mapping species distribution

[kcuestas]

I am trying to plot longitudes and latitudes on a US map, but I am having a hard time coding it.

devtools::install_github('UrbanInstitute/urbnmapr')

ggplot() + 
  geom_polygon(data = urbnmapr::states, mapping = aes(x = long, y = lat, group = group),
               fill = "grey", color = "white") +
  coord_map(projection = "albers", lat0 = 39, lat1 = 45)

Up to this point, I have a plot of the US with no points. I need to plot my longitudes and latitudes but the rest of the code I am trying to use is not coming out right

saltcedar.longlat %>%
  ggplot(aes(lon, lat)) +
  geom_polygon(color = NA) +
  coord_map(projection = "albers", lat0 = 39, lat1 = 45) +
  labs(title = "Species Distribution")

[andresrcs]

Hi, welcome!

We don't really have enough info to help you out. Could you ask this with a minimal REPRoducible EXample (reprex)? A reprex makes it much easier for others to understand your issue and figure out how to help.

If you've never heard of a reprex before, you might want to start by reading this FAQ:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[jlacko]

You will find the mapping easier if you convert your spatial objects to the format of {sf} package, and then use ggplot2::geom_sf() call.

Such as this example, plotting longitudes and latitudes of three North Carolina cities:

library(sf)
library(tidyverse)
library(USAboundaries)

polygons <- us_boundaries(type="state", resolution = "low") %>% 
  filter(!state_abbr %in% c("PR", "AK", "HI")) %>% # lower 48 only
  st_transform(5070) # Albers projection

points <- data.frame(name = c("Raleigh", "Greensboro", "Wilmington"),
                     x = c(-78.633333, -79.819444, -77.912222),
                     y = c(35.766667, 36.08, 34.223333)) %>% 
  st_as_sf(coords = c("x","y"), crs=4326)

ggplot() +
  geom_sf(data = polygons, fill = NA) +
  geom_sf(data = points, color = "red")