Spatial statistics - Point process on a network of one-dimensional lines

In summary, the conversation discusses the speaker's data consisting of road accidents and spatial covariates and their initial plan to apply an inhomogeneous Poisson process with covariates. However, they realize that the accidents can only occur on roads and search for information on how to model a point process on a network of one-dimensional lines. They receive an article that proposes a method but they are unsure if it is applicable to their data. They also consider the possibility of neglecting the fact that the points cannot appear everywhere in space and applying an ordinary point process. The goal of the analysis is to identify influential covariates for reducing the number of accidents. They also mention difficulties with dividing the road data into segments and evaluating the effectiveness of the
  • #1
Nemorad
5
0
Hi everyone,

My data consists of road accidents and spatial covariates. Originally i wanted to apply an inhomogenous Poisson process with covariates. Then I realized that the accidents cannot occur everywhere in space, but only on roads. I found an example, that is quite similar to mine. it is said there, that one may model a Point process on a network of one-dimensional lines. Unfortunately it isn't given any more information. I searched the internet for it, but wasn't able to get information, how to explicitly model this.
The area of interest is 70.000 square kilometers and the coordinates of all roads are given.

I would deeply appreciate it, if somebody gave me a hint and/or name some literature on how to tackle this!

Thank you very much in advance!

Regards
Nemorad
 
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  • #2
If you cited the source of the example you found, someone else might be able to find related material by searching the web. It's not clear to me if you are determined to use a "point process on a network" to model the accidents or whether you are merely looking for a good way to model the accidents. For example, I found this PDF on the web:http://www.google.com/url?sa=t&sour...kuzPBQ&usg=AFQjCNEOQ8kyrbhEJhrVrlEczAWYR1ZT8g
 
  • #3
Thank you for the quick reply and the article!

This approach is very interesting.
The example is merely part of a schedule of different scenarios where point processes are applicable. It is found in Gelfand et. al (2010) "Handbook of Spatial Statistics" p 340, but occupies only six lines. I myself am not commited to point processes on networks, yet my professor told me, I should use point processes to model the data. However he isn't that much into the matter. A more practical problem may be, that it would be hard to employ the method in the article you proposed on my data since I would have to divide the road data into segments of say length one kilometer, which may difficult to realize a posteriori.

Thanks again in advance for further hints!
 
  • #4
What is the format of your data?

My guess: Time and GPS location of accidents. Roads given as vectors or as segments with (x,y) data for each end. Will you have trouble with errors in the accident locations that cause them to be off the roads?
 
  • #5
To be honest, I'm not sure about that. The data set containing the roads is a shp-file and the one containing the accidents is a Rda-File for use in the statistical programming language R and structured as you said. Up to this point I didn't manage to look at the raw data of the roads using the open source geographical information system GRASS GIS. However I managed to look at the roads data visually: The roads appear to be curved in it, but maybe they are composed of lines. The file is in vector format.
The problem I was thinking about is, that it may hard to divide the roads into segments of same length, since it would be difficult to decide, what to do at crossroads and, if the roads are not represented as lines but as irregular curves, how to measure the lengths of the roads in general.
The latter problem would also be present for the point process on a network except the software would conduct that automatically.

In case nobody has an idea how to realize the point process on a network: May it be possible to neglect the fact, that the points cannot appear everywhere in space and apply an ordinary point process, since there are hardly any bigger "holes" with no roads on the map?
 
  • #6
It's best not to make many plans about how to model data until you can inspect the data in detail. (You are in very real-world situation for an analyst. Someone hands you some files and expects an analysis or model. The data often doesn't live up to the expectations.)

Nemorad said:
May it be possible to neglect the fact, that the points cannot appear everywhere in space and apply an ordinary point process, since there are hardly any bigger "holes" with no roads on the map?

What is possible depends on how the final simulation will be judged. Who will evaluated it? What is it expected to do? Is the purpose only to demonstrate your knowledge of particular mathematics and skill as a programmer? Or will you do some formal statistical tests to compare the results to real world data?
 
  • #7
You're right, I'd better edit the data for final use in the analysis before finally deciding on what to do. However it'll probably take some time before I reach that point since I'm not very familiar with GRASS GIS and the shp-data set has to be merged with the R data set. I'll get some help from a fellow student who has already experience with GRASS.

The data are indeed real world data. I'm not sure whether I will conduct a simulation too to validate the effectiveness of the method I will finally apply, but probably not. The main task is to identify covariates that are very influental on the occurence of (deer) accidents so that the number can be reduced in the future by setting up signs in areas with many accidents (although the programming code must be correct). The analysis will be evaluated by a professor. I guess the validity of using an ordinary point process compared to applying a more suitable method can only be judged by comparing the two methods, right?

Thanks again for your help!
 
  • #8
I am also working on this. Any suggestions? I cannot find any detailed references :( Thanks!
 

FAQ: Spatial statistics - Point process on a network of one-dimensional lines

1. What is a point process on a network of one-dimensional lines?

A point process on a network of one-dimensional lines is a statistical method used to analyze the distribution and patterns of points (or events) occurring on a network, such as a transportation system or a river network. It takes into account the spatial structure of the network and can be used to understand the underlying processes that generate the observed point patterns.

2. What are the applications of point process on a network of one-dimensional lines?

Point process on a network of one-dimensional lines has various applications, including transportation planning, epidemiology, ecology, and urban planning. It can be used to identify hotspots or areas of high point density, understand the spread of diseases or species, and optimize resource allocation in cities.

3. How is point process on a network of one-dimensional lines different from traditional point process analysis?

The main difference between point process on a network of one-dimensional lines and traditional point process analysis is that the former takes into account the spatial structure of the network, whereas the latter assumes a random spatial distribution of points. Additionally, point process on a network of one-dimensional lines often involves the use of additional network-specific tools and methods.

4. What are some common challenges in applying point process on a network of one-dimensional lines?

One of the main challenges in point process on a network of one-dimensional lines is accounting for the network structure and its effects on the point patterns. This can be complicated by the presence of multiple networks or overlapping networks. Another challenge is selecting appropriate methods for data preprocessing, model selection, and spatial analysis.

5. How can point process on a network of one-dimensional lines be used to inform decision-making?

Point process on a network of one-dimensional lines can provide valuable insights for decision-making in various fields. For example, it can help identify locations for new transportation infrastructure based on point density and travel patterns, inform public health interventions by identifying hotspots of disease transmission, or optimize resource allocation in urban planning by understanding the distribution of urban amenities.

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