How to set use ggplot2 to map a raster

Question

I would like to make a plot using R studio similar to the one below (created in Arc Map)

I have tried the following code:

# data processing
library(ggplot2)
# spatial
library(raster)
library(rasterVis)
library(rgdal)

#
test <- raster(paste(datafold,'oregon_masked_tmean_2013_12.tif',sep="")) # read the temperature raster
OR<-readOGR(dsn=ORpath, layer="Oregon_10N") # read the Oregon state boundary shapefile

gplot(test) +  
  geom_tile(aes(fill=factor(value),alpha=0.8)) + 
  geom_polygon(data=OR, aes(x=long, y=lat, group=group), 
               fill=NA,color="grey50", size=1)+
  coord_equal()

The output of that code looks like this:

A couple of things to note. First, the watershed shapefiles are missing from the R version. that is fine.

Second, The darker gray background in the R plot is No Data values. In Arc, they do not display, but in R they display with gplot. They do not display when I use 'plot' from the raster package:

plot(test)

My questions are as follows:

1. How do I get rid of the dark grey NoData fill in the 'gplot' example?
2. How do I set the legend (colorbar) to be reasonable (like in the ArcMap and raster 'plot' legends?)
3. How do I control the colormap?

To note, i have tried many different versions of

scale_fill_brewer
scale_fill_manual
scale_fill_gradient

and so on and so forth but I get errors, for example

br <- seq(minValue(test), maxValue(test), len=8)

gplot(test)+
geom_tile(aes(fill=factor(value),alpha=0.8)) +

scale_fill_gradient(breaks = br,labels=sprintf("%.02f", br)) +

geom_polygon(data=OR, aes(x=long, y=lat, group=group), 
             fill=NA,color="grey50", size=1)+
coord_equal()

Regions defined for each Polygons
Error: Discrete value supplied to continuous scale

Finally, once I have a solution for plotting one of these maps, I would like to plot multiple maps on one figure and create a single colorbar for the entire panel (i.e. one colorbar for all the maps) and I would like to be able to control where the colorbar is located and the size of the colorbar. Here is an example of what I can do with grid.arrange, but I cannot figure out how to set a single colorbar:

r1 <- test
r2 <- test
r3 <- test
r4 <- test

colr <- colorRampPalette(rev(brewer.pal(11, 'RdBu')))

l1 <- levelplot(r1, 
          margin=FALSE,                       
          colorkey=list(
             space='bottom',                   
             labels=list(at=-5:5, font=4),
             axis.line=list(col='black')       
          ),    
          par.settings=list(
             axis.line=list(col='transparent') 
          ),
          scales=list(draw=FALSE),            
          col.regions=viridis,                   
          at=seq(-5, 5, len=101)) +           
   layer(sp.polygons(oregon, lwd=3))

l2 <- levelplot(r2, 
                margin=FALSE,                       
                colorkey=list(
                   space='bottom',                   
                   labels=list(at=-5:5, font=4),
                   axis.line=list(col='black')       
                ),    
                par.settings=list(
                   axis.line=list(col='transparent') 
                ),
                scales=list(draw=FALSE),            
                col.regions=viridis,                   
                at=seq(-5, 5, len=101)) +           
   layer(sp.polygons(oregon, lwd=3))

l3 <- levelplot(r3, 
                margin=FALSE,                       
                colorkey=list(
                   space='bottom',                   
                   labels=list(at=-5:5, font=4),
                   axis.line=list(col='black')       
                ),    
                par.settings=list(
                   axis.line=list(col='transparent') 
                ),
                scales=list(draw=FALSE),            
                col.regions=viridis,                   
                at=seq(-5, 5, len=101)) +           
   layer(sp.polygons(oregon, lwd=3))

l4 <- levelplot(r4, 
                margin=FALSE,                       
                colorkey=list(
                   space='bottom',                   
                   labels=list(at=-5:5, font=4),
                   axis.line=list(col='black')       
                ),    
                par.settings=list(
                   axis.line=list(col='transparent') 
                ),
                scales=list(draw=FALSE),            
                col.regions=viridis,                   
                at=seq(-5, 5, len=101)) +           
   layer(sp.polygons(oregon, lwd=3))

grid.arrange(l1, l2, l3, l4,nrow=2,ncol=2) #use package gridExtra   

The output is this:

The shapefile and raster file are available at the following link:

https://drive.google.com/open?id=0B5PPm9lBBGbDTjBjeFNzMHZYWEU

Many thanks ahead of time.

