I read ggmap's documentation and while the density/contour maps look cool, I was wondering whether someone has replicated this example. It creates clusters of points on geographic locations. I have many points to plot on the whole US map, so many that it hides other important information. I am using ggplot and maps to plot these maps. I would appreciate if someone has any examples of cluster plots as given in this example or this example
Related
I have gone through few tutorials and answers here in stackoverflow such as:
Overlap image plot on a Google Map background in R or
Plotting contours on an irregular grid or Geographical heat map of a custom property in R with ggmap or How to overlay global map on filled contour in R language or https://blog.dominodatalab.com/geographic-visualization-with-rs-ggmaps/
They either don't serve my purpose or consider the density of the data to create the image.
I am looking for a way to plot contour on a map of a certain data, and would expect the image to look something like this:
or something like this taken from https://dsparks.wordpress.com/2012/07/18/mapping-public-opinion-a-tutorial/:
I have a data here that gives a contour plot like this in plot_ly but i want this over the map given by latitudes and longitudes.
Please guide me on how this can be done. Any links to potential answers or codes would be helpful.
Ok I did some digging and figured that to plot the data -which in this case are point values randomly distributed across the Latitude and Longitude, one has to make it continuous instead of the discreetly distributed one. To do this I interpolated the data to fill in the gaps, this method is given in Plotting contours on an irregular grid and then take it from there. Now the interpolation here is done using a linear regression, one can use other methods such as IDW, Kriging, Nearest Neighbourhood etc for which R-packages are easily available. These methods are widely used in climatology and topographic analysis. To read more about interpolation methods see this paper.
I would like to use ggmap to plot several data points on top of a koppen-geiger climate map.
The kopper-geiger data and GIS/KMZ maps can be downloaded here:
http://koeppen-geiger.vu-wien.ac.at/present.htm
I've managed to have a code to plot the points on regular maps, obtained through the get_map function but I fail to use other maps such as koppen-geiger.
Any help will be appreaciated!
Your basic problem is that the map you are attmepting to use is an image file that is not georeferenced. So unless you want to go through the unnecessary and probably time consuming process of georeferencing this image yourself, you will be better taking an alternative approach. There are perhaps a few ways to do this. But, unless you have very few data points to overlay on the map which you can place manually using the lat-long grid of the image, then the least painful method will certainly be to redraw the map yourself using the shapefile.
This is not the right place to give you an introductory lesson on GIS, but the basic steps are to
Download shapefile (which is available at the same website as the image you linked)
Project map to desired coordinate system
Plot map, coloring by climate class
Color the ocean layer
Add labels, legend, and graticule, as desired
Overplot with your own climate data, and legend for these.
If you are unsure how to approach any of these steps, then take an introductory course on GIS, and search the Web for instructional materials. You may find this resource useful.
https://cran.r-project.org/doc/contrib/intro-spatial-rl.pdf
I have asked this question in the GIS part of stack exchange https://gis.stackexchange.com/questions/95265/r-how-to-create-a-pre-determined-number-of-identical-square-polygons-to-use-fo - I am asking it here as well as it has also topics of wider interest (e.g. calculation of density) - I hope not to be penalised for this! :)
I am trying to plot crime data density (again!) over a city map, say of NY. As a well known problem there are plenty of examples on this (http://www.obscureanalytics.com/2012/12/07/visualizing-baltimore-with-r-and-ggplot2-crime-data/). These methods plot the crime density through isoclines, while I need to represent it through identical density squares of a pre-determined area (and the area / side length may change from one iteration to the other). This is actually done in commercially available COTS packages like PredPol (see http://www.predpol.com). The reason for representing crime density through squares is that the square are the hotspot areas to be patrolled. The size will influence the overall amount of police people required.
This is what I am trying to achieve:
I would like to be able to create identical square polygons with pre-determined size to overimpose to the map (is it a raster? apologies but I've just started to learn to spell GIS!)
I would like to use the above squares as items to colour as in a choropleth map (i.e. different colouring in relation to frequency of crime in the area), probably using ggplot2 or similar.
This should allow me to see how the density of crimes per square kilometre varies changing the size (i.e. the area) of the square, proposing different patrolling areas.
I do not have a clue if it is possible to use R to create regularly shaped squares polygons of a pre-defined size to use for this (as the code snipped below attests). Any help or links to examples are welcome.
I would be glad to get some indication on alternative ways to calculate the density. I have used the stat_density2 (part of ggplot2) but maybe there are better / faster ways?
(
In hindsight, do I need a density function at all? I just need to count the crimes in a cell and colour-plot it accordingly...)
This is where I got to:
library(rgdal)
library(raster)
library(sp)
#NY boroughs shapefile downloaded from NY website
shp <- readOGR(dsn = "nybb_14a_av", layer = "nybb")
r <- raster(extent(shp))
res(r)=0.05
# using BoroCode as an experiment...
r <- rasterize(shp, field="BoroCode", r)
plot(r)
plot(shp,lwd=10,add=TRUE)
#don't know the result of the above: the laptop basically hangs processing
#plot(r) :)
I have done cluster analysis using hclust(), and now I wish to plot those clusters on to a map. X and Y coordinates of data are available. Finally I have x,y coordinate of the data point, and I have the specific number(cluster to which the data belongs) that must be visible at that specific point. I have plotted Dendrogram already but I wish to plot points using x,y coordinates available.
Suppose a data belongs to the group: 1 and it's coordinates are x1 and y1, I wish to mark/label the point as 1 showing that this specific point belongs to cluster: 1.
Please tell me how to do so, if any better representation of clusters on maps is also available, please tell me about it too.
I am really new to R.
I would suggest coloring each point as the cluster. I am particularly fond of the beautiful graphics in ggplot2 one of the more popular graphics packages.
library(ggplot2)
dat<-data.frame(x=rnorm(10), y=rnorm(10), cluster=rep(c("a","b"),5))
qplot(x=x,y=y,data=dat,color=cluster)
You can do something similar with base R graphics, but the resulting graph is much less attractive IMO. You could certainly "beautify" it, but the simplicity of 1 liner in ggplot2 and the beauty of the output seem to make more sense to me, from a return on code perspective.
plot(x=dat$x, y=dat$y,col=dat$cluster)
legend("topleft",c("a","b"),cex=1,text.col=c("black","red"),bty="n")
I created a network graph from data on flows between US states. For each vertex, I have the lat/long of the state.
I am hoping to recreate a network kind of graph that shows the edges, except that I set the location of each vertex to be their geographic position and have a state boundary map in the background.
I am using to igraph to create my network. There have been some cool mapping examples in ggplot2, so I am wondering if that is an option. I believe I have seen similar options using Pajek, but I am hoping to stay within R.
maps in ggplot2
Any ideas/insight would be appreciated.
Brock
You have multiple packages dealing with maps. The most easy is maps, which gives you the states map. You can plot the vertices over using the coordinates.
map("state")
points(longitute,latitude)
These plots can be manipulated and added to using the base tools, keeping in mind the x axis is the longitude and the y axis is the latitude. edges can be plotted using the segments() function.
In ggplot2 just use the map_data() function, which gives you the shape-data of the map, and the geom_polygon() to add it to the graph in whatever form you want. Again, you can add the vertices and edges using the coordinates with the appropriate ggplot2 function geom_point() and geom_segment(). The code you link at shows you how, or otherwise look at this for an example.
Next to that, you can take a look at the packages maptools, which offers more functionality and, mapproj, which allows for different projections of the same map. You can use these packages as well to calculate geographical distances in a coordinate system.
mapdata contains more databases, and covers basically the whole world. You can work with coordinates pretty nicely.