Adding ESRI’s World Hillshade layer to QGIS

You may have seen my earlier tutorial where I described how to make nice looking hillshaded maps in QGIS using SRTM elevation data. Well, we don’t have to stop with just one hillshade layer on a map, it is possible to overlay multiple hillshades; a procedure that can increase the visual quality and detail. The following image is the hillshade we made before. Once you re-create a hillshade, following the previous tutorial, you can head to the next step (note that brightness and contrast settings may be different due to changes in how QGIS generates and displays hillshades).

We can improve the SRTM hillshade further by adding ESRI’s World Hillshade layer, which uses multi-directional illumination (also called a Swiss Hillshade in tribute to the celebrated Swiss cartographer Eduard Imhof). In addition, World Hillshade has a much higher resolution than SRTM 30m data in some regions of the world, it is 2m for most of the England and Wales, 10m for most of the US, 5m for Spain and 3m for Holland etc. The only drawback is that the style of this layer is somewhat controversial, some love it, some hate it, it looks like it’s illuminated from above, but mixing it with the SRTM hillshade obviates some of it criticised flaws.

To add the World Hillshade layer in QGIS go to the Layer Menu – Add Layer – Add ArcGIS MapServer Layer – click New and add the following URL:

Notice QGIS 2.18 no longer needs a plugin to add ESRI layers, it new has this functionality built in. Also, open the url in a browser such as Firefox, it brings up a webpage that describes the layer. We also see links to other other layers. Yes, they can all be added to QGIS by simply taking the URL of the webpage that describe the layer and connecting to it via the ArcGIS MapServer Layer connector.

Name the layer World Hillshade and click Connect, then click and highlight the layer it connects to. Finally, click the Add button to add the layer to the canvas.

Next, we need to adjust the properties of the World Hillshade layer to properly overlay it above the SRTM hillshade layer. Make sure the World hillshade layer is the topmost layer. In the Layers Panel, right click Layer properties and in the window that opens up, click Style (if not visible). Next, change the Layer Blending mode (under color rendering) to Overlay. Adjust the layer’s brightness to around -20 and leave contrast at 0. If you find the scene is still too dark, brighten the SRTM Hillshade by increasing the layer’s brightness. You may also have to change (lower) the Min value of the Min – Max value boxes. Leave the contrast at 0 for the SRTM hillshade. Also, don’t brighten it too much as it might become washed out, loose detail, especially in bright areas. Play around the controls, settings may vary depending on the SRTM data you download and the version of QGIS you use.

Here’s a comparison in Ireland, a ring like structure of hills with a central peak. No, it’s not a meteorite crater. It’s a different kind of geological marvel, the Slieve Gullion Complex and its ring dyke; the deeply eroded remains of a 410 million year old Caledonian volcano. The SRTM hillshade is on the left and World Hillshade + SRTM hillshade is on the right (click on the image, it’s best appreciated full size):

We can see the World Hillshade + SRTM Hillshade layer shows much finer detail. We see a parallel array of roughly north-south orientated lines, these are fractures and faults that cut the Slieve Gullion Complex that were perhaps enhanced by glacial erosion. Also, look carefully, there seems to be some roads meandering across the landscape (hint, bottom of the map and right of the scale bar). You should get even better results with higher resolution World Hillshade data. We also notice that bending SRTM derived hillshade with World Hillshade adds a naturalistic illumination not apparent in multi-directional hillshading. So we have the best of both worlds, a high resolution hillshade and realistic looking illumination.

Hope you found this tutorial helpful.


Baxter, S., 2008. A Geological Field Guide to Cooley Gullion, Mourne & Slieve Croob [pdf]. Geological Survey of Ireland, Dublin. p. 43-53.

Imhof, E. 1982. Cartographic Relief Presentation. Walter de Gruyter GmbH & Co KG.

Importing CSV files into PostgreSQL using the DB Manager in QGIS

There is very useful tool in QGIS that can import very large CSV files into PostgreSQL rapidly and reliably. The DB Manager’s “Import Vector Layer” tool. Contrary to its highly misleading title it can import CSV files as well. Open the DB Manager (menu Database – DB Manager). Then select the database where you want to store your table and click the “Import layer/file” icon.

Icon_to_ClickFrom the Import Vector Layer GUI, locate our CSV file on disk and enter the name of your new table in the Table box and click OK. Yes, it’s that simple. Proceeding this, you may need to select an text encoding scheme, files created on Windows often use ISO-8859-1 (Latin-1) instead of UTF-8 encoding. In my case, I was able to import a large statistical data set describing the energy efficiency of 525,500 Irish homes (432 megabytes) into PostgreSQL in ~15 minutes. After the CSV file is imported, you can optionally add it to your project using the DB Manager, right-click the table and select Add to Canvas. Don’t use the “Add PostGIS Layers” menu, it’s not a PostGIS layer.

Import_GuiAnd one more useful tip. You can convert Tab delimited text to CSV using QGIS. Load a Tab delimited text file into QGIS using the Add Delimited Text Layer GUI, then right click the imported file in the layer panel and save it as a CSV file.

CartoDB wins best “high-growth web entrepreneur” at the 2014 European Web Entrepreneur of the Year Awards

CartoDB, the FOSS powered web mapping solution, was honoured at the 2014 European Web Entrepreneur of the Year Awards along with three other companies at Dublin’s Web Summit on November 7th. The awards, presented by a European Commission backed body, were announced after a six month competition that involved public voting across four categories. CartoDB won the award for best “high-growth web entrepreneur”. CartoDB now has a growth rate of over 15% per month and customers in over 30 countries.

