How to plot the earthquake data on a topographic map

Utpal Kumar   2 minute read      

Read the earthquake data from a csv file and overlay on a topographic map using PyGMT.

In this post, we will first read the earthquake data from a csv file, and then overlay it on a topographic map.

Read the csv file for events data

I have a csv file containing the earthquake events data. The data is obtained from the PyGMT example dataset. It can be obtained and saved locally:

data = pygmt.datasets.load_japan_quakes()
data.to_csv('my_events_data.csv', index=False)

The data is tabular, so we can read it using the pandas’ read_csv method.

import pandas as pd

# this file is retrieved from the pygmt dataset
data = pd.read_csv('my_events_data.csv')
Earthquake data
Earthquake data

Plot the data on a topographic map

First, we define the region based on the data.

# Set the region
region = [
    data.longitude.min() - 1,
    data.longitude.max() + 1,
    data.latitude.min() - 1,
    data.latitude.max() + 1,
]

Then we initialize the pygmt “Figure” object:

fig = pygmt.Figure()

Next, we obtain the high-resolution topographic data and plot it using the normalized etopo1 colormap. We set the minimum elevation of -8000 m and maximum of 5000 m. If there are any topographic regions outside this range then it will be plotted with white. We select the “Mercator” projection with width of 4inch for plotting.

# make color pallets
pygmt.makecpt(
    cmap='etopo1',
    series='-8000/5000/1000', #min elevation of -8000m and max of 5000m
    continuous=True
)

# define etopo data file
topo_data = "@earth_relief_30s"
# plot high res topography
fig.grdimage(
    grid=topo_data,
    region=region,
    projection='M4i',
    shading=True,
    frame=True
)

We next plot the coastlines with shorelines, and also added frame to the map.

fig.coast(shorelines=True, frame=True)

Finally, we plot the data:

# colorbar colormap
pygmt.makecpt(cmap="jet", series=[
              data.depth_km.min(), data.depth_km.max()])
fig.plot(
    x=data.longitude,
    y=data.latitude,
    sizes=0.1*data.magnitude,
    color=data.depth_km,
    cmap=True,
    style="cc",
    pen="black",
)
fig.colorbar(frame='af+l"Depth (km)"')
fig.savefig('my_earthquakes.png')

We plot the data with color represeting the depths of the earthquakes and size of the circles representing the magnitudes of the earthquakes. We added the horizontal colorbar at the bottom.

Earthquake data
Earthquake data

Complete script

import pygmt
import pandas as pd

# this file is retrieved from the pygmt dataset
data = pd.read_csv('my_events_data.csv')

# Set the region
region = [
    data.longitude.min() - 1,
    data.longitude.max() + 1,
    data.latitude.min() - 1,
    data.latitude.max() + 1,
]


fig = pygmt.Figure()
# fig.basemap(region=region, projection="M15c", frame=True)

# make color pallets
pygmt.makecpt(
    cmap='etopo1',
    series='-8000/5000/1000',
    continuous=True
)

# define etopo data file
topo_data = "@earth_relief_30s"
# plot high res topography
fig.grdimage(
    grid=topo_data,
    region=region,
    projection='M4i',
    shading=True,
    frame=True
)
fig.coast(shorelines=True, frame=True)

# colorbar colormap
pygmt.makecpt(cmap="jet", series=[
              data.depth_km.min(), data.depth_km.max()])
fig.plot(
    x=data.longitude,
    y=data.latitude,
    sizes=0.1*data.magnitude,
    color=data.depth_km,
    cmap=True,
    style="cc",
    pen="black",
)
fig.colorbar(frame='af+l"Depth (km)"')
fig.savefig('my_earthquakes.png')

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