devtools::session_info() Session info --------------------------------------------------------------------------------------------------------------------- setting value
version R version 3.1.1 (2014-07-10) system x86_64, darwin10.8.0
ui RStudio (0.98.1103)
language (EN)
collate en_US.UTF-8
tz America/Los_Angeles

Packages ------------------------------------------------------------------------------------------------------------------------- package * version date source
bitops 1.0-6 2013-08-17 CRAN (R 3.1.0) colorspace 1.2-6 2015-03-11 CRAN (R 3.1.3) devtools 1.8.0 2015-05-09 CRAN (R 3.1.3) digest 0.6.4 2013-12-03 CRAN (R 3.1.0) ggplot2 * 1.0.1 2015-03-17 CRAN (R 3.1.3) ggthemes * 2.1.2 2015-03-02 CRAN (R 3.1.3) git2r 0.10.1 2015-05-07 CRAN (R 3.1.3) gridExtra 0.9.1 2012-08-09 CRAN (R 3.1.0) gtable 0.1.2 2012-12-05 CRAN (R 3.1.0) hexbin * 1.26.3 2013-12-10 CRAN (R 3.1.0) lattice * 0.20-29 2014-04-04 CRAN (R 3.1.1) latticeExtra * 0.6-26 2013-08-15 CRAN (R 3.1.0) magrittr 1.5 2014-11-22 CRAN (R 3.1.2) MASS 7.3-33 2014-05-05 CRAN (R 3.1.1) memoise 0.2.1 2014-04-22 CRAN (R 3.1.0) munsell 0.4.2 2013-07-11 CRAN (R 3.1.0) plyr 1.8.2 2015-04-21 CRAN (R 3.1.3) proto 0.3-10 2012-12-22 CRAN (R 3.1.0) raster * 2.2-31 2014-03-07 CRAN (R 3.1.0) rasterVis * 0.28 2014-03-25 CRAN (R 3.1.0) RColorBrewer * 1.0-5 2011-06-17 CRAN (R 3.1.0) Rcpp 0.11.2 2014-06-08 CRAN (R 3.1.0) RCurl 1.95-4.6 2015-04-24 CRAN (R 3.1.3) reshape2 1.4.1 2014-12-06 CRAN (R 3.1.2) rgdal * 0.8-16 2014-02-07 CRAN (R 3.1.0) rversions 1.0.0 2015-04-22 CRAN (R 3.1.3) scales * 0.2.4 2014-04-22 CRAN (R 3.1.0) sp * 1.0-15 2014-04-09 CRAN (R 3.1.0) stringi 0.4-1 2014-12-14 CRAN (R 3.1.2) stringr 1.0.0 2015-04-30 CRAN (R 3.1.3) viridis * 0.3.1 2015-10-11 CRAN (R 3.2.0) XML 3.98-1.1 2013-06-20 CRAN (R 3.1.0) zoo 1.7-11 2014-02-27 CRAN (R 3.1.0)

Answer 1

library(ggplot2)
library(raster)
library(rasterVis)
library(rgdal)
library(grid)
library(scales)
library(viridis)  # better colors for everyone
library(ggthemes) # theme_map()

datafold <- "/path/to/oregon_masked_tmean_2013_12.tif"
ORpath <- "/path/to/Oregon_10N.shp"

test <- raster(datafold) 
OR <- readOGR(dsn=ORpath, layer="Oregon_10N") 

You did not include whatever you were using to make test so I did this:

test_spdf <- as(test, "SpatialPixelsDataFrame")
test_df <- as.data.frame(test_spdf)
colnames(test_df) <- c("value", "x", "y")

And, then it's just a matter of sending that + the shapefile to ggplot2:

ggplot() +  
  geom_tile(data=test_df, aes(x=x, y=y, fill=value), alpha=0.8) + 
  geom_polygon(data=OR, aes(x=long, y=lat, group=group), 
               fill=NA, color="grey50", size=0.25) +
  scale_fill_viridis() +
  coord_equal() +
  theme_map() +
  theme(legend.position="bottom") +
  theme(legend.key.width=unit(2, "cm"))

It'll work with any continuous temperature scale now, tho. Viridis is just one of the best ones to come around in a very long while.

You can use the following if you have to use gplot:

gplot(test) +  
  geom_tile(aes(x=x, y=y, fill=value), alpha=0.8) + 
  geom_polygon(data=OR, aes(x=long, y=lat, group=group), 
               fill=NA, color="grey50", size=0.25) +
  scale_fill_viridis(na.value="white") +
  coord_equal() +
  theme_map() +
  theme(legend.position="bottom") +
  theme(legend.key.width=unit(2, "cm"))