[R-sig-Geo] analysis of point patterns

[Lars-Daniel Weber]

> Gesendet: Freitag, 01. Juli 2016 um 03:51 Uhr
> Von: "Adrian Baddeley" <adrian.baddeley at curtin.edu.au>
> An: "r-sig-geo at r-project.org" <r-sig-geo at r-project.org>
> Cc: "Greg McSwiggan" <qfengineers at gmail.com>, "Gopalan Nair" <gopalan.nair at uwa.edu.au>, "Lars-Daniel.Weber at gmx.de" <Lars-Daniel.Weber at gmx.de>
>
> The R package SSN is designed for geostatistics on a network (originally,
> river and stream networks) and has full functionality but is initially
> restricted to networks without loops. However it may also be able to
> handle a general road network, depending on what you need.
> 
> In the R package Œspatstat¹ there is infrastructure for data on linear
> networks (classes linnet, lpp etc). The current release does not cover
> geostatistical methods, but you can compute shortest-path distances in the
> network and construct your own Moran¹s I.

Thanks for your answer. Actually, I don't know what I should do with the data.
Don't laugh please. It was addition data, I've got from a laserscanning session;
read at the bottom for more information.

I thought, Local "Moran's I" would be a good idea, to find High-High clusters.
These would indicate a "bad paving quality" and the actual need to fix it.
High-Low/Low-High outliers might be an indication for: "uh, there might be
problems in the near future".

What do you think? It's neither homework, nor a commercial task. The actual
homework is to work with the LIDAR data (extraction of trees and buildings).
I'm junst interested, what statistics I could run on the data to find a
pattern.

Best regards,
Lars-Daniel