Add raster to ggmap base map: set alpha (transparency) and fill color to inset_raster() in ggplot2

Question

I want to plot a map with a raster overlaying a GoogleMaps base map in ggplot2. Therefore, I used get_map() and insert_raster() like this:

library(ggplot2)
library(ggmap)

bm <- ggmap(get_map(location = "Bangkok", maptype = "hybrid"))

bm + inset_raster(as.raster(r), xmin = r@extent[1], xmax = r@extent[2],
                  ymin = r@extent[3], ymax = r@extent[4])

Is there any possibility to set a alpha and change the fill color?

The result looks like this:

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Answer 1

Even Faster without fortify:

read the original post below for further information

From this blog entry I found that we can use spatial polygons directly in ggplot::geom_polygon()

r <- raster(system.file("external/test.grd", package="raster"))
# just to make it reproducible with ggmap we have to transform to wgs84
r <- projectRaster(r, crs = CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs"))

rtp <- rasterToPolygons(r)

bm <- ggmap(get_map(location = bbox(rtp), maptype = "hybrid", zoom = 13))
bm + 
  geom_polygon(data = rtp, 
               aes(x = long, y = lat, group = group, 
                   fill = rep(rtp$test, each = 5)), 
               size = 0, 
               alpha = 0.5)  + 
  scale_fill_gradientn("RasterValues", colors = topo.colors(255)) 

How to tackle plotting SPEED if you just need to visualize something

As described below, such plotting might become very slow with large numbers of pixels. Therefore, you might consider to reduce the number of pixels (which in most cases does not really decrease the amount of information in the map) before converting it to polygons. Therefore, raster::aggregate can be used to reduce the number of pixels to a reasonable amount.

The example shows how the number of pixels is decreased by an order of 4 (i.e. 2 * 2, horizontally * vertically). For further information see ?raster::aggregate.

r <- aggregate(r, fact = 2)
#  afterwards continue with rasterToPolygons(r)...

Original Post:

After a while, I found a way to solve this problem. Converting the raster to polygons! This idea then basically was implemented after Marc Needham's blog post.

Yet, there is one drawback: ggplot gets really slow with large numbers of polygons, which you will inevitably face. However, you can speed things up by plotting into a png() (or other) device.

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Here is a code example:

library(raster)
library(ggplot2)
library(ggmap)

r <- raster(....) # any raster you want to plot
rtp <- rasterToPolygons(r)
rtp@data$id <- 1:nrow(rtp@data)   # add id column for join

rtpFort <- fortify(rtp, data = rtp@data)
rtpFortMer <- merge(rtpFort, rtp@data, by.x = 'id', by.y = 'id')  # join data

bm <- ggmap(get_map(location = "Shanghai", maptype = "hybrid", zoom = 10))

bm + geom_polygon(data = rtpFortMer, 
                  aes(x = long, y = lat, group = group, fill = layer), 
                  alpha = 0.5, 
                  size = 0) +  ## size = 0 to remove the polygon outlines
     scale_fill_gradientn(colours = topo.colors(255))

This results in something like this:

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Answer 2

just been looking into this myself. The issue i encountered was trying to overlay a ggmap output with a raster was the following error:

Error: geom_raster only works with Cartesian coordinates.

the work around to this issue is to use coord_cartesian() as follows:

library(ggplot2)
library(ggmap)

bm <- ggmap(get_map(location = "Bangkok", maptype = "hybrid"))

bm <- bm + geom_raster(...) # insert your raster here

bm <- bm + coord_cartesian()

plot(bm)

I am not sure where your raster r is coming from. for this to work simply convert your raster r into a data frame and add the data according to the geom_raster() instructions, ensure the coordinates are in lat/long (i.e. same as the map).

To answer your question, through geom_raster() you can manipulate alpha and fill.

Hope this helps.

btw this work around was originally raised at this link: https://groups.google.com/forum/embed/#!topic/ggplot2/nqzBX22MeAQ

Morty

Thank you for this answer. However, if Cartesian coordinates are used, the aspect ratio is not maintained. Thus, it is not very suitable for geographic applications – Unlock

Try adding the following: bm <- bm + coord_fixed(xlim=c(a,b),ylim=c(c,d), ratio=1.3), where a,b,c,d are the extents of the view panel you have selected. The key here is setting the ration to 1.3. – Morty

alternatively you just add bm <- bm + coord_fixed(1.3). – Morty