I have downloaded my Latitude location history from Google for the time of about three years and now I'd like to, for starters, visualize where I've been.
It turns out that the history contains some outliers. For example, I have been located in China or in Africa, where in fact I haven't been. Other outliers are more in the nature of back-and-forth between a location where I have in fact been and some different location a few hundred meters away.
As you might imagine, the history consists of geospatial positions (latitude/longitude coordinate pairs) and time stamps. The median time interval is 60 seconds, but some intervals are much longer (phone off etc.).
I am wondering if there is a "standard mechanism" ready to be used to remove outliers (locations where I haven't been).
My own ideas end up in some (maybe theoretical) issues. For example, if I look at locations from step to step, I can easily tell what distance I must have travelled in which time. So I could iterate the positions from start to finish and erase points which would have required me to travel faster than humanly possible. But when comparing point n with n+1, how can I tell which one is likely to be the "true" position? And when I simply delete n+1, I will have to re-visit n in order to now look at the movement from n to n+2. And so on.
So I thought, let's hear what the experts have to say. As you can tell, I'm not one. You can talk code (Python) and R to me and I have basic stats knowledge.