. 3. Discovering Physical Relationships
  65. Spatial join for a performant operational layer interaction
  66. The CartoDB platform
  67. Leaflet and an external API: CartoDB SQL
  68. Summary
  69. 4. Finding the Best Way to Get There
  70. OpenStreetMap data for topology
  71. Database importing and topological relationships
  72. Creating the travel time isochron polygons
  73. Generating the shortest paths for all students
  74. Web applications – creating safe corridors
  75. Summary
  76. 5. Demonstrating Change
  77. TopoJSON
  78. The D3 data visualization library
  79. Summary
  80. 6. Estimating Unknown Values
  81. Interpolated model values
  82. A dynamic web application – OpenLayers AJAX with Python and SpatiaLite
  83. Summary
  84. 7. Mapping for Enterprises and Communities
  85. The cartographic rendering of geospatial data – MBTiles and UTFGrid
  86. Interacting with Mapbox services
  87. Putting it all together
  88. Going further – local MBTiles hosting with TileStream
  89. Summary
  90. 3. Module 3
  91. 1. Data Input and Output
  92. Finding geospatial data on your computer
  93. Describing data sources
  94. Importing data from text files
  95. Importing KML/KMZ files
  96. Importing DXF/DWG files
  97. Opening a NetCDF file
  98. Saving a vector layer
  99. Saving a raster layer
  100. Reprojecting a layer
  101. Batch format conversion
  102. Batch reprojection
  103. Loading vector layers into SpatiaLite
  104. Loading vector layers into PostGIS
  105. 2. Data Management
  106. Joining layer data
  107. Cleaning up the attribute table
  108. Configuring relations
  109. Joining tables in databases
  110. Creating views in SpatiaLite
  111. Creating views in PostGIS
  112. Creating spatial indexes
  113. Georeferencing rasters
  114. Georeferencing vector layers
  115. Creating raster overviews (pyramids)
  116. Building virtual rasters (catalogs)
  117. 3. Common Data Preprocessing Steps
  118. Converting points to lines to polygons and back – QGIS
  119. Converting points to lines to polygons and back – SpatiaLite
  120. Converting points to lines to polygons and back – PostGIS
  121. Cropping rasters
  122. Clipping vectors
  123. Extracting vectors
  124. Converting rasters to vectors
  125. Converting vectors to rasters
  126. Building DateTime strings
  127. Geotagging photos
  128. 4. Data Exploration
  129. Listing unique values in a column
  130. Exploring numeric value distribution in a column
  131. Exploring spatiotemporal vector data using Time Manager
  132. Creating animations using Time Manager
  133. Designing time-dependent styles
  134. Loading BaseMaps with the QuickMapServices plugin
  135. Loading BaseMaps with the OpenLayers plugin
  136. Viewing geotagged photos
  137. 5. Classic Vector Analysis
  138. Selecting optimum sites
  139. Dasymetric mapping
  140. Calculating regional statistics
  141. Estimating density heatmaps
  142. Estimating values based on samples
  143. 6. Network Analysis
  144. Creating a simple routing network
  145. Calculating the shortest paths using the Road graph plugin
  146. Routing with one-way streets in the Road graph plugin
  147. Calculating the shortest paths with the QGIS network analysis library
  148. Routing point sequences
  149. Automating multiple route computation using batch processing
  150. Matching points to the nearest line
  151. Creating a routing network for pgRouting
  152. Visualizing the pgRouting results in QGIS
  153. Using the pgRoutingLayer plugin for convenience
  154. Getting network data from the OSM
  155. 7. Raster Analysis I
  156. Using the raster calculator
  157. Preparing elevation data
  158. Calculating a slope
  159. Calculating a hillshade layer
  160. Analyzing hydrology
  161. Calculating a topographic index
  162. Automating analysis tasks using the graphical modeler
  163. 8. Raster Analysis II
  164. Calculating NDVI
  165. Handling null values
  166. Setting extents with masks
  167. Sampling a raster layer
  168. Visualizing multispectral layers
  169. Modifying and reclassifying values in raster layers
  170. Performing supervised classification of raster layers
  171. 9. QGIS and the Web
  172. Using web services
  173. Using WFS and WFS-T
  174. Searching CSW
  175. Using WMS and WMS Tiles
  176. Using WCS
  177. Using GDAL
  178. Serving web maps with the QGIS server
  179. Scale-dependent rendering
  180. Hooking up web clients
  181. Managing GeoServer from QGIS
  182. 10. Cartography Tips
  183. Using Rule Based Rendering
  184. Handling transparencies
  185. Understanding the feature and layer blending modes
  186. Saving and loading styles
  187. Configuring data-defined labels
  188. Creating custom SVG graphics
  189. Making pretty graticules in any projection
  190. Making useful graticules in printed maps
  191. Creating a map series using Atlas
  192. 11. Extending QGIS
  193. Defining custom projections
  194. Working near the dateline
  195. Working offline
  196. Using the QspatiaLite plugin
  197. Adding plugins with Python dependencies
  198. Using the Python console
  199. Writing Processing algorithms
  200. Writing QGIS plugins
  201. Using external tools
  202. 12. Up and Coming
  203. Preparing LiDAR data
  204. Opening File Geodatabases with the OpenFileGDB driver
  205. Using Geopackages
  206. The PostGIS Topology Editor plugin
  207. The Topology Checker plugin
  208. GRASS Topology tools
  209. Hunting for bugs
  210. Reporting bugs
  211. Bibliography
  212. Index

