Spatial Statistics for roads

Question

I have mule deer-vehicle collision data on highways.  Is it appropriate to use these tools on a road network?  It seems the underlying assumption of randomness would be applied across the extent of the highway not just on the highway.  If so, any pattern of accidents would look non-random to the program.  I have heard about the SANET toolbar that calculates these statistics for networks, but I'm not sure if I have to go there or not.  Does anyone know?

danielmacharia · Answer

Hello @Lauren M Scott

My challenge is slightly different; I want to analyze disease incident clusters' proximity to roads/highways to find out the distance factor - if the nearer the residents are the higher the incidences and the further they are the highways the lower the incidences. Kindly advise what tools are available in 10.2 with Spatial Analyst and 3D Analyst Extensions. Thanks, Daniel

LaurenScott · Answer

If you have ArcGIS 10.2, you can try the new Optimized Hot Spot Analysis tool.  To constrain your analysis to the road network you can:
1) Create a buffer around the road network and use this as your Bounding Polygon when you run Optimized Hot Spot Analysis (you might have to experiment a bit with different buffer widths).
2) Run Optimized Hot Spot Analysis on your accident point data and use the buffer polygon for the parameter called: Bounding Polygons Where the Incidents Are Possible.  This will aggregate the events into fishnet polygons along the road network.  It will automatically identify an appropriate scale of analysis and will apply an FDR correct to results.

Keep in mind that this answers the question: where are there lots of accidents.  It does not take into account differences in the density of the road network or traffic volumes.

There are no doubt many ways to analyze your data; I hope this suggestion is helpful.

Best wishes!
Lauren

Lauren M. Scott, PhD
Esri
Geoprocessing, Spatial Statistics

JeffreyEvans · Answer

No, unfortunately you cannot use tools in the Spatial Statistics toolbox for linear 1D problems. It would violate the random field and spatial randomness (CSR) assumptions associated with every tool. There is a reason that SANET was developed in the first place.