[GIS] Finding Clusters of N Points Within X Distance using ArcGIS Desktop

arcgis-10.0arcgis-desktopclusteringgeoprocessingspatial statistics

We have tried two methods of cluster analysis:

… but neither meets our specification which has these 3 parameters:

a Set of Point features
N points within a Cluster
X distance band to look in

For example "find me the points where each cluster has 10 points within 50 meters" or something to that effect.

ArcGIS 10 has the two tools I’ve linked above but neither seems to address the N points within a cluster part.

Can our requirements be met with other tools in ArcGIS?
Is what I am calling cluster analysis known as a particular clustering type?

We did have a version of this in another application but I really wanted to use the tools within ArcGIS.

Best Answer

Try using the Buffer tool to buffer the points to a tolerance, dissolve to create single polygons for each cluster, and then use a join to count the number of points in the cluster.

Then use the ratio between the area of the cluster and the number of points to apply your parameters.

Related Solutions

[GIS] Determining statistical relationships between rasters using R vs ArcGIS Desktop

I would stick to R. If speed is really a problem ( I doubt so 90.000 is not such a big number) you could try finding relationships between a subset of your data. Actually the first thing I would do is make a plot to look for obvious relationships.

Even if arcgis contains tools to compare rasters, R will always give you a lot more statistical tools.

Eg:

library(rgdal)
map1<-readGDAL('file.asc')
map2<-readGDAL('file2.asc')
samplenr<-sample(length(map1$band1), 1000)
smallset<-data.frame(map1=map1$band1[samplenr],map2=map2$band1[samplenr])
plot(smallset)
lm(map2~map1, smallset)
...

I should actually add that often it is more correct to work with a subset of your data then with your full dataset. In many cases grid cells are not independent from the surrounding data cells, which will result in overly optimistic p values for eg regression fits (you will find more info if you search on declustering).

[GIS] Identifying cluster centroids using ArcGIS Desktop

ArcGIS has a few tools in the Spatial Statistics toolbox that might be useful.

Mean Center

Identifies the geographic center (or the center of concentration) for a set of features.

Median Center

Identifies the location that minimizes overall Euclidean distance to the features in a dataset.

Central Feature

Identifies the most centrally located feature in a point, line, or polygon feature class.

I think the Mean Center would be most useful here when used with the Case Field option.

Best Answer

Related Solutions

[GIS] Determining statistical relationships between rasters using R vs ArcGIS Desktop

[GIS] Identifying cluster centroids using ArcGIS Desktop

Related Question