[R-sig-Geo] Point pattern analysis
Virgilio Gomez Rubio
Virgilio.Gomez at uclm.es
Tue Feb 17 09:22:29 CET 2009
> Thanks :) Actually, I'm busy with developing a Location-Based Service
> (a restaurant finder to be precise) utilising SDA. The goal of my
> research is to integrate SDA in an LBS. For this purpose, I've
> gathered about 13,000 unique restaurants in the Netherlands and would
> like to use 3 SDA techniques that enhance the restaurant finder either
> visually and/or analytically. The motivation behind my research is t
> start a discussion on how SDA can be used inside LBSs to enhance the
> services. In this case, to enable users to make better decisions about
> nearby restaurants. One thing that popped in my mind was to use kernel
> density estimation and overlay it on the google/microsoft map to allow
> users to easily grasp the proximity of restaurants.
Perhaps it would be better if you aggregated your data and considered
municipalities in The Netherlands. I guess that area level maps are
easier to understand. What I mean is that your users will find more
meaningful that there are, say, 20 Indian restaurants in Nijmegen than
saying that the intensity for the Indian restaurants have a peak in the
centre of Nijmegen. Regional maps will be helpful if you have a whole
map of the country, but if you allow them to zoom in then you probably
want to show the individual locations of the restaurants.
> Depending on the number of different types of restaurants, you
> may want
> to estimate a different surface for each type. Basically, you
> consider a multivariate point pattern, so that you estimate a
> surface for each type and you compare then to see if they are
> or not. This will address the question of whether the spatial
> distribution of different types of restaurants is the same or
> This is quite interesting. Would this allow me to estimate a surface
> for let's say Italian restaurants vs Greek restaurants? I have ratings
Yes, you can compare the spatial distributions of different types of
> for each restaurant. So a user might want to ask "Where can I find
> good Italian restaurants in the South?" Where good is any rating above
> a 7.0 for example.
This can be more complex because then you may want to produce a map
based on the rating, and then the rating becomes the response variable
in your model...
> You may also want to compute bivariate K-functions (see
> 'k12hat' in
> splancs; 'Kmulti' in spatstat) to detect differences between
> the spatial
> distributions of types of restaurants. This will give you a
> answer to Question 2.
> Would this mean that a kmulti analysis should be applied for each
> restaurant type and thus each subset I wish to test?
You will need to consider each pair of restaurants at a time.
> Have you considered to test for whether a certain type of
> restaurant tends to appear around a particular area of the
> city? For
> example, are Chinese restaurants clustered around Chinatown?
> This is something I'm looking for as well. Considering the fact that
> I'm in the process of developing such an LBS, it would be something
> along the line of: A user takes out his mobile phone. He starts the
> application and the applications looks acquires a position fix. When
> this is done, a user might want to know: "What type of restaurant is
> typical for my current location or current neighbourhood. So,
> analysing whether a certain type of restaurant tends to appear around
> the CURRENT area of the city. Is this possible?
Yes, I guess that you can make a buffer of, say, 300 m around the user's
location and then display your results based on the restaurants included
in that buffer.
> Overall, thanks very much for your reply. I'm really excited about
> using these SDA techniques and am very grateful for your quick reply.
> I'll look up a copy of the papers you mentioned and will read through
> them as soon as I can. When I've successfully analysed the dataset
> with some SDA techniques I can begin the process of constructing the
> appropriate architecture for the LBS. I'll definitely keep you guys
> posted if you're interested.
That would be good. And if you get free vouchers let us now as well!! :)
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