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All Animations Maps OSGEO PostGIS QGIS Tutorials

My Strava Activities from the Same Place at the Same Time Animated

All of my activities from Strava if they started from the same place at the same time.

Strava Activites Animated

Longest activity time wise is an 11 hour walk.

Distance wise is a 200km helicopter ride.

Includes a couple of 100km cycles. But mainly walks on the beach, 5 km runs, and 10km cycles.

You can see the patterns from a number of locations that I have lived in.

How to

  1. Download your activities from Strava.
  2. Parse them into a PostgreSQL/PostGIS database with Python: https://github.com/HeikkiVesanto/StravaGarminParser/blob/master/parser_points_to_db.py
  3. Process the points to time series in the database: https://gist.github.com/HeikkiVesanto/3fbd55cda45394d069773a34ea244e4b
  4. Create animation in QGIS using the atlas generator.
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All Animations Featured Ireland

Luas Map Compared to Real Geography

Inspired by /u/a_wandering_chemist on Reddit.

This is a look at how the map of the Dublin tram network, the Luas (Irish for speed), compares to the actual geographic footprint.

For a simpler view:

The processing of the transition is done in PostgreSQL with PostGIS, with the final animation in QGIS.

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All Animations Scotland

Scotland’s Cartographic Outline

This is a topic I have covered in the past as well: Scotland’s Changing Outline

But the 1654 Blaeu Atlas of Scotland was an influential cartographic masterpiece. The National Library of Scotland have covered it’s publication history very well: The history behind the publication of the Blaeu Atlas of Scotland.

When the sixth volume of Joannis Blaeu’s Atlas Novus was released in 1655, the maps of Scotland formed one eighth of the total maps in his world atlas. Making Scotland one of the best mapped countries of the seventeenth-century world.

The animations include the following maps from the National Library of Scotland:

Blaeu Compared to Modern Day Outline from OpenStreetMap

Cycling Through the Maps by Publication Date

Blaeu – 1654
Sanson – 1665
Morden – 1687
Moll – 1714
Elphinstone – 1745
Dorret – 1751
Modern
Blaeu – 1654

Comparison to Modern Day In Between

Blaeu – 1654
Modern
Sanson – 1665
Modern
Morden – 1687
Modern
Moll – 1714
Modern
Elphinstone – 1745
Modern
Dorret – 1751
Modern
Blaeu – 1654

Comparison to Blaeu

Blaeu – 1654
Sanson – 1665
Blaeu – 1654
Morden – 1687
Blaeu – 1654
Moll – 1714
Blaeu – 1654
Elphinstone – 1745
Blaeu – 1654
Dorret – 1751
Blaeu – 1654

Overlaid

From: Scotland’s Changing Outline

Read about the maps here: Historic Maps of Scotland from Blaeu to Dorret (1600-1700)

Merch

There is also a t-shirt with all of the outlines overlaid, if you are a fan of Scottish cartographic history.

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All Animations OpenStreetMap

Made With OpenStreetMap

Inspired by the “made with QGIS” logos by Klas Karlsson.

I made a few for OpenStreeMap ones. Well, I added some text to existing logos:

The simple OSM logo by ScubbX.

The main OSM logo by Ken Vermette.

Both logos are trademarked by the OSMF, but these are unofficial. For the full attribution and copyright guidelines visit the OpenStreetMap website.

Color:

License: CC BY-SA 3.0 Ken Vermette

PNG:

SVG:

Black:

License: CC BY-SA 2.0 ScubbX

PNG, clear background:

PNG, white background:

SVG:

White:

License: CC BY-SA 2.0 ScubbX

Example:

All buildings added to OSM in Ireland in 2021

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Featured Posts

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All Ireland Maps OSGEO QGIS

Commuting in Ireland Mapped

As part of the 2016 Irish Census the Central Statistics Office captured data on communing to work and school/college (POWSCAR). The raw data is available for research purposes, but the anonymised data is available to all. This data is aggregated to an Electoral Division (ED) level.

There are 3440 EDs in Ireland, 3409 after amalgamating low population ones. These are legally defined administrative areas. Commutes into Northern Ireland are also captured, but only as one destination (Northern Ireland).

Overall the data consists of a CSV file with 291893 rows of commuting data.

Maps inspired by Dónal Casey.