In September, a partner company of CartoDB, Kudos Ltda., released a plug-in that allows QGIS users to view, create, edit and delete data stored on their CartoDB accounts. Here is a map I created with the help of the new CartoDB plug-in that shows mountains and hills across the contiguous United States in the form of a heat map.

CartoDB and QGIS illustrate the exciting convergence between web hosted and desktop GIS, where interactive maps created in QGIS can be quickly published on the web and viewed by a worldwide audience.


The Coastal Vignette


Coastal Vignette seen on an old Irish ‘6-Inch map’

Occasionally on old maps you may see a pleasing decorative effect on bodies of water called a “Coastal Vignette”, these are fine lines that highlight coastlines and lake shores. The example seen above is from a ca. 100 year old “6-inch map” of Lough Nafooey in County Galway, Ireland. I presume the Coastal Vignette effect in this example was hand drawn, it required considerable skill and patience.

These is no plugin for creating Coastal Vignettes in QGIS just yet, so I developed a simple technique to recreate the effect using the raster Proximity (Raster Distance)’ algorithm accessible in the Processing Toolbox.

In order to use the Proximity Analysis tool I first converted a Shapefile polygon depicting the sea off Dublin into a 10 by 10 metre resolution Raster using the menu command ‘Raster – Conversion – Rasterize (Vector to raster)’.


This generated a Raster that coded the Sea as ‘1’ (white) and ‘0’ (black) for Land.

Next, I selected ‘Proximity (raster distance)’  from the Processing Toolbox – (GDAL/OGR) – [GDAL] Analysis – Proximity (raster distance). You can quickly find the command by typing the algorithm’s name in the box above the Processing Toolbox.


I entered 0 in the ‘Values’ box, this tells the Proximity algorithm to measure the distance away from land (a value of 0). The resulting Raster contains cell values that correspond to the distance away from the coast in metres, which I styled below.

The final step is to create Contours Lines from the Proximity analysis result using the menu item Raster – Contour. In my case I used an “interval between the contour lines” of 200 metres and I added an Attribute name called “DIST”.


The resulting contour lines have distance attributes attached to them can be used to create a Graduated colour style if needed, though in my cause I manually edited the attributes of 10 contour lines nearest the coast and I gradually increased the transparency of the mid-grey contour lines from opaque at the coast to fully transparent out at sea. I made the remaining contour lines transparent.

And here is the finished result, with the Sea and an OpenStreetMap base map styled to look just like Google Maps.

Finished Vignette 2

QGIS Wrocław, Lisboa, Dufour, Valmiera and ?

QGIS 2.4 will be codenamed “Chugiak” in honour of the project founder Gary Sherman who lives in Chugiak, Alaska. This will be the 6th release to bear a codename named after a terrestrial locality, versions 0.8.1 through 1.5 were named after the moons of Jupiter and Saturn e.g. Titan, Io, Tethys etc. The tradition of naming QGIS releases after celestial and terrestrial locations aims to reduce legal risks involving trademarks. QGIS 2.4 will be released at Noon Alaska Time on Friday 20th June (21:00 Irish Standard Time).

Announcement – Swiss QGIS User Group

Orfeo Toolbox – Satellite Remote Sensing for QGIS


Orfeo Toolbox 4.0 (OTB) is now available for QGIS on Ubuntu 13.10 and 14.04 via the UbuntuGIS Unstable repository (it was previously available for earlier versions of Ubuntu and separately MS Windows via OSGeo4W). OTB, which can be accessed via the Processing Toolbox, provides QGIS with advanced satellite remote sensing capabilities, the sophistication of which maybe best appreciated upon thumbing OTB’s rather daunting 732 page manual.

OTB is a library of image processing algorithms based on the medical image processing library ITK v4, adapted for analysis of high resolution satellite imagery. Its algorithms are tuned to cope with huge images, that normally require supercomputer facilities, by using streaming and multithreaded processing.

The OTB project was initiated the French Space Agency (CNES) in 2006 with the objective to provide a suit of opensource tools for the analysis of images produced by the Orfeo constellation of satellites; Pléiades and Cosmo-Skymed. The motto of OTB is “Orfeo Toolbox is not a Black Box”, its algorithms are openly documented and its source code can edited by end users under the GNU compatible French CeCILL opensource license agreement.

The capabilities OTB have greatly increased since its initial release 8 years ago, especially with the release of version 4.0 in Feb 2014. It can now handle the optical sensors of SPOT, QuickBird, WorldView, Landsat and Ikonos, various multispectral sensors (e.g. Hyperion) and synthetic aperture radar imagery of TerraSarX, ERS and Palasar amongst others.

OTB’s sister application Monteverdi 2 can be installed as well. Monteverdi is a GUI batch processor for OTB that allows building complex processing chains by selecting algorithms from a set of simple drop down menus. As for future developments, the following is a demo of Orfeo Toolbox 4.0 controlled via Monteverdi 2.0, it uses the forthcoming OpenGL accelerated ICE API:


Inglada, J. & Christophe, E. 2009. The Orfeo Toolbox Remote Sensing Image Processing Software. In: IGARSS (4). 733–736.