Create Distance to Shore (km) Variable from Lat Lon data? - r

Question

I have a data-frame with 3k + data points spread throughout the northern Gulf of Mexico (here I only provide 6). I am trying to create a new variable for is distance to shore (km). I have a shape-file (gulf.shape) which I would like to use but I'm not clear on how.
Here is some data
require(maptools)
require(sp)
library(rgdal)
library(lubridate)
df <- data.frame(Lat = c(26.84853, 28.38329, 28.00364,
29.53840, 29.32030, 26.81622, 25.28146),
Lon = c(-96.55716, -94.29307, -91.21581,
-88.42556, -84.20031, -83.89737, -82.95665))
and I load the shapefile (provided here).
gulf.shape <- "Shape\\stateshigh.shp"
gulf.shape <- maptools::readShapePoly(gulf.shape)
and a quick plot to visualize what I have.
plot(df$Lon, df$Lat,
xlim = c(-97.5, -80.7), ylim = c(25, 30.5),
xlab ="Latitude", ylab = "Longitude",
pch = 20, col="red", cex=1.5)
par(new=T)
sp::plot(gulf.shape, add= T,
xlim = c(-97.5, -80.7), ylim = c(25, 30.5),
xlab ="Latitude", ylab = "Longitude",
col = "gray")
I found a stack overflow post (here), which allowed me to get an answer using the code below. The shape file they use is available here.
require(rgdal) # for readOGR(...); loads package sp as well
require(rgeos) # for gDistance(...)
require(parallel) # for detect cores
require(foreach) # for foreach(...)
require(snow) # for makeCluster(...)
require(doSNOW) # for resisterDoSNOW(...)
wgs.84 <- "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"
mollweide <- "+proj=moll +lon_0=0 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs"
sp.points <- SpatialPoints(df[,c("Lon","Lat")], proj4string=CRS(wgs.84))
coast <- rgdal::readOGR(dsn=".",layer="ne_10m_coastline",p4s=wgs.84);str(coast)
coast.moll <- spTransform(coast,CRS(mollweide))
point.moll <- spTransform(sp.points,CRS(mollweide))
no_cores <- detectCores()
cl <- makeCluster(no_cores,type="SOCK") # create a 4-processor cluster
registerDoSNOW(cl) # register the cluster
get.dist.parallel <- function(n) {
foreach(i=1:n, .combine=c, .packages="rgeos", .inorder=TRUE,
.export=c("point.moll","coast.moll")) %dopar% gDistance(point.moll[i],coast.moll)
}
df$Dis.to.SHORE <- get.dist.parallel(length(sp.points))
df$Dis.to.SHORE <- df$Dis.to.SHORE/1000
df
plot(coast)
points(sp.points,pch=20,col="red")
However, I do not understand the CRS code used in wgs.84 and mollweide and this makes me uneasy about using the data generated with this code. I would also like to use just the gulf.shape file and not the whole world, since there was some suggestion in the previously mentioned stack overflow post that this would be better.
So my questions are:
Are the values I'm getting for distance to shore reasonably accurate (i.e. within 5 - 10m)?
How can I modify the code to utilize the gulf.shape file rather than the whole world?
Can anyone explain the CRS code or point me toward a good reference?
Note that I use parallel computing to speed things up since I have more than 6 data points in reality.

Answer 1

I'll try to answer your 3rd question.
CRS (Coordinate Reference System) is quite important in mapping as it defines the coordinate system of your points. Here's a helpful overview.
https://www.nceas.ucsb.edu/~frazier/RSpatialGuides/OverviewCoordinateReferenceSystems.pdf
For your particular situation, when you change to a different shapefile, you'll need to (1) find out what the CRS is for your shapefile (gulf.shape). Usually, it's in the .prj file or metadata that comes with the shapefile. (2) pick a CRS that's suitable for your goal. You are calculating distance, so an equidistant projection likely is most helpful to you. (3) transform the original crs to the target crs before calculating the distance.
The code you cited was also doing this. The world shapefile came with wgs84 crs; the chosen target crs was mollweide; and it converted wgs84 to mollweide using the spTransform() function.
On another note, related to your 1st question, the accuracy of your calculation is related to the crs you use, but is also related to the scale of your shapefile, and precision of your points (lat/long).