GSTools provides support for geographic coordinates given by:

- latitude
`lat`

: specifies the north–south position of a point on the Earth's surface - longitude
`lon`

: specifies the east–west position of a point on the Earth's surface

If you want to use this feature for field generation or Kriging, you
have to set up a geographical covariance Model by setting `latlon=True`

in your desired model (see `CovModel`

):

```
import numpy as np
import gstools as gs
model = gs.Gaussian(latlon=True, var=2, len_scale=np.pi / 16)
```

By doing so, the model will use the associated `Yadrenko`

model on a sphere
(see here).
The `len_scale`

is given in radians to scale the arc-length.
In order to have a more meaningful length scale, one can use the `rescale`

argument:

```
import gstools as gs
model = gs.Gaussian(latlon=True, var=2, len_scale=500, rescale=gs.EARTH_RADIUS)
```

Then `len_scale`

can be interpreted as given in km.

A `Yadrenko`

model $C$ is derived from a valid
isotropic covariance model in 3D $C_{3D}$ by the following relation:

$C(\zeta)=C_{3D}\left(2 \cdot \sin\left(\frac{\zeta}{2}\right)\right)$

Where $\zeta$ is the great-circle distance.

## Note¶

`lat`

and `lon`

are given in degree, whereas the great-circle distance
$zeta$ is given in radians.

Note, that $2 \cdot \sin\left(\frac{\zeta}{2}\right)$ is the
chordal distance
of two points on a sphere, which means we simply think of the earth surface
as a sphere, that is cut out of the surrounding three dimensional space,
when using the `Yadrenko`

model.

## Note¶

Anisotropy is not available with the geographical models, since their
geometry is not euclidean. When passing values for `CovModel.anis`

or `CovModel.angles`

, they will be ignored.

Since the Yadrenko model comes from a 3D model, the model dimension will
be 3 (see `CovModel.dim`

) but the `field_dim`

will be 2 in this case
(see `CovModel.field_dim`

).