I am trying to map some data in R with the mercator map as a background.
Here is what is I am using, the data points come out fine, but I am not getting the map.
qplot(nt_phi_lambda$longitude, xlab='Longitude',
nt_phi_lambda$latitude, ylab='Latitude',
data=nt_phi_lambda, main='Global Indsutry Break-down',
colour=industry, projection='mercator()', parameters=c(0,0,0))
You need a data.frame with the coordinates of the country boundaries. Just setting projection = 'mercator() does not add a map in mercator projection. See a recent question of mine for an example of how to plot a world map. An example in a few lines of code:
require(maps)
world_map = data.frame(map(plot=FALSE)[c("x","y")])
ggplot(aes(x = x, y = y), data = world_map) + geom_path()
See also the documentation of coord_map.
Related
I ploted an Argentina map and then I took the region I am interested in. But the problem is, I can not plot specific dots in specific latitudes and longitudes. It does not work.
And I want to plot different dots with values all over the map!!
This is the website where I took the data to plot the map: https://gadm.org/download_country_v3.html (I only downloaded a file, that was all).
library(sp)
gadm <- readRDS("gadm36_ARG_1_sf.rds")
gadm<-gadm[2]
plot(gadm)
mapaposta= plot(gadm, col = 'lightgrey', border = 'black',ylim = c(-40,-27),xlim=c(-68,-55))
points(-63.4,-34.1167,col=2)
This is the plot I am getting with no dots on it!!
You need to set the coordinate reference system of the spatial polygons data frame.
library(sp)
# download data from https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_ARG_1_sp.rds
gadm <- readRDS("gadm36_ARG_1_sp.rds")
proj4string(gadm)=CRS("+proj=longlat +datum=WGS84")
plot(gadm, col = 'lightgrey', border = 'black',ylim = c(-40,-27),xlim=c(-68,-55))
points(-63.4,-34.1167,col=2)
I'm currently trying to plot the position of some weather stations in Switzerland. Using pretty standard code with ggmap and geom_point.
register_google(key = "YOUR KEY")
map <- get_map(location='Bern', zoom=12, maptype = "terrain", color = "color")
ggmap(map) + geom_point( aes(x=stations_coord$long, y=stations_coord$lat)
, data = stations_coord, colour = "red", size = 3 )
Problem: All values are misplaced in the plot when comparing to Google Earth
Here is an example for the Bern station.
I really don't understand how this is possible. Also there are no threads on this issue anywhere.
Could anyone help me?
The satellite map and terrain maps use different datums. You are comparing a satellite image with a terrain map - those are different maps and are likely to use different datums. The default datum for google earth (the screencap of your web browser) is WGS84. I don't know what the default datum for the terrain map is but it appears to be different.
Try changing 'maptype = "satellite"' and you will get the same lat/long:
map <- get_map(location='Bern', zoom=12, maptype = "satellite", color = "color")
ggmap(map) + geom_point( aes(x=stations_coord$long, y=stations_coord$lat)
, data = stations_coord, colour = "red", size = 3 )
Futher reading on datums: https://en.wikipedia.org/wiki/Geodetic_datum
A side note: accidents happen all the time because of this. Ships reading GPS are using one datum and their charts (maps) are in another datum, so they aren't where they think they are and can crash into stuff. This can also happen with aircraft and in land navigation.
Bottom line: ggmap uses the datums associated with the map that you tell it to look at. You are telling ggmap to look at one type of map (terrain) and comparing it with another type of map (satellite) - probably different datums.
I would like to plot a series of lat-lon points of a seal track, each coloured according to an attribute, on to a map that shows the bathymetry (100m contours) and coastline. I learnt how to create a map to show the bathymetry+coastline using marmap and ggplot2. The code is here:
dat <- getNOAA.bathy(-58,-62.5,43,46.0,res=0, keep=TRUE)
plot(dat,image=TRUE,bpal = list(c(min(dat), 0, "darkblue", "blue","lightblue"), c(0, max(dat), "gray90","gray10")),drawlabels=TRUE,deep=c(-500,200,0),shallow=c(-500,100,0),step=c(500,100,0),lwd=c(1,1,1),lty=c(1,1,1),land=TRUE)+
scaleBathy(dat, deg=1.232, x="bottomleft", inset=5) #100km
This created a useful map. However, I am stalled over how to add the seal track on to this map.
I could do this in ggmap (using the code below) but I much prefer the marmap map
myLocation <- c(-62.5,43,-58,46)
seal_map2<-get_map(location=myLocation,maptype="watercolor",source="stamen",zoom=10)
ggmap(seal_map2)+
geom_point(data=sealtrack,aes(color=category),size=0.5)+
scale_color_gradientn(colours=rainbow(6), breaks=seq(1,6,by=1))
Any guidance will be much appreciated
You should be able to add the bathymetric info from marmap as a contour layer on your plot after "fortifying" it. Without your data it's difficult to make sure that it works (and the NOAA server is down for me right now):
library(ggplot2)
library(marmap)
dat <- getNOAA.bathy(-58,-62.5,43,46.0,res=0, keep=TRUE)
dat <- fortify(dat)
ggmap(seal_map2) +
geom_contour(dat, aes(x = x, y = y, z = z)) +
geom_point(data=sealtrack,aes(color=category),size=0.5) +
scale_color_gradientn(colours=rainbow(6), breaks=seq(1,6,by=1))
I'm trying to add this plot of a function defined on Veneto (italian region)
obtained by an image and contour:
image(X,Y,evalmati,col=heat.colors(100), xlab="", ylab="", asp=1,zlim=zlimits,main=title)
contour(X,Y,evalmati,add=T)
(here you can find objects: https://dl.dropboxusercontent.com/u/47720440/bounty.RData)
on a Google Map background.
