使用 R 中的 Lambert Conformal Conic 投影在 ggplot2 中映射 Arctic/subarctic 个区域

Map Arctic/subarctic regions in ggplot2 with Lambert Conformal Conic projection in R

我正在尝试使用 ggplot2 映射 lat/lon 区域中的 lat/lon 位置,并按类型为它们着色。

这是我正在使用的软件包:

library(ggplot2)
library(rgdal)
library(ggmap)
library(sp)
library(dplyr) 
library(ggspatial) #To use geom_sf to add shapefiles

这是我的数据示例:

dat <- data.frame(
  "Lat" =  c(70.5,74.5,58.5,60.5), 
  "Lon" = c(-21.5,19.0,-161.5,-147.5), 
  "Type"=c("A","B","A","B")
)
dat

我为北极圈创建了一个 shapefile,在此处找到:https://www.arcgis.com/home/item.html?id=f710b74427a14a1d804e90fbf94baed4

ArcticCircle <- sf::st_read("C:/.../LCC_AC.shp")

我正在尝试使用 ggplot2 对此进行映射,但我找不到使用 Lambert Conformal Conic 投影添加底图的方法。

我知道你可以使用 coord_sf() 来指定投影和边界,但我找不到圆锥投影的代码。

p <- ggplot()+
geom_point(data = dat, aes(x = Lon, y = Lat, colour = Type))+
geom_sf(data = ArcticCircle, linetype = "dashed", aes())+
xlab("Longitude")+
ylab("Latitude")+
p

我的地图边界最好是在大约 45 度纬度处围绕北极圈的一圈。如果无法制作圆形边界,则围绕该纬度的矩形也可以。

我是 R 的新手,如有任何帮助,我们将不胜感激!

我在你的代码中发现了一些错误,首先你的 dat 数据框包含字符串格式的 x 和 y 值,而不是数字(这在绘图时没有帮助!)。

其次,与其他GIS软件不同,R不进行动态投影转换!因此,将您的点与 LAT LONG 一起使用对您的 shapefile 不起作用,因为它在不同的 CRS 中!这是 ArcticCircle 的 CRS:

proj4string:    +proj=lcc +lat_1=50 +lat_2=70 +lat_0=40 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs

所以,我所做的就是将您的 LAT LONG 点文件转换为上面显示的 CRS,然后制作 ggplot,我将在下面将所有代码放在一起,并附上注释:

library(ggplot2)
library(rgdal)
library(ggmap)
library(sp)
library(dplyr) 
library(ggspatial) #To use geom_sf to add shapefiles

#### Breaking apart all the values
x = c(-21.5,19.0,-161.5,-147.5)
y = c(70.5,74.5,58.5,60.5)
Type =c("A","B","A","B")

### Creating spatial LAT LONG coordinates, which will be converted to Lambert Conformal Conic Projection below
dat <- data.frame(lon = x, lat = y)

#### Creating LAT LONG SpatialPoints
  coordinates(dat) = c("lon", "lat")
proj4string(dat) <- CRS("+init=epsg:4326")

#### The coordinate reference system, that is used in your shapefile. Will use this when converting the spatial points
polar = "+proj=lcc +lat_1=50 +lat_2=70 +lat_0=40 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs +ellps=GRS80 +towgs84=0,0,0"

### Converting the LAT LONG to the polar CRS shown above
polar_dat = spTransform(dat, polar)
polar_dat = as.data.frame(polar_dat)

#### Adding the Type column back to the data frame, with the new polar coordinates
polar_dat = data.frame(polar_dat, Type)

#### Reading in the Circle Shapefile
ArcticCircle = st_read("P:\SHP\LCC_AC\LCC_AC.shp")

### Putting it togather in ggplot
p <- ggplot()+
  geom_point(data = polar_dat, aes(x = lon, y = lat, colour = Type))+
  geom_sf(data = ArcticCircle, linetype = "dashed", aes())+
  xlab("Longitude")+
  ylab("Latitude")

最后剧情是这样的:

希望对您有所帮助,如果有任何不清楚的地方,请告诉我!

编辑:带有底图的新代码(感谢 Majid 提供的数据)

library(ggplot2)
library(rgdal)
library(ggmap)
library(sp)
library(dplyr) 
library(ggspatial)
library(sf)
library(rnaturalearth)
library(rnaturalearthdata)

#### Breaking apart all the values
x = c(-21.5,19.0,-161.5,-147.5)
y = c(70.5,74.5,58.5,60.5)
Type =c("A","B","A","B")

### Creating spatial LAT LONG coordinates, which will be converted to Lambert Conformal Conic Projection below
dat <- data.frame(lon = x, lat = y)

#### Creating LAT LONG SpatialPoints
coordinates(dat) = c("lon", "lat")
proj4string(dat) <- CRS("+init=epsg:4326")

#### The coordinate reference system, that is used in your shapefile. Will use this when converting the spatial points
polar = "+proj=lcc +lat_1=50 +lat_2=70 +lat_0=40 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs +ellps=GRS80 +towgs84=0,0,0"
b <- bbox(dat)

### Converting the LAT LONG to the polar CRS shown above
polar_dat = spTransform(dat, polar)
polar_dat = as.data.frame(polar_dat)

#### Adding the Type column back to the data frame, with the new polar coordinates
polar_dat = data.frame(polar_dat, Type)

#### Reading in the Circle Shapefile
ArcticCircle = st_read("P:\SHP\LCC_AC\LCC_AC.shp")

### Getting basemap shapefile
world <- ne_countries(scale = "medium", returnclass = "sf")
world_cropped <- st_crop(world, xmin = -180.0, xmax = 180.0,
                         ymin = 45.0, ymax = 90.0)

### Plotting it all togather
p = ggplot(data = world_cropped) + 
  geom_sf(colour = "#6380ad", fill = "#9cb3db") + 
  geom_sf(data = ArcticCircle, linetype = "dashed", aes())+
  geom_point(data = polar_dat, aes(x = lon, y = lat, colour = Type))+
  coord_sf(crs = 
             "+proj=lcc +lat_1=50 +lat_2=70 +lat_0=40 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs +ellps=GRS80 +towgs84=0,0,0")

这可能有帮助:

国家边界数据

library("rnaturalearth")
library("rnaturalearthdata")
world <- ne_countries(scale = "medium", returnclass = "sf")

然后可以裁剪和绘制感兴趣的区域如下:

world_cropped <- st_crop(world, xmin = -180.0, xmax = 180.0,
                          ymin = 45.0, ymax = 90.0)
ggplot(data = world_cropped) + 
  geom_sf() + 
  geom_sf(data = ArcticCircle, linetype = "dashed", aes())+
  geom_sf(data = dat_sf, color = 'red') + 
  coord_sf(crs = 
             "+proj=lcc +lat_1=50 +lat_2=70 +lat_0=40 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs +ellps=GRS80 +towgs84=0,0,0")