# Bounding geo points using R?

I am new to geodata processing.

For my sample project I am trying to solve next problem.

I have array of geo points. If we place it on plot we can visually see that there are areas where density is higher. I need to find this areas.

I heard about R-tree's and bounding box, but can someone advise me on what way should I go and what material should I read? You could use model-based clustering; e.g. mclust (Manual) is a contributed R package for model-based clustering, classification, and density estimation based on finite normal mixture modeling. It provides functions for parameter estimation via the EM algorithm for normal mixture models with a variety of covariance structures.

``````## create example data set
set.seed(1)
library("MASS")
x <- rbind(mvrnorm(150, c(50,50), 35*diag(c(1, 1))),
mvrnorm(150, c(70,70), 20*matrix(c(1, 0.8, 0.8, 1), 2, 2)))
plot(V2 ~ V1, data=x, col=group)
`````` ``````library("mclust")

res <- Mclust(x[, 1:2])
res
##'Mclust' model object:
## best model: ellipsoidal, varying volume, shape, and orientation (VVV) with 2 components

summary(res)
## ----------------------------------------------------
## Gaussian finite mixture model fitted by EM algorithm
## ----------------------------------------------------
##
## Mclust VVV (ellipsoidal, varying volume, shape, and orientation) model with 2 components:
##
##  log.likelihood   n df   BIC   ICL
##           -1953 300 11 -3968 -3973

##
## Clustering table:
##   1   2
## 152 148
##

plot(res, what="classification")
`````` 