How to find the right CRS to plot coordinates derived from another map

I've recorded coordinates of points on some maps (see image below) using the juicr package. However, when I come to plot the points in R, they end up in different places (second image below).

If I use juicr to extract positions of the points along the x and y axes, what do I need to do so that the points are projected to the correct locations? I presume this is a CRS issue (?) but how do I know what the right projection to use is?

Here's the code I'm using to plot the coordinates:

#set theme
theme_set(theme_bw())

#create base map
world <- ne_countries(scale = "medium", returnclass = "sf")
class(world)

base.map <- ggplot(data = world) + 
  geom_sf(color = "dark gray", fill = "white") +
  coord_sf(xlim = c(20, 62), ylim = c(22, 48), expand = FALSE) +
  theme(panel.background = element_rect(fill = "#c6dbef")) +
  theme(plot.title = element_text(lineheight=.8, face="bold"), legend.position = "none")


#create Cupressus sempervirens L. map
#sample of coordinates derived from original map

csem$x <- c(21.06574, 21.45329, 21.64706, 21.84083, 22.95502, 23.68166, 24.02076, 23.87543, 24.0692) 
csem$y <- c(31.85996, 31.85996, 31.62298, 31.82047, 34.50628, 34.62478, 34.46679, 34.38779, 34.34829)
 


#plot occurrence mapCupressus sempervirens L. populations
csem.map <- base.map +
  geom_point(data = csem, aes(x = x, y = y), size = 0.75)+
  scale_color_manual(values=c("#56B4E9", "black")) +
  labs(title = "Distribution of Cupressus sempervirens L. recorded by Browicz") + 
  theme(plot.title = element_text(lineheight=.8, face="bold"), 
        plot.caption = element_text(face = "italic"), 
        legend.position = "none") + 
  theme(axis.title  = element_blank()) +
  theme(plot.caption = element_text(hjust = 0))

csem.map

Solution

Your code is working properly, however the coordinates are misaligned; the first 4 points (located on African coast) have latitude misaligned about 0.8 deg.

I have loaded your scanned map to QGIS, referenced it, and to check if the georeferencing was done properly, have generated a grid 2x2 deg. As you can see, it's aligned with the grid on scan:

Using Coordinate Conversion plugin you can check the coordinates of the points:

So, your first 4 points:

newcsem <- data.frame(
  x = c(21.06574, 21.45329, 21.64706, 21.84083),
  y = c(32.62377, 32.55922, 32.32941, 32.65600)
)

I have leaved longitude coordinates unchanged.

library(rnaturalearth)
library(ggplot2)
#set theme
theme_set(theme_bw())

#create base map
world <- ne_countries(scale = "medium", returnclass = "sf")
class(world)
#> [1] "sf"         "data.frame"

base.map <- ggplot(data = world) + 
  geom_sf(color = "dark gray", fill = "white") +
  coord_sf(xlim = c(20, 62), ylim = c(22, 48), expand = FALSE) +
  theme(panel.background = element_rect(fill = "#c6dbef")) +
  theme(plot.title = element_text(lineheight=.8, face="bold"), legend.position = "none")

csem <- data.frame(
  x = c(21.06574, 21.45329, 21.64706, 21.84083, 22.95502, 23.68166, 24.02076, 23.87543, 24.0692),
  y = c(31.85996, 31.85996, 31.62298, 31.82047, 34.50628, 34.62478, 34.46679, 34.38779, 34.34829)
)

newcsem <- data.frame(
  x = c(21.06574, 21.45329, 21.64706, 21.84083),
  y = c(32.62377, 32.55922, 32.32941, 32.65600)
)

csem.map <- base.map +
  geom_point(data = csem, aes(x = x, y = y), size = 0.75)+
  geom_point(data = newcsem, aes(x = x, y = y, color = "blue"), size = 0.75, )+
  scale_color_manual(values=c("#56B4E9", "black")) +
  labs(title = "Distribution of Cupressus sempervirens L. recorded by Browicz") + 
  theme(plot.title = element_text(lineheight=.8, face="bold"), 
        plot.caption = element_text(face = "italic"), 
        legend.position = "none") + 
  theme(axis.title  = element_blank()) +
  theme(plot.caption = element_text(hjust = 0))

csem.map

You can find georeferenced tiff under link

Hope it helps, Grzegorz

^{Created on 2022-09-04 with reprex v2.0.2}