I try to do this ggplot:
<code>library (sf)
library(dplyr)
library(ggplot2)
continents.f.xy <- st_zm(continents.f)
continents_map_SA <- continents.f.xy%>%
dplyr::bind_rows() %>% #bind the list into a data.frame
sf::st_cast(to = "POINT") %>% #convert polygon to a list of points
dplyr::mutate(
long = sf::st_coordinates(geometry)[,1], #retrieve X coord
lat = sf::st_coordinates(geometry)[,2], #retrieve Y coord
group = rep(1, nrow(.)) #create a group column
) %>%
sf::st_drop_geometry() #drop the geometry column
continents_map_SA <- continents_map_SA%>%select(long,lat,group)
continents_map_SA <- fortify(continents_map_SA , region = "South America")
plotactual.high<-ggplot() +
geom_raster(data = ras.actual.df, aes(x = longitude, y = latitude, fill = hpds)) +
scale_fill_gradientn(name="hpds",colours = c("white","red"))+
#scale_y_continuous(breaks=seq(-50, 50, by = 10)) +
#scale_x_continuous(breaks=seq(-100, 0, by = 10)) +
xlab("longitude") + ylab("latitude") +
geom_polygon(data = continents_map_SA, aes(x=long, y = lat, group = group), fill = NA, color = "black") +
annotate(geom="text", x=-45, y=-45, label="Potential area = 9,338.380 km2", color="black", family = c("serif"), size=4.5) +
coord_quickmap() +
theme_bw() +
theme(panel.border = element_blank(), plot.margin = margin(r = 1, l = 1), panel.grid.major = element_blank(),
panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"),
text=element_text(size=16, family="serif"),legend.position="none")
plotactual.high
</code>
<code>library (sf)
library(dplyr)
library(ggplot2)
continents.f.xy <- st_zm(continents.f)
continents_map_SA <- continents.f.xy%>%
dplyr::bind_rows() %>% #bind the list into a data.frame
sf::st_cast(to = "POINT") %>% #convert polygon to a list of points
dplyr::mutate(
long = sf::st_coordinates(geometry)[,1], #retrieve X coord
lat = sf::st_coordinates(geometry)[,2], #retrieve Y coord
group = rep(1, nrow(.)) #create a group column
) %>%
sf::st_drop_geometry() #drop the geometry column
continents_map_SA <- continents_map_SA%>%select(long,lat,group)
continents_map_SA <- fortify(continents_map_SA , region = "South America")
plotactual.high<-ggplot() +
geom_raster(data = ras.actual.df, aes(x = longitude, y = latitude, fill = hpds)) +
scale_fill_gradientn(name="hpds",colours = c("white","red"))+
#scale_y_continuous(breaks=seq(-50, 50, by = 10)) +
#scale_x_continuous(breaks=seq(-100, 0, by = 10)) +
xlab("longitude") + ylab("latitude") +
geom_polygon(data = continents_map_SA, aes(x=long, y = lat, group = group), fill = NA, color = "black") +
annotate(geom="text", x=-45, y=-45, label="Potential area = 9,338.380 km2", color="black", family = c("serif"), size=4.5) +
coord_quickmap() +
theme_bw() +
theme(panel.border = element_blank(), plot.margin = margin(r = 1, l = 1), panel.grid.major = element_blank(),
panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"),
text=element_text(size=16, family="serif"),legend.position="none")
plotactual.high
</code>
library (sf)
library(dplyr)
library(ggplot2)
continents.f.xy <- st_zm(continents.f)
continents_map_SA <- continents.f.xy%>%
dplyr::bind_rows() %>% #bind the list into a data.frame
sf::st_cast(to = "POINT") %>% #convert polygon to a list of points
dplyr::mutate(
long = sf::st_coordinates(geometry)[,1], #retrieve X coord
lat = sf::st_coordinates(geometry)[,2], #retrieve Y coord
group = rep(1, nrow(.)) #create a group column
) %>%
sf::st_drop_geometry() #drop the geometry column
continents_map_SA <- continents_map_SA%>%select(long,lat,group)
continents_map_SA <- fortify(continents_map_SA , region = "South America")
plotactual.high<-ggplot() +
geom_raster(data = ras.actual.df, aes(x = longitude, y = latitude, fill = hpds)) +
scale_fill_gradientn(name="hpds",colours = c("white","red"))+
#scale_y_continuous(breaks=seq(-50, 50, by = 10)) +
#scale_x_continuous(breaks=seq(-100, 0, by = 10)) +
xlab("longitude") + ylab("latitude") +
geom_polygon(data = continents_map_SA, aes(x=long, y = lat, group = group), fill = NA, color = "black") +
annotate(geom="text", x=-45, y=-45, label="Potential area = 9,338.380 km2", color="black", family = c("serif"), size=4.5) +
coord_quickmap() +
theme_bw() +
theme(panel.border = element_blank(), plot.margin = margin(r = 1, l = 1), panel.grid.major = element_blank(),
panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"),
text=element_text(size=16, family="serif"),legend.position="none")
plotactual.high
and I have as a result:
I also use fortify and group inside aes in geom_polygon and arrange.
As you have not supplied copies of your data, this solution only addresses your polygon issue.
For your use case, it is better to create and geospatial objects. In other words, if you want a continent for a map, create a polygon sf. Then you can simply use ggplot2::geom_sf() to plot your data.
There is a lot going on in your code that I won’t address, but your primary issue is that you need to use something like summarise() in conjunction with st_combine() to ‘join’ points in the correct order. Here is a method to create a South America polygon sf using data from the rnaturalearth package. I have used scale = large to return the most detailed option. This can be changed to medium or small if it does not suit. You may be prompted to install another rnaturalearth package for the most detailed data.
<code>library(sf)
library(dplyr)
library(rnaturalearth)
library(ggplot2)
sa_countries <- c("Brazil", "Peru", "Venezuela", "Chile", "Ecuador",
"Bolivia", "Paraguay", "Uruguay", "Guyana", "Suriname",
"French Guiana", "Falkland Islands", "Colombia", "Argentina")
continents_map_SA <- ne_countries(scale = "large") %>%
filter(admin %in% sa_countries) %>%
st_union()
ggplot() +
geom_sf(data = continents_map_SA)
</code>
<code>library(sf)
library(dplyr)
library(rnaturalearth)
library(ggplot2)
sa_countries <- c("Brazil", "Peru", "Venezuela", "Chile", "Ecuador",
"Bolivia", "Paraguay", "Uruguay", "Guyana", "Suriname",
"French Guiana", "Falkland Islands", "Colombia", "Argentina")
continents_map_SA <- ne_countries(scale = "large") %>%
filter(admin %in% sa_countries) %>%
st_union()
ggplot() +
geom_sf(data = continents_map_SA)
</code>
library(sf)
library(dplyr)
library(rnaturalearth)
library(ggplot2)
sa_countries <- c("Brazil", "Peru", "Venezuela", "Chile", "Ecuador",
"Bolivia", "Paraguay", "Uruguay", "Guyana", "Suriname",
"French Guiana", "Falkland Islands", "Colombia", "Argentina")
continents_map_SA <- ne_countries(scale = "large") %>%
filter(admin %in% sa_countries) %>%
st_union()
ggplot() +
geom_sf(data = continents_map_SA)