I tried two ways:
PACKAGE RGoogleMaps
I downloaded the map mbackground
MapVeneto<-GetMap.bbox(lonR=c(10.53,13.18),latR=c(44.7,46.76),size = c(640,640),MINIMUMSIZE=TRUE)
PlotOnStaticMap(MapVeneto)
but i don't know the commands useful to add the plot defined by image and contour to the map
PACKAGE loa
I tried this way:
lat.loa<-NULL
lon.loa<-NULL
z.loa<-NULL
nx=dim(evalmati)[1]
ny=dim(evalmati)[2]
for (i in 1:nx)
{
for (j in 1:ny)
{
if(!is.na(evalmati[i,j]))
{
lon.loa<-c(lon.loa,X[i])
lat.loa<-c(lat.loa,Y[j])
z.loa<-c(z.loa,evalmati[i,j])
}
}
}
GoogleMap(z.loa ~ lat.loa*lon.loa,col.regions=c("red","yellow"),labels=TRUE,contour=TRUE,alpha.regions=list(alpha=.5, alpha=.5),panel=panel.contourplot)
but the plot wasn't like the first one:
in the legend of this plot I have 7 colors, and the plot use only these values. image plot is more accurate.
How can I add image plot to GoogleMaps background?
If the use of a GoogleMap map is not mandatory (e.g. if you only need to visualize the coastline + some depth/altitude information on the map), you could use the package marmap to do what you want. Please note that you will need to install the latest development version of marmap available on github to use readGEBCO.bathy() since the format of the files generated when downloading GEBCO files has been altered recently. The data from the NOAA servers is fine but not very accurate in your region of interest (only one minute resolution vs half a minute for GEBCO). Here is the data from GEBCO I used to produce the map : GEBCO file
library(marmap)
# Get hypsometric and bathymetric data from either NOAA or GEBCO servers
# bath <- getNOAA.bathy(lon1=10, lon2=14, lat1=44, lat2=47, res=1, keep=TRUE)
bath <- readGEBCO.bathy("GEBCO_2014_2D_10.0_44.0_14.0_47.0.nc")
# Create color palettes for sea and land
blues <- c("lightsteelblue4", "lightsteelblue3", "lightsteelblue2", "lightsteelblue1")
greys <- c(grey(0.6), grey(0.93), grey(0.99))
# Plot the hypsometric/bathymetric map
plot(bath, land=T, im=T, lwd=.03, bpal = list(c(0, max(bath), greys), c(min(bath), 0, blues)))
plot(bath, n=1, add=T, lwd=.5) # Add coastline
# Transform your data into a bathy object
rownames(evalmati) <- X
colnames(evalmati) <- Y
class(evalmati) <- "bathy"
# Overlay evalmati on the map
plot(evalmati, land=T, im=T, lwd=.1, bpal=col2alpha(heat.colors(100),.7), add=T, drawlabels=TRUE) # use deep= shallow= step= to adjust contour lines
plot(outline.buffer(evalmati),add=TRUE, n=1) # Outline of the data
# Add cities locations and names
library(maps)
map.cities(country="Italy", label=T, minpop=50000)
Since your evalmati data is now a bathy object, you can adjust its appearance on the map like you would for the map background (adjust the number and width of contour lines, adjust the color gradient, etc). plot.bath() uses both image() and contour() so you should be able to get the same results as when you plot with image(). Please take a look at the help for plot.bathy() and the package vignettes for more examples.
