The trouble with making a higher res image is that when you make that lat/lon buckets smaller, you have fewer samples in each one, so the image gets noisier. For the best possible image you'd want to download all the years of data.
The process of making it was quite simple. I zeroed a 2d array of integers, then took all the pickup/dropoff points and incremented the nearest cell. The pixel values are based on the logarithm of the counts, since otherwise everything outside midtown would be pretty much black.
There are some artifacts, like the thin vertical line down the east river. I think that was because of how the data was rounded, i.e. the number of unique longitude values that map to a certain image column.
I wrote this myself with a few hundred lines of C++, though I'm sure there's GIS software out there that will do all this for you with a few clicks.
Can you explain why there is a line going to the airport? Shouldn't the airport be more of an island of light (since I imagine most people aren't getting picked up / dropped off a half mile from the airport)?
Also did you overlay it onto a map? How did you get the angled effect if it's just a grid?
> Can you explain why there is a line going to the airport?
I assume it is because there is a fixed fare to/from JFK so drivers have little incentive to start/stop the meter at the exact pickup/dropoff location.
> Also did you overlay it onto a map?
No. If taxis did not pick up or drop off people on some street, that street does not appear. For example there is an area downtown where there are streets but they have had security barriers since 9/11 thus no taxis.
> How did you get the angled effect if it's just a grid?
None of NYCs grids are exactly north/south/east/west aligned.
If you are interested in what the 2013 data looks like at full resolution, I have a web map of it (https://www.mapbox.com/blog/vector-density/). Haven't updated with the new data yet.