Convert From Geographical to Geodesic Coordinates

Description

The method employs geodesic calculations of the distances along geodesic curves, i.e. akin to great-circle curves that go along the surface of the ellipsoidal earth; see geodDist. The results are minimally sensitive to the ellipsoidal geometry assumed, but this is not a matter in serious question today. Note that the results are quite unlike the values returned from a map projection; in the latter case, the results vary greatly across a range of popular projections. Use the present function for things like gridding data or calculating drifter speeds.

Usage

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geodXy(longitude, latitude, longitudeRef = 0, latitudeRef = 0, rotate = 0)

Arguments

longitude

vector of longitudes

latitude

vector of latitudes

longitudeRef

numeric, reference longitude

latitudeRef

numeric, reference latitude

rotate

numeric, counterclockwise angle, in degrees, by which to rotate the (x, y) coordinates about the reference point. This is useful in rotating the coordinate system to align with a coastline, a mean current, etc.

Details

Consider the i-th point in the longitude and latitude vectors. The value of x[i] is inferred from the distance along a geodesic curve from from (longitude[i], latitude[i]) to (longitudeRef[i], latitude[i]), i.e. the distance along a line of constant latitude. Similarly, y[i] is inferred the geodesic distance from (longitude[i], latitude[i]) to (longitude[i], latitudeRef). Once the distances are inferred, signs are calculated from determining the sign of longitude[i]-longitudeRef for x[i] and similarly y[i].

Value

Data frame of x and y, geodesic distance components, measured in metres. See “Details” for the definitions.

Change notification

Until 2015-11-02, the names of the arguments were lon, lat, lon.ref and lat.ref; these were changed to be more in keeping with names in the rest of oce.

Caution

The calculation is devised by the author and is without known precedent in the literature, so users might have to explain it in their publications–hence the detailed discussion below.

This is possibly useful, possibly not. The method changed in Oct, 2015.

Author(s)

Dan Kelley

See Also

geodDist

Other functions relating to geodesy: geodDist, geodGc, geodXyInverse

Examples

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library(oce)
data(section)
lon <- section[["longitude", "byStation"]]
lat<- section[["latitude", "byStation"]]
lon <- lon
lat <- lat
lonR <- lon[1]
latR <- lat[1]
## 1. ellipse
km <- 1e3 # nicer for graphs
xy <- geodXy(lon, lat, lonR, latR) / km
## 2. sphere, with scale tailored to mean local latitude
kmperdeg <- geodDist(0, mean(lat)-0.5, 0, mean(lat)+0.5) # mid-latitude estimate
X <- (lon - lonR) * kmperdeg * cos(lat * pi / 180)
Y <- (lat - latR) * kmperdeg
XY <- list(x=X, y=Y)
## plot, with labels for sphere-ellipse deviations
par(mfrow=c(2,1), mar=c(3, 3, 1, 1), mgp=c(2, 0.7, 0))
plot(lon, lat, asp=1/cos(median(lat*pi/180)))
plot(xy$x, xy$y, asp=1, xlab="x [km]", ylab="y [km]")
rms<- function(x) sqrt(mean(x^2))
mtext(sprintf("RMS dev.: x %.2f km, y %.2f km",
              rms(xy$x-XY$x), rms(xy$y-XY$y)), side=3, line=-1)
mtext(sprintf("RMS dev / span: x %.2g, y %.2g",
              rms(xy$x-XY$x)/diff(range(xy$x)),
              rms(xy$y-XY$y)/diff(range(xy$y))),
      side=3, line=-2)

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