T2 - Population clipping¶

This example shows up to calculate populations contained within a shapefile using a population raster (e.g., WorldPop)

In [1]:

from pathlib import Path
import rastertoolkit
from rastertoolkit import raster_clip
from rastertoolkit.shape import plot_shapes

print(f"rastertoolkit version v{rastertoolkit.__version__}")

from pathlib import Path import rastertoolkit from rastertoolkit import raster_clip from rastertoolkit.shape import plot_shapes print(f"rastertoolkit version v{rastertoolkit.__version__}")

rastertoolkit version v0.3.4

We need both a raster file with the population data along with the shapes.

In [2]:

# Using example DRC shapefile and raster
shape_file = Path("data/COD_LEV02_ZONES")
raster_file = Path("data/cod_2020_1km_aggregated_unadj.tif")

# Using example DRC shapefile and raster shape_file = Path("data/COD_LEV02_ZONES") raster_file = Path("data/cod_2020_1km_aggregated_unadj.tif")

Now we clip. Note that we'll use one of the fieldnames (default: DOTNAME) that is contained in the shapefile to provide an index for the result.

In [3]:

# Clipping raster with shapes (only pop values)
popdict = raster_clip(
    raster_file, shape_file, include_latlon=True, shape_attr="DOTNAME", quiet=True
)

# Clipping raster with shapes (only pop values) popdict = raster_clip( raster_file, shape_file, include_latlon=True, shape_attr="DOTNAME", quiet=True )

Loading data...
Clipping:
1 of 519 (0%) AFRO:DRCONGO:BAS_UELE:AKETI (np.float64(23.755399318383496), np.float64(2.666893086229791)) {'lat': np.float64(2.666893086229791), 'lon': np.float64(23.755399318383496), 'pop': 111915}
519 of 519 (100%) AFRO:DRCONGO:TSHUAPA:YALIFAFO (np.float64(22.433076247922404), np.float64(-1.3598826795835743)) {'lat': np.float64(-1.3598826795835743), 'lon': np.float64(22.433076247922404), 'pop': 73333}

In [4]:

from math import log10

y = [e["lat"] for e in popdict.values()]
x = [e["lon"] for e in popdict.values()]
c = [5 * log10(e["pop"] + 0.1) for e in popdict.values()]
fig, ax = plot_shapes(
    shape_file, linewidth=0.2, alpha=1.0, edgecolor="k", facecolor="None"
)
ax.scatter(x, y, s=c, alpha=0.3)
ax.set_aspect(1)

from math import log10 y = [e["lat"] for e in popdict.values()] x = [e["lon"] for e in popdict.values()] c = [5 * log10(e["pop"] + 0.1) for e in popdict.values()] fig, ax = plot_shapes( shape_file, linewidth=0.2, alpha=1.0, edgecolor="k", facecolor="None" ) ax.scatter(x, y, s=c, alpha=0.3) ax.set_aspect(1)

/workspaces/RasterToolkitDocs/.venv/lib/python3.10/site-packages/matplotlib/collections.py:1008: RuntimeWarning: invalid value encountered in sqrt
  scale = np.sqrt(self._sizes) * dpi / 72.0 * self._factor