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Pendle Hill


Image of Pendle Hill, Lancashire made with Blender adaptive subdivision from 1m DTM.

Digital terrain model sourced from © Environment Agency copyright and/or database right 2018.

Roads and rivers from OS OpenMap Local. All rights reserved. Contains Ordnance Survey data © Crown copyright and database right 2018.

Sentinel 2 imagery from European Space Agency – ESA.

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Pen yr Ole Wen & Llyn Ogwen


Contains Ordnance Survey data © Crown copyright and database right 2017.

Contains Natural Resources Wales information © Natural Resources Wales and Database Right. All rights Reserved.

Imagery sources: Esri, DigitalGlobe, GeoEye, i-cubed, USDA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community

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Ogilby Automation

Inspired by the work of John Ogilby (1600-1676), I  wanted to create a modern day map in the style of Britannia,  the first British road atlas in 1675.

Or to be more precise:

Britannia, Volume the First: or an Illustration of the Kingdom of England and Dominion of Wales: By a Geographical and Historical Description of the Principal Roads thereof.


Covering 23,000 miles the atlas depicts road routes all over England and Wales, by a unique style of depicting the places on route, with river crossings, counties and signposts to nearby towns.

Using FME (of course) and Ordnance Survey open data, I set about making an updated version the plate above, which is a route from London to Banbury, following the modern roads as closely as possible. Or as quickly as possible. Rather than a painstaking replica of the original, I wanted to create a data driven workspace that creates the panels from the route itself.

JOFull res version here (36mb)




To replicate the route as closely as possible, I used the ShortestPathFinder and fed it a point to point From-To line from London, (stopping at Shepherds Bush, Acton, Ealing, Uxbridge, Amersham, Aylesbury) and a road network filtered to include the ‘A roads’. Satisfying to see how little has changed in 342 years! A route using motorways would be interesting to see but would not pass through towns in the same way.

To make it as fast as possible I have used FeatureReaders, which only read the other map features (water features, buildings, place names, etc) that intersect the input path. This way the workspace can automate the production of plates, for anywhere in Great Britain.


To create the panels, I used a Tiler to divide a rectangle into 7 columns, scaled them and then offset the vertices to make them more scroll shaped.

The nearby places, eg ‘to Chelsea’ were also made with the ShortestPathFinder, with junctions on the main route that had roads to multiple towns being aggregated together and comma separated. For example, ‘to Isleworth, Teddington, Twickenham’.

To coerce the real world route into the panels, I first divided the route into 7 sections (Snipper) and replaced each section with its bounding box. Then, using the Chopper (1 vertex) and LeftRightSpatialCalculator I was able to create a set of control points that mapped the vertices of the route sections to those of the panels.

The map features (route, roads, label points, rivers, buildings) were then clipped to the route bounding boxes and fed into the AffineWarper to get them in the right place. Finally the map was rendered in the MapnikRasterizer.

Slightly beaten to the post by R J Andrews’ excellent data vis in an Ogilby style.

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Blender cycles render of Ordnance Survey Terrain 50 DTM and OpenMap foreshore, surface water and tidal water data.


Contains Ordnance Survey data © Crown copyright and database right 2017.

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Irfon Valley

Recently I have been working with the good people at Albion Cycling on a project to create a model of the Irfon Valley in mid Wales.


This model had a similar set to the Beddgelert image, with the difference being that I used the lidar data to map the trees, rather than Ordnance Survey data.

In FME, I used the RasterExpressionEvaluator to subtract the digital terrain model (DTM) values from the digital surface model (DSM), to leave the vegetation. As this area is quite remote, and mostly plantation woodland, it was fairly simple to derive a texture to use in Blender for the placement of tree instances.


Contains Natural Resources Wales information © Natural Resources Wales and Database Right. All rights Reserved. Contains OS data © Crown copyright and database right 2017.

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Blender micro-displacement terrain model


Image rendered using a single plane displaced with a 1 metre digital terrain model of the Llyn Peninsula, North Wales sourced from Natural Resources Wales.

The displacement uses an adaptive subsurf modifier new to Blender 2.78, which subdivides the object until the polygon is the size of a pixel.

This potentially allows for a massively detailed surface model to be created, but efficiently so that the detail is only applied at time of rendering, with parts of the plane closer to the camera subdivided  to the full amount, and less in the distance.

I used FME to mosaic 96 ASCII DTM files in to a single png image texture, 10km wide.

Contains Natural Resources Wales information © Natural Resources Wales and Database Right. All rights Reserved.