Contour to GIS¶

The hera.utils.matplotlibCountour module provides toGeopandas, a function that converts matplotlib contour output into a GeoDataFrame. This makes it straightforward to export contour plots as GeoJSON, shapefiles, or any other format supported by geopandas.

Requirements¶

This module requires shapely and geopandas to be installed:

pip install shapely geopandas

Importing¶

from hera.utils.matplotlibCountour import toGeopandas

Basic Usage¶

Generate a contour plot with matplotlib and pass the result to toGeopandas:

import numpy as np
import matplotlib.pyplot as plt
from hera.utils.matplotlibCountour import toGeopandas

# Create sample data on a grid
x = np.linspace(0, 1000, 100)
y = np.linspace(0, 1000, 100)
X, Y = np.meshgrid(x, y)
Z = np.exp(-((X - 500)**2 + (Y - 500)**2) / (2 * 200**2))

# Generate contours
fig, ax = plt.subplots()
cs = ax.contour(X, Y, Z, levels=10)
plt.close(fig)

# Convert to GeoDataFrame
gdf = toGeopandas(cs)
print(gdf.head())

The resulting GeoDataFrame has two columns:

Level -- the contour level value.
contour -- the polygon geometry (set as the active geometry column).

Saving as GeoJSON¶

gdf.to_file("contours.geojson", driver="GeoJSON")

Saving as Shapefile¶

gdf.to_file("contours.shp")

Unit Conversion¶

If your contour coordinates are not in meters, use the inunits parameter to specify the input units. The output will be converted to meters:

from hera.utils.unitHandler import ureg
from hera.utils.matplotlibCountour import toGeopandas

# Contour data is in kilometers
gdf = toGeopandas(cs, inunits=ureg.km)

The default is ureg.m (no conversion).

Working with contourf¶

The same function works with filled contours (contourf):

fig, ax = plt.subplots()
cs = ax.contourf(X, Y, Z, levels=10)
plt.close(fig)

gdf = toGeopandas(cs)

Example: Overlay on a Map¶

Combine with contextily or folium for quick map visualization:

import matplotlib.pyplot as plt

gdf.plot(column="Level", legend=True, cmap="RdYlGn_r")
plt.title("Concentration Contours")
plt.xlabel("Easting (m)")
plt.ylabel("Northing (m)")
plt.show()