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# Using GeoPandas with Rasterio to sample point data#

This example shows how to use GeoPandas with Rasterio. Rasterio is a package for reading and writing raster data.

In this example a set of vector points is used to sample raster data at those points.

The raster data used is Copernicus Sentinel data 2018 for Sentinel data.

[1]:

import geopandas
import rasterio
import matplotlib.pyplot as plt
from shapely.geometry import Point


# Create example vector data#

Generate a geodataframe from a set of points

[2]:

# Create sampling points
points = [Point(625466, 5621289), Point(626082, 5621627), Point(627116, 5621680), Point(625095, 5622358)]
gdf = geopandas.GeoDataFrame([1, 2, 3, 4], geometry=points, crs=32630)


The GeoDataFrame looks like this:

[3]:

gdf.head()

[3]:

0 geometry
0 1 POINT (625466.000 5621289.000)
1 2 POINT (626082.000 5621627.000)
2 3 POINT (627116.000 5621680.000)
3 4 POINT (625095.000 5622358.000)

# Open the raster data#

Use rasterio to open the raster data to be sampled

[4]:

src = rasterio.open('s2a_l2a_fishbourne.tif')


Let’s see the raster data with the point data overlaid.

[5]:

from rasterio.plot import show

fig, ax = plt.subplots()

# transform rasterio plot to real world coords
extent=[src.bounds[0], src.bounds[2], src.bounds[1], src.bounds[3]]
ax = rasterio.plot.show(src, extent=extent, ax=ax, cmap='pink')

gdf.plot(ax=ax)

[5]:

<AxesSubplot: >


# Sampling the data#

Rasterio requires a list of the coordinates in x,y format rather than as the points that are in the geomentry column.

This can be achieved using the code below

[6]:

coord_list = [(x,y) for x,y in zip(gdf['geometry'].x , gdf['geometry'].y)]


Carry out the sampling of the data and store the results in a new column called value. Note that if the image has more than one band, a value is returned for each band.

[7]:

gdf['value'] = [x for x in src.sample(coord_list)]

[7]: