producing heat map over Geo locations in R

I want to produce heat map based on some geo-location data on top of the US map using r. The following plot is created over the US map where I used geom_polygon() and geom_point().

How can I convert this to a heat map to get something as follows or similar?

the r script used to produce the above graph:

library(ggplot2);library(maps);
states <- map_data("state")
ggplot() + 
  geom_polygon(data=states, aes(x=long, y=lat, group=group), color="grey", fill="white")+
  geom_point(data=data, aes(x=long, y=lat, color = X, size = X), alpha = 0.5)+
  scale_colour_gradient(low = "red", high = "green")+ 
  scale_x_discrete()+ scale_y_discrete()+ theme_void()+
  facet_wrap( ~type, nrow = 2)

The data I used:

data <- structure(list(X = c(3L, 2L, 6L, 1L, 4L, 4L, 1L, 2L, 5L, 3L, 
0L, 4L, 4L, 3L, 3L, 2L, 4L, 3L, 4L, 4L, 5L, 3L, 4L, 4L, 2L, 3L, 
5L, 2L, 2L, 0L, 1L, 0L, 3L, 4L, 2L, 3L, 0L, 0L, 1L, 3L, 3L, 1L, 
2L, 0L, 0L, 3L, 4L, 3L, 4L, 4L, 3L, 2L, 0L), Y = c(3L, 9L, 7L, 
6L, 3L, 3L, 6L, 5L, 3L, 10L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 4L, 
5L, 4L, 4L, 4L, 5L, 6L, 5L, 4L, 4L, 4L, 2L, 2L, 0L, 2L, 4L, 2L, 
4L, 4L, 3L, 3L, 4L, 7L, 7L, 2L, 3L, 2L, 4L, 3L, 4L, 3L, 3L, 7L, 
3L, 4L, 3L), Z = c(35L, 31L, 31L, 32L, 35L, 36L, 33L, 37L, 32L, 
30L, 39L, 35L, 33L, 35L, 35L, 35L, 30L, 35L, 33L, 31L, 33L, 35L, 
33L, 35L, 35L, 35L, 34L, 36L, 38L, 42L, 43L, 36L, 37L, 36L, 39L, 
35L, 38L, 40L, 39L, 33L, 33L, 41L, 38L, 38L, 41L, 39L, 35L, 35L, 
35L, 34L, 39L, 39L, 39L), type = structure(c(2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L), .Label = c("BF", "DE", "TS", "ZN"), class = "factor"), lat = c(40.77486, 
33.72621, 30.38654, 39.21092, 42.56396, 39.17866, 41.42014, 38.8756, 
39.98261, 32.73808, 39.36327, 42.31465, 42.95051, 38.18899, 26.05433, 
45.21794, 36.13051, 30.00133, 40.7747, 35.48284, 41.32453, 28.45942, 
39.94898, 33.27457, 40.43147, 45.63667, 41.81694, 32.73808, 39.36327, 
42.31465, 42.95051, 35.9996, 34.83323, 41.76574, 29.53539, 39.80981, 
30.34521, 39.09211, 35.95858, 35.92756, 33.78383, 38.18899, 36.13051, 
30.00133, 40.7747, 35.48284, 41.32453, 28.45942, 39.94898, 33.27457, 
40.43147, 45.63667, 41.81694), long = c(-75.94306, -85.44905, 
-97.78677, -77.6507, -72.23171, -84.7458, -82.23518, -104.89844, 
-83.27101, -98.0848, -106.07907, -83.24842, -85.86264, -85.81685, 
-80.99071, -94.50328, -87.32164, -90.19677, -74.68918, -97.61928, 
-96.59226, -81.96995, -75.87195, -112.45182, -80.05054, -123.21019, 
-71.45619, -98.0848, -106.07907, -83.24842, -85.86264, -80.0537, 
-82.39784, -72.7151, -96.11084, -86.41153, -81.82319, -94.8559, 
-83.99512, -115.53027, -119.30347, -85.81685, -87.32164, -90.19677, 
-74.68918, -97.61928, -96.59226, -81.96995, -75.87195, -112.45182, 
-80.05054, -123.21019, -71.45619)), class = "data.frame", row.names = c(NA, 
-53L))

I appreciate your help.

You can use stat_density2d, specifying geom = "polygon". From the comments, it appears that you would like a plot with 4 facets for each of the values X, Y, and Z. Because stat_density2d will only count each instance of X, Y or Z, rather than taking its magnitude into account, we need to make n replicates of each row according to the value at each point.

dfX <- data.frame(long = rep(data$long, data$X), 
                  lat  = rep(data$lat,  data$X), 
                  type = rep(data$type, data$X))

dfY <- data.frame(long = rep(data$long, data$Y), 
                  lat  = rep(data$lat,  data$Y), 
                  type = rep(data$type, data$Y))

dfZ <- data.frame(long = rep(data$long, data$Z), 
                  lat  = rep(data$lat,  data$Z), 
                  type = rep(data$type, data$Z))

Now we can define a plotting function:

plot_mapdata <- function(df)
{
  states <- ggplot2::map_data("state")

  ggplot2::ggplot(data = df, ggplot2::aes(x = long, y = lat)) + 
    ggplot2::lims(x = c(-140, 50), y = c(20, 60)) +
    ggplot2::coord_cartesian(xlim = c(-130, -60), ylim = c(25, 50)) +
    ggplot2::geom_polygon(data = states, ggplot2::aes(x = long, y = lat, group = group), 
                 color = "black", fill = "white") +
    ggplot2::stat_density2d(ggplot2::aes(fill = ..level.., alpha = ..level..), 
                            geom = "polygon") +
    ggplot2::scale_fill_gradientn(colours = rev(RColorBrewer::brewer.pal(7, "Spectral"))) +
    ggplot2::geom_polygon(data = states, ggplot2::aes(x = long, y = lat, group = group), 
                 color = "black", fill = "none") +
    ggplot2::facet_wrap( ~type, nrow = 2) + 
    ggplot2::theme(legend.position = "none")
}

So we can do:

plot_mapdata(dfX)

plot_mapdata(dfY)

plot_mapdata(dfZ)