I created a relief map of Haiti for the Canadian Museum of Civilization exhibit “VODOU“.

The map is displayed in the entrance corridor as an introduction to the exhibit.

The particularity is that I used a “new” technique by Leland Brown called Texture Shading.

Contrary to a standard shaded relief, texture shading shows the relative height of each point relative to the terrain nearby. It will show small ridges and canyon that are important in their relative environment, even though they aren’t in the whole area… You can read everything about it here (15mb pdf) and take a look at the software…

 The final design was done by a design firm, but I’m really pleased with the result!

Here’s the problem (due to confidentiality, the values aren’t the true ones, but you’ll get the idea).

So, the problem is to visualize the flow of movement from and to a region in a certain territory, the use of public transportation and the possible clients that aren’t taking it. There’s 8 regions so we will have 8 arrows.

For now, here’s the variable:
Total movements : Number of movements from the study area to the other regions.
Use of public transit : Of all the movements from and to the study area, the ratio that are made using public transportation (%)

This is what we have (click to enlarge):

This map tells us that between 30 and 40K people are going from region 6 to region 2 and than 1 in 4 are sing public transit. A little less is going to region 1, but almost 1 in 2 movement is made with public transit. Which is good. Region 4 is interesting. There’s 10-20K people going there, but less that 1 in 5 is using public transportation. There’s room for improvement. Maybe.

There’s many reason that can influence car ridership instead of public transit. On of them is the number of stop you have to made. If you move from you home to work and in the evening from work to home, this is what we call a pendulum movement. Those people are easier to convince to use (or at least try) public transit. Once they know the schedule and route to take.

On the other hand, if you go normally from home, then drop a kid to school, the go to work, the in the evening pick kid from school, go to the grocery store, drop the kid to soccer practice before coming home, it’s more difficult. So, we have identified those making pendulum movements.

Now, how can I add to the same arrows (ideally), a symbology that can represent the ratio of car users that are making pendulum movement?

For now, I think of using a bivariate color legend:

The arrow will be colored using this chart so the darker the color, the more pendulum movements are made on this axis. If also, the use of public transit is low (yellow or red), the more clients we could hope to convince…

What do you think?

J’ai reçu ma copie de «Cartographer’s Toolkit» par Gretchen Peterson de PetersonGIS.

Dans ce livre, Gretchen a trouvé des solutions pratiques aux problèmes fréquemment rencontrés par les cartographes : le choix des couleurs, la typographes ainsi que le style de carte et la mise en page.

Sans tomber dans la théorie lourde – ce qu’elle ne laisse pas de côté d’ailleurs – Gretchen se concentre sur des exemples concrets pour nous inspirer. Elle a créé 30 palettes de couleurs (coordonnées, continues et différenciées), montre une cinquantaine d’exemples de polices de caractères – en contexte – et 28 types de cartes et d’embellissement possible le tout accompagné de 36 cartes «par plusieurs cartographes “dominants” d’aujourd’hui» (dont votre humble serviteur ).

C’est le livre à avoir pour toute personne qui aspire à devenir cartographe ou pour tout cartographe qui pourraient, un jour, être en manque d’inspiration.

Même si l’anglais n’est pas votre langue préférée pour la lecture, vous pourrez profiter de la quantité incroyable d’informations utiles contenuse dans ce livre.

Pour vous procurer le livre : Amazon.ca
Pour suivre Gretchen sur Twitter : @PetersonGIS

Ok, it took a incredible ridiculous amount of time to create it, but I finally did it!

CREATE NETWORK FLOW ARCS

The script is quite simple. It takes a shapefile with an ID, and origins and destinations coordinates in it and calculate from a given index, a curve between the origin and destinations. That’s it. It don’t do much, but it answered a need I had so…

HOW IT WORKS

The arguments on the command line must be: >;python FlowArcs.py [C:/Path/Shapefile.shp] [curvature index]

The source shapefile must be structured like that: id | FromX | FromY | ToX | ToY

The script use the values in the shapefile to create the arcs, not the geometry of the points. The order is important because it search for the position of the field, not its name.

The curvature index determine the “roundness” of the arcs created. With an index of 1 (there’s a mistake on the picture below), you will have a perfect half circle and the higher the index, the flatter the arcs will be. It depends of your data, but with our tests, an index of 10 is usually good.

The output will be in a “Arc” directory, in the same directory as your source shapefile.

For those interested in the “principle” behind it:

You’ll need GDAL-OGR and Shapely in order to make it works.

You can download the file here: FlowArcs.py

FlowArcs.py by François Goulet is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License