问题描述
我想用栅格覆盖 ggplot2 中的 GoogleMaps 底图绘制地图.因此,我像这样使用了 get_map()
和 insert_raster()
:
库(ggplot2)图书馆(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])
是否有可能设置 alpha
并更改 fill
颜色?
结果如下:
即使没有 fortify
也更快:
阅读下面的原始帖子以获取更多信息
来自
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:
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$test, each = 5)),
size = 0,
alpha = 0.5) +
scale_fill_gradientn("RasterValues", colors = topo.colors(255))
How to tackle plotting SPEED if you just need to visualize something
As described below, such plotting might become very slow with large numbers of pixels. Therefore, you might consider to reduce the number of pixels (which in most cases does not really decrease the amount of information in the map) before converting it to polygons. Therefore, raster::aggregate
can be used to reduce the number of pixels to a reasonable amount.
The example shows how the number of pixels is decreased by an order of 4 (i.e. 2 * 2, horizontally * vertically). For further information see ?raster::aggregate
.
r <- aggregate(r, fact = 2)
# afterwards continue with rasterToPolygons(r)...
Original Post:
After a while, I found a way to solve this problem. Converting the raster to polygons! This idea then basically was implemented after Marc Needham's blog post.
Yet, there is one drawback: ggplot gets really slow with large numbers of polygons, which you will inevitably face. However, you can speed things up by plotting into a png()
(or other) device.
Here is a code example:
library(raster)
library(ggplot2)
library(ggmap)
r <- raster(....) # any raster you want to plot
rtp <- rasterToPolygons(r)
rtp@data$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:
这篇关于将光栅添加到ggmap底图:在ggplot2中将alpha(透明度)和填充颜色设置为inset_raster()的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!