在ggmap中向地图添加比例的“最简单”方法是什么

Question

说真的，我到处搜索，在地图上编写比例尺太难了…… Adding scale bar to ggplot map

Is there a way to add a scale bar (for linear distances) to ggmap?

是否可以制作一条与我们在函数中选择的缩放预设不同缩放的简单线条？

我有这张简单的地图：

library(ggmap)
pngMAP_df2 = get_map(location = c(-90.5, -0.5), source = "google", zoom = 8,color = "bw")
s = ggmap(pngMAP_df2)
s

我还想在此图中添加 GPS 坐标：

myGPS = data.frame(lat=c( -0.6850556,-0.6854722,  -0.6857778  ),lon=c(-90.22275,-90.22261,  -90.22272)) 

容易实现吗？

我只想添加一些非常简单的东西。就像一条始终为整数的线，表示地图的缩放。

此外，是否可以使用此代码使地图看起来更简单。就像看到白色的水和黑色的陆地轮廓？

谢谢，

Answer 1

类似：

library(rgdal)
library(rgeos)
library(ggplot2)
library(ggthemes)
library(ggsn)

URL <- "https://osm2.cartodb.com/api/v2/sql?filename=public.galapagos_islands&q=select+*+from+public.galapagos_islands&format=geojson&bounds=&api_key="
fil <- "gal.json"
if (!file.exists(fil)) download.file(URL, fil)

gal <- readOGR(fil, "OGRGeoJSON")

# sample some points BEFORE we convert gal
rand_pts <- SpatialPointsDataFrame(spsample(gal, 100, type="random"), data=data.frame(id=1:100))

gal <- gSimplify(gUnaryUnion(spTransform(gal, CRS("+init=epsg:31983")), id=NULL), tol=0.001)

gal_map <- fortify(gal)

# now convert our points to the new CRS
rand_pts <- spTransform(rand_pts, CRS("+init=epsg:31983"))

# and make it something ggplot can use
rand_pts_df <- as.data.frame(rand_pts)

gg <- ggplot()
gg <- gg + geom_map(map=gal_map, data=gal_map,
                    aes(x=long, y=lat, map_id=id),
                    color="black", fill="#7f7f7f", size=0.25)
gg <- gg + geom_point(data=rand_pts_df, aes(x=x, y=y), color="steelblue")
gg <- gg + coord_equal()
gg <- gg + scalebar(gal_map, dist=100, location="topright", st.size=2)
gg <- gg + theme_map()
gg

Answer 2

这将是地图上特定点的完整答案。

library(rgdal)
library(rgeos)
library(ggplot2)
library(ggthemes)
library(ggsn)
myGPS = data.frame(lat=c( -0.6850556,-0.6854722,  -0.6857778  ),lon=c(-90.22275,-90.22261,  -90.22272)) 
coord.deg = myGPS

class(coord.deg)
## "data.frame"
coordinates(coord.deg)<-~lon+lat
class(coord.deg)
## "SpatialPointsDataFrame"
## attr(,"package")
## "sp"

# does it have a projection/coordinate system assigned?
proj4string(coord.deg) # nope
## NA

# Manually tell R what the coordinate system is
proj4string(coord.deg)<-CRS("+proj=longlat +ellps=WGS84 +datum=WGS84")

# now we can use the spTransform function to project. We will project
# the mapdata and for coordinate reference system (CRS) we will
# assign the projection from counties

coord.deg<-spTransform(coord.deg, CRS(proj4string(gal)))
# double check that they match
identical(proj4string(coord.deg),proj4string(gal))
## [1] TRUE
my_pts <- SpatialPointsDataFrame(coords = coord.deg, data=data.frame(id=1:length(coord.deg)))

URL <- "https://osm2.cartodb.com/api/v2/sql?filename=public.galapagos_islands&q=select+*+from+public.galapagos_islands&format=geojson&bounds=&api_key="
fil <- "gal.json"
if (!file.exists(fil)) download.file(URL, fil)
gal <- readOGR(fil, "OGRGeoJSON")
gal <- gSimplify(gUnaryUnion(spTransform(gal, CRS("+init=epsg:31983")), id=NULL), tol=0.001)
gal_map <- fortify(gal)
rand_pts <- spTransform(my_pts, CRS("+init=epsg:31983"))

# ggplot can't deal with a SpatialPointsDataFrame so we can convert back to a data.frame
my_pts <- data.frame(my_pts)
my_pts.final = my_pts[,2:3]
# we're not dealing with lat/long but with x/y
# this is not necessary but for clarity change variable names
names(my_pts.final)[names(my_pts.final)=="lat"]<-"y"
names(my_pts.final)[names(my_pts.final)=="lon"]<-"x"

gg <- ggplot()
gg <- gg + geom_map(map=gal_map, data=gal_map,
                    aes(x=long, y=lat, map_id=id),
                    color="black", fill="#FFFFFF", size=.5)
gg <- gg + coord_equal()
gg <- gg + ggsn:::scalebar(gal_map, dist=50, location="bottomleft", st.size=5)
gg <- gg + theme_map()
gg <- gg + geom_point(data=my_pts.final, aes(x=x, y=y), color="red")
gg