Styling raster layers

After this introduction to data sources, we can create our first map. We will build the map from the bottom up by first loading some background rasters (hillshade and land cover), which we will then overlay with point, line, and polygon layers.

Let's start by loading a land cover and a hillshade from landcover.img and SR_50M_alaska_nad.tif, and then opening the Style section in the layer properties (by going to Layer | Properties or double-clicking on the layer name). QGIS automatically tries to pick a reasonable default render type for both raster layers. Besides these defaults, the following style options are available for raster layers:

  • Multiband color: This style is used if the raster has several bands. This is usually the case with satellite images with multiple bands.
  • Paletted: This style is used if a single-band raster comes with an indexed palette.
  • Singleband gray: If a raster has neither multiple bands nor an indexed palette (this is the case with, for example, elevation model rasters or hillshade rasters), it will be rendered using this style.
  • Singleband pseudocolor: Instead of being limited to gray, this style allows us to render a raster band using a color map of our choice.

The SR_50M_alaska_nad.tif hillshade raster is loaded with Singleband gray Render type, as you can see in the following screenshot. If we want to render the hillshade raster in color instead of grayscale, we can change Render type to Singleband pseudocolor. In the pseudocolor mode, we can create color maps either manually or by selecting one of the premade color ramps. However, let's stick to Singleband gray for the hillshade for now.

Styling raster layers

The Singleband gray renderer offers a Black to white Color gradient as well as a White to black gradient. When we use the Black to white gradient, the minimum value (specified in Min) will be drawn black and the maximum value (specified in Max) will be drawn in white, with all the values in between in shades of gray. You can specify these minimum and maximum values manually or use the Load min/max values interface to let QGIS compute the values.

Tip

Note that QGIS offers different options for computing the values from either the complete raster (Full Extent) or only the currently visible part of the raster (Current Extent). A common source of confusion is the Estimate (faster) option, which can result in different values than those documented elsewhere, for example, in the raster's metadata. The obvious advantage of this option is that it is faster to compute, so use it carefully!

Below the color settings, we find a section with more advanced options that control the raster Resampling, Brightness, Contrast, Saturation, and Hue—options that you probably know from image processing software. By default, resampling is set to the fast Nearest neighbour option. To get nicer and smoother results, we can change to the Bilinear or Cubic method.

Click on OK or Apply to confirm. In both cases, the map will be redrawn using the new layer style. If you click on Apply, the Layer Properties dialog stays open, and you can continue to fine-tune the layer style. If you click on OK, the Layer Properties dialog is closed.

The landcover.img raster is a good example of a paletted raster. Each cell value is mapped to a specific color. To change a color, we can simply double-click on the Color preview and a color picker will open. The style section of a paletted raster looks like what is shown in the following screenshot:

Styling raster layers

If we want to combine hillshade and land cover into one aesthetically pleasing background, we can use a combination of Blending mode and layer Transparency. Blending modes are another feature commonly found in image processing software. The main advantage of blending modes over transparency is that we can avoid the usually dull, low-contrast look that results from combining rasters using transparency alone. If you haven't had any experience with blending, take some time to try the different effects. For this example, I used the Darken blending mode, as highlighted in the previous screenshot, together with a global layer transparency of 50 %, as shown in the following screenshot:

Styling raster layers