Lat/Lon data with background map

For a given set of points of interest (POI) with lat/lon coordinates, download a background map from contextily and display it in napari together with the POI. Requires geopandas and contextily to be installed.

Tags: gui

Python (.py)

Notebook (.ipynb)

Extra packages required

This example requires additional packages that are not available in typical napari installations. For this example to work in recommended napari installations, you will need to install additional packages: contextily, geopandas. See the plugin manager guide for ways to install additional packages from within napari.

/home/runner/work/docs/docs/.venv/lib/python3.12/site-packages/napari/_qt/qt_event_loop.py:49: UserWarning: System theme detection requires a Qt6 backend. Please switch to PyQt6 or PySide6 to use it.
  theme_type=get_system_theme(),
/home/runner/work/docs/docs/.venv/lib/python3.12/site-packages/napari/_qt/qt_event_loop.py:49: UserWarning: System theme detection requires a Qt6 backend. Please switch to PyQt6 or PySide6 to use it.
  theme_type=get_system_theme(),

import contextily as ctx
import geopandas as gpd
import pandas as pd

import napari

# some point of interest with lat/lon coordinates and a description
df = pd.DataFrame([
    {'lon': 14.3983569, 'lat': 50.0897206, 'sight': 'old castle', 'nature': False, 'stars': 5.0},
    {'lon': 14.4112958, 'lat': 50.0864922, 'sight': 'crowded bridge', 'nature': False, 'stars': 4.0},
    {'lon': 14.4178942, 'lat': 50.0629778, 'sight': 'even older castle', 'nature': False, 'stars': 4.1},
    {'lon': 14.4495206, 'lat': 50.0884767, 'sight': 'nice view from here', 'nature': True, 'stars': 3.2},
    {'lon': 14.4052019, 'lat': 50.1171367, 'sight': 'zoo', 'nature': True, 'stars': 5.0}
])
gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df.lon, df.lat), crs='EPSG:4326')


# convert bounds to crs=3857 (web mercator), and get the background map from contextily
boundsWgs84 = gdf.total_bounds
bounds = gpd.GeoSeries(gpd.GeoDataFrame(geometry=gpd.points_from_xy([boundsWgs84[0], boundsWgs84[2]],
                                              [boundsWgs84[1], boundsWgs84[3]], crs=4326)).to_crs(3857).geometry).total_bounds
bg_map, bg_extent = ctx.bounds2img(bounds[0], bounds[1], bounds[2], bounds[3], zoom=13)

# convert the true bounds of the downloaded map to WGS84 (crs=4326) coordinates
boundsWgsMap = gpd.GeoSeries(gpd.GeoDataFrame(geometry=gpd.points_from_xy([bg_extent[0], bg_extent[1]],
                                              [bg_extent[2], bg_extent[3]], crs=3857)).to_crs(4326).geometry).total_bounds

# display the background map in napari
viewer = napari.Viewer()
viewer.camera.orientation2d=('up','right')
viewer.floating_axes.visible=True
viewer.dims.axis_labels=('lat','lon')
viewer.window.add_plugin_dock_widget('napari', 'Features table widget')

# add the downloaded background map as an image layer, with the correct translation and scale to match the lat/lon coordinates
viewer.add_image(bg_map[:,:,:3][::-1], name='background', opacity=0.9, rgb=True,
                   translate=(boundsWgsMap[1], boundsWgsMap[0]),
                   scale=((boundsWgsMap[3]-boundsWgsMap[1])/bg_map.shape[0], (boundsWgsMap[2]-boundsWgsMap[0])/bg_map.shape[1])

                  )

# add the points of interest as a points layer, using some of the features for coloring
points_layer = viewer.add_points(
    data=df[['lat','lon']].to_numpy(),
    features=df,
    border_color='nature',
    border_color_cycle=['blue', 'green'],
    border_width=0.4,
    face_color='stars',
    face_colormap='reds',
    size=0.002, name='POI'
)

if __name__ == '__main__':
    napari.run()