Ireland

Mapping Irish commuting data at a country level allows us to see the patterns of commuting.

Purple

The map styles can easily be achieved in QGIS. They utilise blending modes and variable levels of symbology based on the commuter counts.

A great guide can be found on this from the Ordnance Survey. Carto tips: Using blend modes and opacity levels

I also talk about this at my FOSS4GUK 2019 talk: YouTube – IE
FOSS4GUK LIVE – Main Room / Biosphere Green – DAY 2

The purple map above use color: #6450d7 – Addition blend – 100% opacity – Line thickness: if (“count”>1000, 1000, “count”)/1000

Gold:

Gold

Color: #e5b636 – Addition blend – 100% opacity

This map was featured in the 2020 GeoHipster calendar.

Black and White:

9 cities

Nine largest cities:

9 cities

Individual Cities

I have also created individual maps for all settlements in Ireland. This should give a better local picture of the commuter flows.

Settlements were linked to EDs based on a few characteristics:

  • Settlement intersects ED AND either
  • The original point on surface is within 100 meters of a settlement OR
  • 75% of the settlement is in the ED OR
  • 90% of the ED is in the settlement

List of all settlements.

Examples:

Letterkenny:

Letterkenny

Galway:

Galway

Castleisland:

Castleisland

Tramore:

Tramore
Categories
All Featured Ireland Maps OSGEO PostGIS QGIS

Dublin Neighborhoods Mapped

Neighborhood boundaries are a fascinating topic. Where do people see their neighborhood extending to, how clear are those boundaries, and how do they shift with time.

This is a topic that has been tackled a number of times around the world, and with different types of locations (like cities). With the general public asked to draw their own neighborhood, or the ones they are familiar with, on a map. But there are challenges.

Sometimes the results are successful, like in Boston. Boston only has around 60 neighborhoods, which are relatively clearly defined based on the mapping results. And Bostonography clearly had a great readership, with over 2300 responses.

Older cities, like Glasgow are much more complex. In 2016 I did a similar survey, and from 367 responses I received 241 unique neighborhoods. You would need a much bigger set of responses to come to any real conclusions. But I still mapped the results for the West End of Glasgow, where most neighborhoods had multiple responses: Glasgow Regions Mapped

The challenges for Dublin neighborhoods is similar to Glasgow, although not as complex. But anything worth doing would require a lot of responses.

Luckily the Dublin InQuirer decided to run a similar survey, polling their subscribers for responses. The number of submissions was good, not quite beating the Boston yet, but getting close. 2200 responses and 133 unique neighborhoods mapped. They also did a few great things. One was making the data available to download. This meant that anyone could map the results, which is great. Additionally they are reaching out to areas with less responses, which is a great effort on their part.

Dublin InQuirer – Will You Draw Your Dublin Neighbourhood for Us?

Map your neighborhood.

Results:

I have mapped all of the neighborhoods as an interactive map, and individually if they had 10 or more responses.

Interactive:

Full page.

Individual Dublin Hoods:

The following have been mapped as they had over 10 responses:

Artane,
Baldoyle,
Ballinteer,
Ballsbridge,
Ballybough,
Ballyfermot,
Beaumont,
Blackrock,
Broadstone,
Cabra,
Castleknock,
Churchtown,
Clondalkin,
Clontarf,
Crumlin,
Dolphins Barn,
Donnybrook,
Donnycarney,
Drimnagh,
Drumcondra,
Dun Laoghaire,
East Wall,
Fairview,
Finglas,
Firhouse,
Glasnevin,
Goatstown,
Harold’s Cross,
Inchicore,
Islandbridge,
Kilmainham,
Kimmage,
Knocklyon,
Lower Crumlin,
Lucan,
Malahide,
Marino,
Navanroad,
Phibsborough,
Portmarnock,
Portobello,
Raheny,
Ranelagh,
Rathfarnham,
Rathgar,
Rathmines,
Rialto,
Sandymount,
Santry,
Smithfield,
Stoneybatter,
Sutton,
Tallaght,
Terenure,
The Liberties,
The Tenters,
Whitehall

Creation:

These maps were created with Python for downloading the data, PostgreSQL/PostGIS for the data processing, and QGIS for the rendering.

There is not a full tutorial, but the processing code is available in here:

Downloading the data.

SQL processing.