The Comic Book Cartography blog collects maps and diagrams from the golden age of comic books and serves them up to your eyeballs. I particularly like this neighbourhood map from a 1958 ‘Little Archie’ comic. Neat stuff.
I am trying to understand the extent of the new proposed mining sites on New Zealand conservation land. It is difficult to imagine what thousands of hectares look like. I have hacked together a tool that compares the proposed sites to places I know around the country. The tool splits the screen in half and binds the zoom levels of the two maps (I first came across this technique on compare-places.com). The left screen depicts the mining areas. The right screen can display any place you want. I have added some links at the bottom of the screen to assist navigation.
Click here to play with the tool.
Comparing proposed mining site at Okupu to Downtown Auckland
The data is digitised from maps available on the Ministry of Economic Development website. The data I derived should be treated very cautiously as the original MED maps were published at a relatively small cartographic scale. Treat my depictions as approximations.
A tour of the Universe from the Himalayas to the echo of the Big Bang. The film was created from data in the Digital Universe Atlas, which is maintained by astrophysicists at the American Museum of Natural History.
Dim the lights, switch to hi-res, hit full-screen and enjoy.
Over the last few days I have been building a simple Twitter client to visualize time series data embedded in tweets. You can find the proof of concept client here. Feel free to play with the tool and to repurpose the code. Read on for my initial thoughts on embedded Twitter data and ambient visualization.
Time series data visualized in twitter feed
A couple of days ago I stumbled across the Twitter Data proposal.
“In 140 chars: Twitter Data lets people embed bits of data in their tweets so that computers can read the data and do cool stuff #twitterdata“.
The syntax behind Twitter Data is simple.
These rules enable folk and bots to embed structured data in a tweet and send it out to the interested world.
I made a new Twitter account (sparkviz) and tweeted some time series data.
A raw data tweet - 13 years of NZ population figures
I also built a proof of concept web-based Twitter client to visualize time series data structured in this format. The client grabs the most recent posts for a specified user. Posts containing structured data are transformed into sparklines – “small, high resolution graphics embedded in a context of words, numbers, images”.
I think there is some merit to this idea. I would love to see visualizations of financial market trends, climate data and river health appear in my Twitter stream, nestled between tweets from my friends and colleagues. Am I a special case though?
I have reservations about this technique. It is difficult to appropriately contextualise the data. In particular, there is no facility to record the dates and time when these measurements were taken. There should also be some way to link to the source dataset. This could be as simple as a link at the end of the tweet. Of course, this consumes valuable characters. I have some ideas but I will let them sit for now.
This Christmas I received a copy of Karen Fonstad’s Atlas of Middle Earth. The work consists of hundreds of two-colour maps describing the imaginary land’s history and geography. Fonstad drew all the figures by hand and used pictorial symbols to depict landforms and vegetation in a style that echoes Tolkien’s original maps. I am particulary fond of her large-scale oblique sketch maps of important locales such as The Inn of the Prancing Pony, Cirith Ungol and Thranduil’s Caverns. Dorky but beautiful.
Sketch map of Thranduil's Caverns ('The Hobbit')
The view from Manukau. Red is more deprived; blue is less deprived.
Since 1994, a group of New Zealand social scientists have attempted to quantify and map socio-economic inequalities. Their work has resulted in the production of four national datasets (based on analyses of the 1991, 1996, 2001 and 2006 censuses) and three atlases of deprivation.
Last night I downloaded the 2006 data from the good folks at Koordinates. The data arrives as a set of NZ census meshblock polygons. I wanted to visualise both deprivation and population. Representing absolute population figures for areas of varying size can result in deeply misleading maps, so I created an additional field to the dataset to represent the population density of each meshblock (i.e. number of people/area of the polygon).
To symbolise the data I stretched the meshblocks into three-dimensional prisms – the taller the prism the greater the population density. Then I symbolised the data according to deprivation. Red prisms are more deprived, blue prisms are less deprived.
Looking over Remuera, Glen Innes and the Tamaki Estuary to Howick
I have uploaded the Google Earth KMZ file to my drop.io account. Download it and play around with the visualization. I recommend turning 3D terrain off as I extruded the meshblock area units from sea-level (using the land as a base distorts the apparent population density heights).
Last weekend I started wondering what a year of NZ earthquakes looked like. This video is my first attempt at animating ten months of 2009 New Zealand earthquake data. Blue circles represent seismic activity recordings. Each event leaves behind a small red dot to show the overall pattern.
Visualising New Zealand Earthquake Data from Chris McDowall on Vimeo.
It amazes me how active our Earth is. It’s easy to forget that we live on a planet that is in constant motion.
I created the frames using Python and matplotlib and stitched the images together with VirtualDub. The animation is licenced under Creative Commons Attribution-Non-Commercial 3.0 NZ.
I acknowledge the New Zealand GeoNet project and its sponsors EQC, GNS Science and LINZ for providing the data. The original data comes from the New Zealand Geonet project and is available for download.
Tiny expedition
On Wednesday night I took the evening train home from Wellington. As the Tararuas hurtled by, I started designing a game on my iPod Touch using a graphics app called TinyPixels [iTunes link]. When the train pulled into the station I had a concept screen for an exploration game controlled with a Lemmings mechanic. Now I want to play it. Perhaps I will have a go at coding it up while I am in transit today.
Some tiny dudes explore a cavern and try not to get into too much trouble.