Example for georeferencing a radar dataset#

[1]:

import wradlib as wrl
import xarray as xr
import xradar as xd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib.patches import Rectangle
import warnings

warnings.filterwarnings("ignore")
try:
    get_ipython().run_line_magic("matplotlib inline")
except:
    plt.ion()

/home/runner/micromamba/envs/wradlib-tests/lib/python3.11/site-packages/h5py/__init__.py:36: UserWarning: h5py is running against HDF5 1.14.3 when it was built against 1.14.2, this may cause problems
  _warn(("h5py is running against HDF5 {0} when it was built against {1}, "

1st step: Compute centroid coordinates and vertices of all radar bins in WGS84 (longitude and latitude).

[2]:

swp = (
    xd.model.create_sweep_dataset(rng=1000)
    .swap_dims(time="azimuth")
    .isel(range=slice(0, 100))
)
swp = swp.assign_coords(sweep_mode="azimuthal_surveillance")
swp = swp.wrl.georef.georeference()
swp

We can now generate the polgon vertices of the radar bins - with each vertex in lon/lat coordinates.

[3]:

proj_wgs84 = wrl.georef.epsg_to_osr(4326)
polygons = swp.wrl.georef.spherical_to_polyvert(crs=proj_wgs84, keep_attrs=True)
polygons

… or we can compute the corresponding centroids of all bins - - with each centroid in lon/lat coordinates.

[4]:

centroids = swp.wrl.georef.spherical_to_centroids(crs=proj_wgs84, keep_attrs=True)
centroids

In order to understand how vertices and centroids correspond, we can plot them together.

[5]:

fig = plt.figure(figsize=(16, 16))
site = (polygons.longitude.values, polygons.latitude.values)

aspect = (centroids[..., 0].max() - centroids[..., 0].min()) / (
    centroids[..., 1].max() - centroids[..., 1].min()
)
ax = fig.add_subplot(121, aspect=aspect)
polycoll = mpl.collections.PolyCollection(
    polygons.isel(xy=slice(0, 2)), closed=True, facecolors="None", linewidth=0.1
)
ax.add_collection(polycoll, autolim=True)
# ax.plot(centroids[..., 0], centroids[..., 1], 'r+')
plt.title("Zoom in\n(only possible for interactive plots).")
ax.add_patch(
    Rectangle(
        (site[0] + 0.25, site[1] + 0.25),
        0.2,
        0.2 / aspect,
        edgecolor="red",
        facecolor="None",
        zorder=3,
    )
)
plt.xlim(centroids[..., 0].min(), centroids[..., 0].max())
plt.ylim(centroids[..., 1].min(), centroids[..., 1].max())

ax = fig.add_subplot(122, aspect=aspect)
polycoll = mpl.collections.PolyCollection(
    polygons.isel(xy=slice(0, 2)), closed=True, facecolors="None"
)
ax.add_collection(polycoll, autolim=True)
ax.plot(centroids[..., 0], centroids[..., 1], "r+")
plt.title("Zoom into red box of left plot")
plt.xlim(site[0] + 0.25, site[0] + 0.25 + 0.2)
plt.ylim(site[1] + 0.25, site[1] + 0.25 + 0.2 / aspect)

[5]:

(46.422541, 46.56147892646742)

../../_images/notebooks_georeferencing_georef_10_1.png

2nd step: Reproject the centroid coordinates to Gauss-Krueger Zone 3 (i.e. EPSG-Code 31467).

[6]:

centroids_xyz = centroids.assign_coords(xyz=["x", "y", "z"]).to_dataset("xyz")
centroids_xyz

[7]:

proj_gk3 = wrl.georef.epsg_to_osr(31467)
centroids_xyz = centroids_xyz.wrl.georef.reproject(trg_crs=proj_gk3)
centroids_xyz

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