This visualizations shows the geographic location of 1,139,441,531 ip adresses. The locations are grouped by city, divided into four categories according to the total number of ip adresses belonging to a city. The categories are net-metropoles (more than 10,000,000 IPs), net-capitals (1,000,000 up tp 10,000,000 IPs), net-cities (100,000 up 1,000,000 IPs) and net-villages (fewer than 100,000 IPs). IP adresses that cannot be allocated to a city were left out.
Update: I strongly recommend the use of as3-proj instead, which includes far more map projections and lots of other features.
Something you definitely need if you’re planning to create some geospatial visualizations from scratch is map projection. Map projection means the conversion of sphere coordinates (basically pairs of latitude and longitude values) to 2D-screen coordinates. While this is very easy for smaller regions like single countries things are getting complicated if you want to display the whole world. Continue reading →
Figure 1: Visualization of climate changes taken from EagerEyes.org
It’s showing the average world temperature over the last 250 years. Looking at this chart your first thought is something like: Oh my god, it’s getting hot on earth. But wait a minute. An mean temperature increase of 10°C in only 200 years? And what about this hard step around 1950? To answer these questions I had to step deeper into the data. Therefore I made a visualization myself, that simply shows a world map with all weather stations. The temperature range is from -70°C (dark blue) over 0° (white), 10°C (yellow), 32°C (red) to 40°C (dark red). The video goes through 3 loops showing the mean temperature (MT), the summer mean temperature (SMT) and the winter mean temperature (WMT).
One of the major insights you get from seeing this is the unequal and unsteady distribution of weather stations around world and time. While there are only few stations outside europe in 1850 the world is almost complete “filled” in 2000. Did you notice how suddenly africa fills with weather stations around 1950? To get a clearer look at the distribution of weather stations I made this stacked area chart:
Figure 2: Distribution of weather stations over latitude ranges
You can see that there was a steady increasing number of weather stations in the near equator regions. You can even find the peak around 1950 in this chart.
As it’s always warmer near the equator than near the poles and this temperature difference is much bigger than the estimated increase over 200 years, one cannot simply average the data from unevenly distributed weather stations. The more stations you have in africa, the higher your global temperature gets. What you have to do instead is something like taking the average of the average temperature of the weather stations on the same latitude. I think this type of error is called a systematic bias.
So, who is going to make a corrected version of the firstly shown chart?
The last days I worked on a visualization experiment that shows the geographic locations of blog page requests on a world map. Furthermore, the visualization should be animated over time, so one can replay past events or just view the current live data. The last thing I added was an indicator for night and day phases in the world. Here you can see a little preview video showing the current results…
I just made a corrected version of the previosly mentioned visualization using ActionScript. I tried a few map projections and decided to use the Winkel III projection which has a few advantages over the Mercator projection. One of them is the accaptable area distortion of countries near the poles.