I am not realy inside the subject, but Lovelace, R. "Introduction to visualising spatial data in R" might help you
https://github.com/Robinlovelace/Creating-maps-in-R/raw/master/intro-spatial-rl.pdf From section "Adding base maps to ggplot2 with ggmap" with small changes and data from https://github.com/Robinlovelace/Creating-maps-in-R/archive/master.zip
library(dplyr)
library(ggmap)
library(rgdal)
lnd_sport_wgs84 <- readOGR(dsn = "./Creating-maps-in-R-master/data",
layer = "london_sport") %>%
spTransform(CRS("+init=epsg:4326"))
lnd_wgs84_f <- lnd_sport_wgs84 %>%
fortify(region = "ons_label") %>%
left_join(lnd_sport_wgs84#data,
by = c("id" = "ons_label"))
ggmap(get_map(location = bbox(lnd_sport_wgs84) )) +
geom_polygon(data = lnd_wgs84_f,
aes(x = long, y = lat, group = group, fill = Partic_Per),
alpha = 0.5)
library(sp)
library(spdep)
library(ggplot2)
library(ggmap)
library(rgdal)
Get and fiddle with data:
nc.sids <- readShapePoly(system.file("etc/shapes/sids.shp", package="spdep")[1],ID="FIPSNO", proj4string=CRS("+proj=longlat +ellps=clrk66"))
nc.sids=spTransform(nc.sids,CRS("+init=epsg:4326"))
Get background map from stamen.com, plot, looks nice:
ncmap = get_map(location=as.vector(bbox(nc.sids)),source="stamen",maptype="toner",zoom=7)
ggmap(ncmap)
Create a data frame with long,lat,Z, and plot over the map and a blank plot:
ncP = data.frame(coordinates(nc.sids),runif(nrow(nc.sids)))
colnames(ncP)=c("long","lat","Z")
ggmap(ncmap)+geom_point(aes(x=long,y=lat,col=Z),data=ncP)
ggplot()+geom_point(aes(x=long,y=lat,col=Z),data=ncP)
give it some unique ids called 'id' and fortify (with vitamins and iron?)
nc.sids#data[,1]=1:nrow(nc.sids)
names(nc.sids)[1]="id"
ncFort = fortify(nc.sids)
Now, my map and my limits, I want to plot the 74 birth rate:
myMap = geom_map(aes(fill=BIR74,map_id=id),map=ncFort,data=nc.sids#data)
Limits = expand_limits(x=ncFort$long,y=ncFort$lat)
and on a blank plot I can:
ggplot() + myMap + Limits
but on a ggmap I can't:
ggmap(ncmap) + myMap + Limits
# Error in eval(expr, envir, enclos) : object 'lon' not found
Some versions:
> packageDescription("ggplot2")$Version
[1] "0.9.0"
> packageDescription("ggmap")$Version
[1] "2.0"
I can add geom_polygon to ggplot or ggmap and it works as expected. So something is up with geom_map....
The error message is, I think, the result of an inheritance issue. Typically, it comes about when different data frames are used in subsequent layers.
In ggplot2, every layer inherits default aes mappings set globally in the initial call to ggplot. For instance, ggplot(data = data, aes(x = x, y = y)) sets x and y mappings globally so that all subsequent layers expect to see x and y in whatever data frame has been assigned to them. If x and y are not present, an error message similar to the one you got results. See here for a similar problem and a range of solutions.
In your case, it's not obvious because the first call is to ggmap - you can't see the mappings nor how they are set because ggmap is all nicely wrapped up. Nevertheless, ggmap calls ggplot somewhere, and so default aesthetic mappings must have been set somewhere in the initial call to ggmap. It follows then that ggmap followed by geom_map without taking account of inheritance issues results in the error.
So, Kohske's advice in the earlier post applies - "you need to nullify the lon aes in geom_map when you use a different dataset". Without knowing too much about what has been set or how they've been set, it's probably simplest to globber the lot by adding inherit.aes = FALSE to the second layer - the call to geom_map.
Note that you don't get the error message with ggplot() + myMap + Limits because no aesthetics have been set in the ggplot call.
In what follows, I'm using R version 2.15.0, ggplot2 version 0.9.1, and ggmap version 2.1. I use your code almost exactly, except for the addition of inherit.aes = FALSE in the call to geom_map. That one small change allows ggmap and geom_map to be superimposed:
library(sp)
library(spdep)
library(ggplot2)
library(ggmap)
library(rgdal)
#Get and fiddle with data:
nc.sids <- readShapePoly(system.file("etc/shapes/sids.shp", package="spdep")[1],ID="FIPSNO", proj4string=CRS("+proj=longlat +ellps=clrk66"))
nc.sids=spTransform(nc.sids,CRS("+init=epsg:4326"))
#Get background map from stamen.com, plot, looks nice:
ncmap = get_map(location=as.vector(bbox(nc.sids)),source="stamen",maptype="toner",zoom=7)
ggmap(ncmap)
#Create a data frame with long,lat,Z, and plot over the map and a blank plot:
ncP = data.frame(coordinates(nc.sids),runif(nrow(nc.sids)))
colnames(ncP)=c("long","lat","Z")
ggmap(ncmap)+geom_point(aes(x=long,y=lat,col=Z),data=ncP)
ggplot()+geom_point(aes(x=long,y=lat,col=Z),data=ncP)
#give it some unique ids called 'id' and fortify (with vitamins and iron?)
nc.sids#data[,1]=1:nrow(nc.sids)
names(nc.sids)[1]="id"
ncFort = fortify(nc.sids)
#Now, my map and my limits, I want to plot the 74 birth rate:
myMap = geom_map(inherit.aes = FALSE, aes(fill=BIR74,map_id=id), map=ncFort,data=nc.sids#data)
Limits = expand_limits(x=ncFort$long,y=ncFort$lat)
# and on a blank plot I can:
ggplot() + myMap + Limits
# but on a ggmap I cant:
ggmap(ncmap) + myMap + Limits
The result from the last line of code is: