R/GeographicalDistances.R

In villardon/MultBiplotR: Multivariate Analysis Using Biplots in R

# Calculates the geodesic distance between two points specified by radian latitude/longitude using the
# Spherical Law of Cosines (slc)
gcd.slc <- function(long1, lat1, long2, lat2) {
  R <- 6371 # Earth mean radius [km]
  d <- acos(sin(lat1)*sin(lat2) + cos(lat1)*cos(lat2) * cos(long2-long1)) * R
  return(d) # Distance in km
}

# Calculates the geodesic distance between two points specified by radian latitude/longitude using the
# Haversine formula (hf)
gcd.hf <- function(long1, lat1, long2, lat2) {
  R <- 6371 # Earth mean radius [km]
  delta.long <- (long2 - long1)
  delta.lat <- (lat2 - lat1)
  a <- sin(delta.lat/2)^2 + cos(lat1) * cos(lat2) * sin(delta.long/2)^2
  c <- 2 * asin(min(1,sqrt(a)))
  d = R * c
  return(d) # Distance in km
}


# Calculates the geodesic distance between two points specified by radian latitude/longitude using
# Vincenty inverse formula for ellipsoids (vif)
gcd.vif <- function(long1, lat1, long2, lat2) {
  
  # WGS-84 ellipsoid parameters
  a <- 6378137         # length of major axis of the ellipsoid (radius at equator)
  b <- 6356752.314245  # ength of minor axis of the ellipsoid (radius at the poles)
  f <- 1/298.257223563 # flattening of the ellipsoid
  
  L <- long2-long1 # difference in longitude
  U1 <- atan((1-f) * tan(lat1)) # reduced latitude
  U2 <- atan((1-f) * tan(lat2)) # reduced latitude
  sinU1 <- sin(U1)
  cosU1 <- cos(U1)
  sinU2 <- sin(U2)
  cosU2 <- cos(U2)
  
  cosSqAlpha <- NULL
  sinSigma <- NULL
  cosSigma <- NULL
  cos2SigmaM <- NULL
  sigma <- NULL
  
  lambda <- L
  lambdaP <- 0
  iterLimit <- 100
  while (abs(lambda-lambdaP) > 1e-12 & iterLimit>0) {
    sinLambda <- sin(lambda)
    cosLambda <- cos(lambda)
    sinSigma <- sqrt( (cosU2*sinLambda) * (cosU2*sinLambda) +
                        (cosU1*sinU2-sinU1*cosU2*cosLambda) * (cosU1*sinU2-sinU1*cosU2*cosLambda) )
    if (sinSigma==0) return(0)  # Co-incident points
    cosSigma <- sinU1*sinU2 + cosU1*cosU2*cosLambda
    sigma <- atan2(sinSigma, cosSigma)
    sinAlpha <- cosU1 * cosU2 * sinLambda / sinSigma
    cosSqAlpha <- 1 - sinAlpha*sinAlpha
    cos2SigmaM <- cosSigma - 2*sinU1*sinU2/cosSqAlpha
    if (is.na(cos2SigmaM)) cos2SigmaM <- 0  # Equatorial line: cosSqAlpha=0
    C <- f/16*cosSqAlpha*(4+f*(4-3*cosSqAlpha))
    lambdaP <- lambda
    lambda <- L + (1-C) * f * sinAlpha *
      (sigma + C*sinSigma*(cos2SigmaM+C*cosSigma*(-1+2*cos2SigmaM*cos2SigmaM)))
    iterLimit <- iterLimit - 1
  }
  if (iterLimit==0) return(NA)  # formula failed to converge
  uSq <- cosSqAlpha * (a*a - b*b) / (b*b)
  A <- 1 + uSq/16384*(4096+uSq*(-768+uSq*(320-175*uSq)))
  B <- uSq/1024 * (256+uSq*(-128+uSq*(74-47*uSq)))
  deltaSigma = B*sinSigma*(cos2SigmaM+B/4*(cosSigma*(-1+2*cos2SigmaM^2) -
                                             B/6*cos2SigmaM*(-3+4*sinSigma^2)*(-3+4*cos2SigmaM^2)))
  s <- b*A*(sigma-deltaSigma) / 1000
  
  return(s) # Distance in km
}