Calculate geographical metrics

Calculate geographical metrics (distance, area) for two or three geographical locations.

Usage

geoarea(lat1, lon1, lat2, lon2, lat3, lon3, earth = 6371008.7714)

geodist(lat1, lon1, lat2, lon2, earth = 6371008.7714)

Arguments

lat1: latitude of the first geographical location, [DD]. Type: assert_double.
lon1: longitude of the first geographical location, [DD]. Type: assert_double.
lat2: latitude of the second geographical location, [DD]. Type: assert_double.
lon2: longitude of the second geographical location, [DD]. Type: assert_double.
lat3: latitude of the third geographical location, [DD]. Type: assert_double.
lon3: longitude of the third geographical location, [DD]. Type: assert_double.
earth: Earth radius, [m]. See Details. Type: assert_numeric.

Value

For geodist:: distance between two geographical locations, [m].
For geoarea:: area of spherical triangle between three geographical locations, [km^2].

Type: assert_double.

Details

geodist calculates distance between two geographical locations on Earth, whereas geoarea calculates the area of spherical triangle between three geographical locations. Both functions use absolute positions of geographical locations described by geographical coordinate system in decimal degrees units denoted as DD. The haversine formula is applied to calculate the distance, and so the spherical model of Earth is considered in both functions.

Since several variants of Earth radius can be accepted, the user is welcome to provide its own value. WGS-84 mean radius of semi-axes, \(R_1\), is the default value.

The resulting distance is expressed in metres (m), whereas the area is expressed in square kilometers(km^2).

Examples

library(pipenostics)

# Consider the longest linear pipeline segment in Krasnoyarsk, [DD]:
pipe <- list(
  lat1 = 55.98320350, lon1 = 92.81257226,
  lat2 = 55.99302417, lon2 = 92.80691885
)

# and some official Earth radii, [m]:
R <- c(
  nominal_zero_tide_equatorial = 6378100.0000,
  nominal_zero_tide_polar      = 6356800.0000,
  equatorial_radius            = 6378137.0000,
  semiminor_axis_b             = 6356752.3141,
  polar_radius_of_curvature    = 6399593.6259,
  mean_radius_R1               = 6371008.7714,
  same_surface_R2              = 6371007.1810,
  same_volume_R3               = 6371000.7900,
  WGS84_ellipsoid_axis_a       = 6378137.0000,
  WGS84_ellipsoid_axis_b       = 6356752.3142,
  WGS84_ellipsoid_curvature_c  = 6399593.6258,
  WGS84_ellipsoid_R1           = 6371008.7714,
  WGS84_ellipsoid_R2           = 6371007.1809,
  WGS84_ellipsoid_R3           = 6371000.7900,
  GRS80_axis_a                 = 6378137.0000,
  GRS80_axis_b                 = 6356752.3141,
  spherical_approx             = 6366707.0195,
  meridional_at_the_equator    = 6335439.0000,
  Chimborazo_maximum           = 6384400.0000,
  Arctic_Ocean_minimum         = 6352800.0000,
  Averaged_center_to_surface   = 6371230.0000
)

# Calculate length of the pipeline segment for different radii:
len <- with(
  pipe, vapply(
    R, geodist, double(1), lat1 = lat1, lon1 = lon1, lat2 = lat2, lon2 = lon2
  )
)

print(range(len))
#> [1] 1140.823 1152.376

# [1] 1140.82331483 1152.37564656 #  [m]


# Consider some remarkable objects on Earth, [DD]:
objects <- rbind(
  Mount_Kailash      = c(lat = 31.069831297551982, lon =  81.31215667724196),
  Easter_Island_Moai = c(lat =-27.166873910247862, lon =-109.37092217323053),
  Great_Pyramid      = c(lat = 29.979229451772856, lon =  31.13418110843685),
  Antarctic_Pyramid  = c(lat = -79.97724194984573, lon = -81.96170583068950),
  Stonehendge        = c(lat = 51.179036665131870, lon =-1.8262150017463086)
)

# Consider all combinations of distances between them:
path <- t(combn(rownames(objects), 2))

d <- geodist(
  lat1 = objects[path[, 1], "lat"],
  lon1 = objects[path[, 1], "lon"],
  lat2 = objects[path[, 2], "lat"],
  lon2 = objects[path[, 2], "lon"]
)*1e-3

cat(
  paste(
    sprintf("%s <--- %1.4f km ---> %s", path[, 1], d, path[, 2]),
    collapse = "\n"
)
)
#> Mount_Kailash <--- 18890.9362 km ---> Easter_Island_Moai
#> Mount_Kailash <--- 4765.7923 km ---> Great_Pyramid
#> Mount_Kailash <--- 14523.7267 km ---> Antarctic_Pyramid
#> Mount_Kailash <--- 6917.4240 km ---> Stonehendge
#> Easter_Island_Moai <--- 16164.4674 km ---> Great_Pyramid
#> Easter_Island_Moai <--- 6010.1422 km ---> Antarctic_Pyramid
#> Easter_Island_Moai <--- 13520.3511 km ---> Stonehendge
#> Great_Pyramid <--- 13726.9374 km ---> Antarctic_Pyramid
#> Great_Pyramid <--- 3595.6153 km ---> Stonehendge
#> Antarctic_Pyramid <--- 15396.3978 km ---> Stonehendge

# Consider two areas 
#         * Bermuda triangle     * Polynesian Triangle
lat1 <- c(Miami   =  25.789106,  Hawaii       =   19.820680)
lon1 <- c(Miami   = -80.226529,  Hawaii       = -155.467989)

lat2 <- c(Bermuda =  32.294887,  NewZeland    =  -43.443219)
lon2 <- c(Bermuda = -64.781380,  NewZeland    =  170.271360)

lat3 <- c(SanJuan =  18.466319,  EasterIsland =  -27.112701)
lon3 <- c(SanJuan = -66.105743,  EasterIsland = -109.349668)

# Area provided by manually operated Google Earth:
GETriangleArea <- c(
  Bermuda    =  1147627.48,  # [km^2]
  Polynesian = 28775517.77   # [km^2]
)

# Show the discrepancy in calculations, [km^2]:
print(geoarea(lat1, lon1, lat2, lon2, lat3, lon3)) 
#> [1]  1147628 28775529
 
 #   Bermuda Polynesian 
 # 0.4673216 11.1030971

Usage

Arguments

Value

Details

See also

Examples