The following SQL script creates my connections table: Afterwards, I decided to look into which station combinations are most popular. The GUI is really helpful here – everything is done in a few clicks. To get started, I loaded both station Shapefile and trip CSV into a new Spatialite database. What a great chance to play with some real-world data! Hubway is a bike sharing system in Boston and they are currently hosting a data visualization challenge. Most of the connections are clearly heading south east, across Charles River, except for that group of connections pointing the opposite direction, to Harvard Square. I think it’s more appropriate for the data at hand: While the above example uses pretty wide petals this one is done with a much narrower petal. Using the advanced options “size scale” and “rotation”, it is possible to rotate the petals into the right direction as well as scale them using the previously calculated values for connection length and orientation. This style is applied to the connection start points. (atan((xat(-1)-xat(0))/(yat(-1)-yat(0)))) * 180/3.14159 + (180 *(((yat(-1)-yat(0)) 0)*2)))įor the style, I created a new “flower petal” SVG symbol in Inkscape and styled it with varying transparency values: Rare connections are more transparent than popular ones. To get there, I reprojected the connection lines to EPSG:3857 and calculated connection length and line orientation using QGIS Field Calculator $length operator and the bearing formula given in QGIS Wiki: (Looking at the final result, they should probably go much narrower towards the end again.) The area covered by the petals is a simple approximation of where I’d expect the bike routes without performing any routing. The “flower petals” have a pointed origin and grow wider towards the middle.

The ideas was to add a notion of direction as well as uncertainty. The following image shows my first results: Today, I’ve been experimenting with a new way to visualize origin-destination pairs (ODs).

Gis plugin openoffice draw